Datasets:

AIAT
/

Machima-humangendataset

	thai_instruction,eng_instruction,table,sql,pandas,real_table
	Ticket ID สำหรับบันทึกแรกคือ 1 หรือไม่ ,Is the Ticket ID for the first record 1?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Ticket_ID'].iloc[0] == 1,customer
	ลูกค้าที่มีอายุสูงสุดมากกว่า 70 ปีใช่หรือไม่,Is the highest customer age greater than 70?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Customer_Age'].max() > 70,customer
	คะแนนความพึงพอใจของลูกค้าต่ำสุดน้อยกว่า 2 หรือไม่ ,Is the lowest customer satisfaction rating less than 2?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Customer_Satisfaction_Rating'].min() < 2,customer
	ลูกค้าท่านใดมีสถานะตั๋ว 'ปิด' แล้วบ้าง ,Does any customer have 'Closed' ticket status?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Ticket_Status'].str.contains('Closed').any(),customer
	จำนวนตั๋วทั้งหมดน้อยกว่า 20 ใบใช่หรือไม่ ,Is the total number of tickets less than 20?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,len(data) < 20,customer
	มีลูกค้าชื่อ 'เจสสิก้า ริออส' มั้ย ,Is there a customer named 'Jessica Rios'?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Customer_Name'].str.contains('Jessica Rios').any(),customer
	'การสอบถามการเรียกเก็บเงิน' เป็นตั๋วประเภทหนึ่งหรือไม่,Is 'Billing inquiry' a type of ticket?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Ticket_Type'].str.contains('Billing inquiry').any(),customer
	'อีเมล' เป็นช่องทางตั๋วสำหรับบันทึกที่ห้าหรือไม่ ,Is 'Email' a ticket channel for the fifth record?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Ticket_Channel'].iloc[4] == 'Email',customer
	เป็นเวลาตอบกลับครั้งแรกสำหรับบันทึกครั้งแรกในปี 2023 หรือไม่ ,Is the first response time for the first record in 2023?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['First_Response_Time'].iloc[0].year == 2023,customer
	ตั๋วใด ๆ ที่ถูกทำเครื่องหมายว่า 'สำคัญ' หรือไม่ ,Is any ticket marked as 'Critical'?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Ticket_Priority'].str.contains('Critical').any(),customer
	มีลูกค้าอายุเกิน 50 บ้างไหม ,Are there any customers older than 50?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Customer_Age'] > 50,customer
	มีตั๋วจากลูกค้าผู้หญิงหรือเปล่า ,Is any ticket from a female customer?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Customer_Gender'].str.contains('Female').any(),customer
	มีการซื้อใดๆ ในปี 2021 หรือไม่ ,Has any purchase been made in 2021?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Date_of_Purchase'].dt.year == 2021,customer
	มีสินค้าที่ซื้อชื่อ 'GoPro Hero' หรือไม่ ,Is there any product purchased named 'GoPro Hero'?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Product_Purchased'].str.contains('GoPro Hero').any(),customer
	บันทึกล่าสุดมีคะแนนความพึงพอใจของลูกค้าสูงกว่า 4 หรือไม่ ,Does the last record have a customer satisfaction rating above 4?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Customer_Satisfaction_Rating'].iloc[-1] > 4,customer
	ตั๋วใดๆ เกี่ยวข้องกับปัญหาทางเทคนิคหรือไม่ ,Does any ticket involve a technical issue?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Ticket_Type'].str.contains('Technical issue').any(),customer
	อายุเฉลี่ยของลูกค้าต่ำกว่า 30 ปีหรือไม่ ,Is the average customer age below 30?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Customer_Age'].mean() < 30,customer
	มีลูกค้าที่ได้รับอีเมลจาก 'example.com' หรือไม่,Is there any customer with an email from 'example.com'?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Customer_Email'].str.contains('example.com').any(),customer
	ตั๋วทั้งหมดเปิดหรือปิดแล้ว ,Are all tickets either open or closed?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,(data['Ticket_Status'] == 'Open') \| (data['Ticket_Status'] == 'Closed'),customer
	ลำดับความสำคัญของตั๋วใบที่สามต่ำหรือไม่ ,Is the third ticket's priority low?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Ticket_Priority'].iloc[2] == 'Low',customer
