MMTU-benchmark/MMTU huggingface dataset:
Task: Transform-by-input-output-table (source dataset: Scythe)

Your task is to create a data transformation pipeline in Python using pandas libraries.

Given input table(s) and a corresponding output table below, please write Python pandas code that can transform the input table into the given output table. Your code should save the resulting DataFrame to a CSV file named 'output.csv'. Ensure that the code is executable and can be run directly as is, in a Python environment with pandas installed.

Input Table:


Table #0
Filename: input_0.csv
Sample Rows in Markdown:
|   ID | Fruit    |
|-----:|:---------|
|    1 | apples   |
|    1 | bananas  |
|    2 | apples   |
|    2 | oranges  |
|    2 | cherries |
|    2 | lychees  |
|    3 | bananas  |
|    3 | cherries |
|    3 | lychees  |


Output Table:
|   ID1 |   ID2 | Fruit    |
|------:|------:|:---------|
|     1 |     2 | apples   |
|     1 |     3 | bananas  |
|     2 |     3 | cherries |
|     2 |     3 | lychees  |

Return only the final code in markdown codeblock format, without any additional text or explanation. 



inputs: input_0.csv
Task: Transform-by-input-output-table (source dataset: Scythe)

Your task is to create a data transformation pipeline in Python using pandas libraries.

Given input table(s) and a corresponding output table below, please write Python pandas code that can transform the input table into the given output table. Your code should save the resulting DataFrame to a CSV file named 'output.csv'. Ensure that the code is executable and can be run directly as is, in a Python environment with pandas installed.

Input Table:


Table #0
Filename: input_0.csv
Sample Rows in Markdown:
|   VehicleID | Name   |
|------------:|:-------|
|           1 | Chuck  |
|           2 | Larry  |


Table #1
Filename: input_1.csv
Sample Rows in Markdown:
|   LocationID |   VehicleID | City        |
|-------------:|------------:|:------------|
|            1 |           1 | New York    |
|            2 |           1 | Seattle     |
|            3 |           1 | Vancouver   |
|            4 |           2 | Los Angeles |
|            5 |           2 | Houston     |


Output Table:
|   VehicleID | Name   | Locations                    |
|------------:|:-------|:-----------------------------|
|           1 | Chuck  | New York, Seattle, Vancouver |
|           2 | Larry  | Los Angeles, Houston         |

Return only the final code in markdown codeblock format, without any additional text or explanation. 



inputs: input_0.csv
input_1.csv
Task: Transform-by-input-output-table (source dataset: Scythe)

Your task is to create a data transformation pipeline in Python using pandas libraries.

Given input table(s) and a corresponding output table below, please write Python pandas code that can transform the input table into the given output table. Your code should save the resulting DataFrame to a CSV file named 'output.csv'. Ensure that the code is executable and can be run directly as is, in a Python environment with pandas installed.

Input Table:


Table #0
Filename: input_0.csv
Sample Rows in Markdown:
|   Item_Txn | Item_Name   |
|-----------:|:------------|
|        101 | Mouse       |
|        102 | Mouse       |
|        103 | Mouse       |
|        104 | Keyboard    |
|        105 | CPU         |
|        106 | Monitor     |
|        107 | Monitor     |


Output Table:
|   Item_Txn | Item_Name   |
|-----------:|:------------|
|        101 | Mouse       |
|        104 | Keyboard    |
|        105 | CPU         |
|        106 | Monitor     |

Return only the final code in markdown codeblock format, without any additional text or explanation. 



inputs: input_0.csv
Task: Transform-by-input-output-table (source dataset: Scythe)

Your task is to create a data transformation pipeline in Python using pandas libraries.

Given input table(s) and a corresponding output table below, please write Python pandas code that can transform the input table into the given output table. Your code should save the resulting DataFrame to a CSV file named 'output.csv'. Ensure that the code is executable and can be run directly as is, in a Python environment with pandas installed.

Input Table:


Table #0
Filename: input_0.csv
Sample Rows in Markdown:
|   id | name   |   phone_number |
|-----:|:-------|---------------:|
|    1 | John   |   111111111111 |
|    2 | Jane   |   222222222222 |


Table #1
Filename: input_1.csv
Sample Rows in Markdown:
|   id |   date |   phone_number |
|-----:|-------:|---------------:|
|    1 |    945 |    1.11111e+11 |
|    2 |    950 |    2.22222e+11 |
|    3 |   1045 |    3.33333e+11 |


Output Table:
|   id |   date |   phone_number |
|-----:|-------:|---------------:|
|    3 |   1045 |    3.33333e+11 |

Return only the final code in markdown codeblock format, without any additional text or explanation. 



inputs: input_0.csv
input_1.csv
Task: Transform-by-input-output-table (source dataset: Scythe)

Your task is to create a data transformation pipeline in Python using pandas libraries.

Given input table(s) and a corresponding output table below, please write Python pandas code that can transform the input table into the given output table. Your code should save the resulting DataFrame to a CSV file named 'output.csv'. Ensure that the code is executable and can be run directly as is, in a Python environment with pandas installed.

Input Table:


Table #0
Filename: input_0.csv
Sample Rows in Markdown:
|   school_id |   class_id | school_location   |
|------------:|-----------:|:------------------|
|         400 |         50 | Arizona           |


Table #1
Filename: input_1.csv
Sample Rows in Markdown:
|   staff_id | forename   |   school_id |   wage |
|-----------:|:-----------|------------:|-------:|
|          1 | Peter      |         400 |   5000 |


Output Table:
|   school_id |   numberofstaff |   salary |
|------------:|----------------:|---------:|
|         400 |               1 |     5000 |

Return only the final code in markdown codeblock format, without any additional text or explanation. 



inputs: input_0.csv
input_1.csv
Task: Transform-by-input-output-table (source dataset: Scythe)

Your task is to create a data transformation pipeline in Python using pandas libraries.