	มีตั๋วที่ส่งทางอีเมลหรือไม่ ,Are there any tickets submitted via email?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Ticket_Channel'].str.contains('Email').any(),customer
	คะแนนความพึงพอใจของลูกค้าสำหรับตั๋วใบแรกน้อยกว่า 5 หรือไม่ ,Is the customer satisfaction rating for the first ticket less than 5?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Customer_Satisfaction_Rating'].iloc[0] < 5,customer
	มีการลงมติสำหรับตั๋วใบแรกหรือไม่ ,Has the resolution for the first ticket been provided?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,pd.notna(data['Resolution'].iloc[0]),customer
	มีลูกค้าคนไหนอายุต่ำกว่า 25 ปี บ้างมั้ยคะ ,Is there any customer under 25 years old?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Customer_Age'] < 25,customer
	ชุดข้อมูลมีตั๋วมากกว่า 10 ใบหรือไม่,Are there more than 10 tickets in the dataset?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,len(data) > 10,customer
	ตั๋วใด ๆ มีคะแนนความพึงพอใจอยู่ที่ 5 หรือไม่ ,Is any ticket rated with a satisfaction rating of 5?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Customer_Satisfaction_Rating'] == 5,customer
	มีตั๋วที่มีปัญหาที่ยังไม่ได้รับการแก้ไขหรือไม่ ,Are there any tickets with unresolved issues?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Ticket_Status'].str.contains('Pending').any(),customer
	มีตั๋วใดบ้างที่ได้รับการแก้ไขภายในหนึ่งวันนับจากการตอบกลับครั้งแรก ,Has any ticket been resolved within a day of its first response?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,(data['Time_to_Resolution'] - data['First_Response_Time']).dt.days < 1,customer
	ตั๋วใดๆ มีสถานะลำดับความสำคัญสูงหรือไม่ ,Do any tickets have a high priority status?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Ticket_Priority'].str.contains('High').any(),customer
	มีผลิตภัณฑ์ที่ซื้อเรียกว่า 'Microsoft Office' หรือไม่,Is there a product purchased called 'Microsoft Office'?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Product_Purchased'].str.contains('Microsoft Office').any(),customer
	เวลาสูงสุดในการแก้ไขคือมากกว่า 10 วันหรือไม่,Is the maximum time to resolution over 10 days?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,(data['Time_to_Resolution'] - data['First_Response_Time']).dt.days.max() > 10,customer
	ลูกค้าท่านใดให้คะแนนความพึงพอใจ 1 บ้าง ,Has any customer given a satisfaction rating of 1?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Customer_Satisfaction_Rating'] == 1,customer
	มีตั๋วเกี่ยวกับ 'ข้อมูลสูญหาย' หรือไม่ ,Is there a ticket concerning 'Data loss'?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Ticket_Subject'].str.contains('Data loss').any(),customer
	ชุดข้อมูลมีตั๋วจากปี 2022 หรือไม่,Does the dataset contain any tickets from 2022?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Date_of_Purchase'].dt.year == 2022,customer
	มีบันทึกของลูกค้าชื่อ 'อเล็กซานเดอร์ คาร์โรลล์' หรือไม่ ,Is there a record of a customer named 'Alexander Carroll'?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Customer_Name'].str.contains('Alexander Carroll').any(),customer
	ตั๋วใบแรกส่งผ่านโซเชียลมีเดียหรือไม่ ,Is the first ticket submitted through social media?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Ticket_Channel'].iloc[0] == 'Social media',customer
	มีตั๋วที่มีลำดับความสำคัญที่มีป้ายกำกับว่า 'ปานกลาง' หรือไม่ ,Is there a ticket with a priority labeled as 'Moderate'?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Ticket_Priority'].str.contains('Moderate').any(),customer
	คะแนนความพึงพอใจของลูกค้าเฉลี่ยมากกว่า 3 หรือไม่ ,Does the customer satisfaction rating average more than 3?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Customer_Satisfaction_Rating'].mean() > 3,customer
	ตั๋วทั้งหมดเป็นของลูกค้าผู้ชายหรือเปล่า ,Are all tickets from male customers?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Customer_Gender'].unique() == ['Male'],customer
	มีตั๋วใดบ้างที่ได้รับการกำหนดสถานะลำดับความสำคัญเป็น 'ด่วน' หรือไม่ ,Has any ticket been assigned a priority status of 'Urgent'?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Ticket_Priority'].str.contains('Urgent').any(),customer
	มีการส่งตั๋วในเดือนมิถุนายน 2023 หรือไม่ ,Is there a ticket submitted in June 2023?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['First_Response_Time'].dt.month == 6 and data['First_Response_Time'].dt.year == 2023,customer
	ตั๋วใดบ้างที่มีเวลาในการแก้ไขปัญหาเกิน 48 ชั่วโมง ,Do any tickets have a resolution time over 48 hours?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,(data['Time_to_Resolution'] - data['First_Response_Time']).dt.total_seconds() / 3600 > 48,customer
	Ticket ID 10 เชื่อมโยงกับลูกค้าที่มีอายุต่ำกว่า 30 ปีหรือไม่,Is the Ticket ID 10 associated with a customer under 30?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,"data.loc[data['Ticket_ID'] == 10, 'Customer_Age'].iloc[0] < 30",customer
	มีลูกค้ารายใดที่ซื้อผลิตภัณฑ์มากกว่าหนึ่งรายการหรือไม่ ,Has any customer purchased more than one product?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Customer_Email'].duplicated().any(),customer
	มีตั๋วที่ยังไม่ได้รับการแก้ไขจากปี 2020 หรือไม่ ,Are there any unresolved tickets from 2020?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,(data['Date_of_Purchase'].dt.year == 2020) & (data['Ticket_Status'].str.contains('Pending').any()),customer
	ตั๋วประเภท 'ปัญหาทางเทคนิค' ที่พบบ่อยที่สุดใช่หรือไม่,Is the most common ticket type 'Technical issue'?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Ticket_Type'].mode()[0] == 'Technical issue',customer
	มีตั๋วจากลูกค้าอายุ 40 พอดีหรือไม่,Is there a ticket from a customer aged exactly 40?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Customer_Age'] == 40,customer
	ลูกค้ารายใดมีคะแนนความพึงพอใจต่ำกว่า 3 หรือไม่ ,Does any customer have a satisfaction rating below 3?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Customer_Satisfaction_Rating'] < 3,customer
	มีตั๋วใดบ้างที่มีการแก้ไขเกี่ยวกับ 'การเข้าถึงบัญชี' หรือไม่,Are there any tickets with a resolution involving 'account access'?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,"data['Resolution'].str.contains('account access', case=False, na=False).any()",customer
	มีลูกค้าชื่อ 'Christina Dillon' ที่มีตั๋วสอบถามเรื่องการเรียกเก็บเงินหรือไม่ ,Is there a customer named 'Christina Dillon' with a billing inquiry ticket?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,(data['Customer_Name'] == 'Christina Dillon') & (data['Ticket_Type'] == 'Billing inquiry'),customer
	มีตั๋วจากลูกค้าที่มีอายุมากกว่า 80 ปีหรือไม่ ,Is there any ticket from a customer over 80 years old?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Customer_Age'] > 80,customer
	ลูกค้ารายแรกชื่อ 'มาริสา โอเบรียน' หรือเปล่าคะ ,Is the first customer named 'Marisa Obrien'?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Customer_Name'].iloc[0] == 'Marisa Obrien',customer
	ตั๋วใดบ้างที่เกี่ยวข้องกับ 'ความเข้ากันได้ของอุปกรณ์ต่อพ่วง' หรือไม่,Are any tickets related to 'Peripheral compatibility'?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Ticket_Subject'].str.contains('Peripheral compatibility').any(),customer
	มีผลิตภัณฑ์ใดบ้างที่ซื้อชื่อ 'Dell XPS',Is any product purchased named 'Dell XPS'?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Product_Purchased'].str.contains('Dell XPS').any(),customer
	ตั๋วใด ๆ ได้รับการแก้ไขภายใน 5 ชั่วโมงหลังจากการตอบกลับครั้งแรกหรือไม่ ,Has any ticket been resolved within 5 hours of its first response?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,(data['Time_to_Resolution'] - data['First_Response_Time']).dt.total_seconds() / 3600 < 5,customer
	มีตั๋วจากลูกค้าที่มีโดเมนอีเมล '@example.org' หรือไม่,Is there a ticket from a customer with the email domain '@example.org'?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Customer_Email'].str.contains('@example.org').any(),customer
	มีตั๋ว 15 ใบในชุดข้อมูลหรือไม่,Are there exactly 15 tickets in the dataset?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,len(data) == 15,customer
	มีลูกค้ารายใดจากชุดข้อมูลที่ได้รับคะแนนความพึงพอใจตั้งแต่ 4 ขึ้นไป ,Has any customer from the dataset given a satisfaction rating of 4 or higher?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Customer_Satisfaction_Rating'] >= 4,customer
	มีตั๋วที่มีลำดับความสำคัญ 'ต่ำ' ที่ถูกปิดแล้วหรือไม่ ,Is there a ticket with a 'Low' priority that has been closed?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,((data['Ticket_Priority'] == 'Low') & (data['Ticket_Status'] == 'Closed')).any(),customer
	ชุดข้อมูลรวมตั๋วใดๆ ที่เพิ่มขึ้นในเดือนมกราคมหรือไม่,Does the dataset include any tickets raised in January?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Date_of_Purchase'].dt.month == 1,customer
	อายุของลูกค้าทุกคนในชุดข้อมูลมากกว่า 20 ปีหรือไม่,Are all customer ages in the dataset above 20?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Customer_Age'].min() > 20,customer
	มีการยื่นตั๋วใด ๆ ภายใต้ 'การเข้าถึงบัญชี' หรือไม่ ,Has any ticket been filed under 'Account access'?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Ticket_Subject'].str.contains('Account access').any(),customer
	ตั๋วมีเวลาตอบกลับครั้งแรกในช่วงสุดสัปดาห์หรือไม่ ,Is any ticket's first response time on a weekend?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['First_Response_Time'].dt.weekday >= 5,customer
	มีตั๋วที่มีสถานะลำดับความสำคัญสูงที่ยังคงเปิดอยู่หรือไม่ ,Is there a ticket with a high priority status that is still open?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,((data['Ticket_Priority'] == 'High') & (data['Ticket_Status'].str.contains('Open'))).any(),customer
	มีตั๋วใดบ้างที่ถูกทำเครื่องหมายว่า 'ด่วน' โดยมีคะแนนความพึงพอใจต่ำกว่า 2 หรือไม่ ,Has any ticket been marked as 'Urgent' with a satisfaction rating below 2?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,((data['Ticket_Priority'] == 'Urgent') & (data['Customer_Satisfaction_Rating'] < 2)).any(),customer
	มีตั๋วใดบ้างที่มีเวลาแก้ไขเป็นหนึ่งวันพอดี ,Are there any tickets with a resolution time of exactly one day?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,(data['Time_to_Resolution'] - data['First_Response_Time']).dt.days == 1,customer
	มีบันทึกเกี่ยวกับผลิตภัณฑ์ที่ลูกค้ารายอื่นซื้อมากกว่า 10 ครั้งหรือไม่ ,Is there any record of a product purchased more than 10 times by different customers?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Product_Purchased'].value_counts().max() > 10,customer
	เวลาเฉลี่ยในการแก้ปัญหาสำหรับตั๋วเกิน 12 ชั่วโมงหรือไม่,Is the average resolution time for tickets over 12 hours?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,(data['Time_to_Resolution'] - data['First_Response_Time']).dt.total_seconds().mean() / 3600 > 12,customer
	หัวข้อตั๋ว 'การตั้งค่าผลิตภัณฑ์' เกี่ยวข้องกับลำดับความสำคัญสูงหรือไม่,Is the ticket subject 'Product setup' associated with a high priority?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,(data[data['Ticket_Subject'] == 'Product setup']['Ticket_Priority'] == 'High').any(),customer
	ตั๋วใด ๆ จาก 'โซเชียลมีเดีย' ถูกทำเครื่องหมายว่าได้รับการแก้ไขแล้วหรือไม่,Has any ticket from 'Social media' been marked as resolved?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,((data['Ticket_Channel'] == 'Social media') & (data['Ticket_Status'] == 'Closed')).any(),customer
	มีลูกค้าชื่อ 'John Doe' ในชุดข้อมูลหรือไม่,Is there a customer named 'John Doe' in the dataset?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Customer_Name'].str.contains('John Doe').any(),customer
	มีการออกตั๋วในวันคริสต์มาส (25 ธ.ค. ) หรือไม่ ,Has any ticket been issued on Christmas Day (Dec 25)?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Date_of_Purchase'].dt.month == 12 and data['Date_of_Purchase'].dt.day == 25,customer
	มีตั๋วที่เปิดเกิน 30 วันไหม ,Is there any ticket that has been open for more than 30 days?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,(data['Ticket_Status'] == 'Open') & ((pd.Timestamp.now() - data['Date_of_Purchase']).dt.days > 30),customer
	ตั๋วทั้งหมดมาจากลูกค้าที่มีอายุ 30 ปีขึ้นไปหรือไม่,Do all tickets come from customers aged 30 or older?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Customer_Age'].min() >= 30,customer
	มีตั๋วใดบ้างที่ถูกปิดภายใน 24 ชั่วโมงหลังจากเปิดหรือไม่ ,Has any ticket been closed within 24 hours of its opening?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,(data['Ticket_Status'] == 'Closed') & ((data['Time_to_Resolution'] - data['First_Response_Time']).dt.total_seconds() / 3600 <= 24),customer
	วิธีแก้ปัญหาที่พบบ่อยที่สุดเกี่ยวข้องกับ 'ปัญหาบัญชี' หรือไม่,Is the most common resolution related to 'account issues'?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Resolution'].str.contains('account').value_counts().idxmax(),customer
	มีตั๋วจากลูกค้านามสกุล 'Smith' หรือไม่ ,Are there any tickets from a customer with the last name 'Smith'?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Customer_Name'].str.contains('Smith').any(),customer
	ลูกค้ารายใดให้คะแนนความพึงพอใจเป็นศูนย์หรือไม่ ,Has any customer given a satisfaction rating of zero?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Customer_Satisfaction_Rating'] == 0,customer
	มีตั๋วจากลูกค้าที่มีอายุต่ำกว่า 18 ปีหรือไม่ ,Are there any tickets from customers under the age of 18?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Customer_Age'] < 18,customer
	ชุดข้อมูลมีตั๋วจากทุกเดือนของปีหรือไม่,Does the dataset contain tickets from every month of the year?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Date_of_Purchase'].dt.month.nunique() == 12,customer
	ตั๋วเคยได้รับการอัปเกรดจากลำดับความสำคัญ 'ต่ำ' เป็น 'สูง' หรือไม่,Has a ticket ever been upgraded from 'Low' to 'High' priority?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,"data.sort_values(by=['Ticket_ID', 'Ticket_Priority'], ascending=[True, False]).duplicated(subset=['Ticket_ID'], keep=False).any()",customer
	มีตั๋วสำหรับการซื้อในวันอธิกสุรทินหรือไม่ ,Is there a ticket concerning a purchase made on a leap day?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Date_of_Purchase'].dt.day == 29 and data['Date_of_Purchase'].dt.month == 2,customer
	" มีตั๋วที่เกี่ยวข้องกับผลิตภัณฑ์ที่มีราคามากกว่า $1,000 หรือไม่ ",Has any ticket involved a product priced over $1000?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Product_Purchased'].str.contains('Expensive').any(),customer
	มีตั๋วใดบ้างที่ได้รับการแก้ไขโดยไม่มีคำติชมจากลูกค้า ,Are there any tickets that were resolved without any customer feedback?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,(data['Ticket_Status'] == 'Closed') & (data['Customer_Satisfaction_Rating'].isna()),customer
	คำอธิบายตั๋วใด ๆ กล่าวถึง 'การคืนเงิน' หรือไม่ ,Does any ticket description mention a 'refund'?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,"data['Ticket_Description'].str.contains('refund', case=False).any()",customer
	มีลูกค้าจากนิวยอร์กที่ใช้โดเมนอีเมล '@ny.com' หรือไม่,Is there any customer from New York based on the email domain '@ny.com'?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Customer_Email'].str.contains('@ny.com').any(),customer
	ตั๋วทั้งหมดได้รับการจัดอันดับด้วยคะแนนความพึงพอใจของลูกค้าอย่างน้อย 3 หรือไม่ ,Are all tickets rated with a customer satisfaction rating of at least 3?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Customer_Satisfaction_Rating'].min() >= 3,customer
	มีการกล่าวถึงผลิตภัณฑ์ 'iPhone 12' ในตั๋วใด ๆ หรือไม่ ,Is the product 'iPhone 12' mentioned in any ticket?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Product_Purchased'].str.contains('iPhone 12').any(),customer
	มีลูกค้าที่ชื่อ 'ไมเคิล' ส่งตั๋วมาบ้างไหม ,Has any ticket been submitted by a customer named 'Michael'?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Customer_Name'].str.contains('Michael').any(),customer
	มีลูกค้าผู้หญิงมากกว่าลูกค้าผู้ชายในชุดข้อมูลหรือไม่,Are there more female customers than male customers in the dataset?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Customer_Gender'].value_counts()['Female'] > data['Customer_Gender'].value_counts()['Male'],customer