Given input table(s) and a corresponding output table below, please write Python pandas code that can transform the input table into the given output table. Your code should save the resulting DataFrame to a CSV file named 'output.csv'. Ensure that the code is executable and can be run directly as is, in a Python environment with pandas installed.

Input Table:


Table #0
Filename: input_0.csv
Sample Rows in Markdown:
|   ID | Name   |   Age | Parent   |
|-----:|:-------|------:|:---------|
|    1 | Bob    |    50 | NULL     |
|    2 | Matt   |    20 | 1        |
|    3 | Rick   |    18 | 1        |


Output Table:
|   ID | Name   |
|-----:|:-------|
|    1 | Bob    |

Return only the final code in markdown codeblock format, without any additional text or explanation. 



inputs: input_0.csv
Task: Transform-by-input-output-table (source dataset: Scythe)

Your task is to create a data transformation pipeline in Python using pandas libraries.

Given input table(s) and a corresponding output table below, please write Python pandas code that can transform the input table into the given output table. Your code should save the resulting DataFrame to a CSV file named 'output.csv'. Ensure that the code is executable and can be run directly as is, in a Python environment with pandas installed.

Input Table:


Table #0
Filename: input_0.csv
Sample Rows in Markdown:
| product_code   |   qty |   stock_before |   stock_after | date       |
|:---------------|------:|---------------:|--------------:|:-----------|
| xpto1          |     0 |              1 |             1 | 2015-01-01 |
| xpto1          |     1 |              1 |             2 | 2015-02-01 |
| xpto1          |     2 |             -1 |             1 | 2015-03-01 |
| xpto2          |     0 |              1 |             1 | 2015-01-01 |
| xpto2          |     1 |              1 |             2 | 2015-02-01 |
| xpto2          |     2 |             -1 |             1 | 2015-03-01 |


Output Table:
| product_code   |   qty |   stock_before |   stock_after | date       |
|:---------------|------:|---------------:|--------------:|:-----------|
| xpto1          |     1 |              1 |             2 | 2015-02-01 |
| xpto2          |     1 |              1 |             2 | 2015-02-01 |

Return only the final code in markdown codeblock format, without any additional text or explanation. 



inputs: input_0.csv
Task: Transform-by-input-output-table (source dataset: Scythe)

Your task is to create a data transformation pipeline in Python using pandas libraries.

Given input table(s) and a corresponding output table below, please write Python pandas code that can transform the input table into the given output table. Your code should save the resulting DataFrame to a CSV file named 'output.csv'. Ensure that the code is executable and can be run directly as is, in a Python environment with pandas installed.

Input Table:


Table #0
Filename: input_0.csv
Sample Rows in Markdown:
|   id | date       | time_stamp   | licenseid   |   storeid | deviceid   |   value |
|-----:|:-----------|:-------------|:------------|----------:|:-----------|--------:|
|    1 | 2015-06-12 | 17:36:15     | lic0001     |         1 | 0add       |      52 |
|    2 | 2015-06-12 | 17:36:15     | lic0002     |         1 | 0add       |      54 |
|    3 | 2015-06-12 | 17:36:15     | lic0003     |         1 | 0add       |      53 |
|    4 | 2015-06-12 | 17:36:21     | lic0001     |         1 | 0add       |      54 |
|    5 | 2015-06-12 | 17:36:21     | lic0002     |         1 | 0add       |      59 |
|    6 | 2015-06-12 | 17:36:21     | lic0003     |         1 | 0add       |      62 |
|    7 | 2015-06-12 | 17:36:21     | lic0004     |         1 | 0add       |      55 |
|    8 | 2015-06-12 | 17:36:15     | lic0001     |         1 | 0bdd       |      53 |
|    9 | 2015-06-12 | 17:36:15     | lic0002     |         1 | 0bdd       |      52 |
|   10 | 2015-06-12 | 17:36:15     | lic0003     |         1 | 0bdd       |      52 |


Output Table:
| date       | deviceid   |   count |
|:-----------|:-----------|--------:|
| 2015-06-12 | 0add       |       2 |
| 2015-06-12 | 0bdd       |       1 |

Return only the final code in markdown codeblock format, without any additional text or explanation. 



inputs: input_0.csv
Task: Transform-by-input-output-table (source dataset: Scythe)

Your task is to create a data transformation pipeline in Python using pandas libraries.

Given input table(s) and a corresponding output table below, please write Python pandas code that can transform the input table into the given output table. Your code should save the resulting DataFrame to a CSV file named 'output.csv'. Ensure that the code is executable and can be run directly as is, in a Python environment with pandas installed.

Input Table:


Table #0
Filename: input_0.csv
Sample Rows in Markdown:
|   user_id | names   |
|----------:|:--------|
|       701 | Name1   |
|       701 | Name2   |
|       701 | Name3   |
|       701 | Name4   |
|       702 | Name5   |
|       702 | Name6   |
|       703 | Name7   |
|       703 | Name8   |


Output Table:
|   user_id | names   |
|----------:|:--------|
|       701 | Name1   |
|       701 | Name2   |
|       701 | Name3   |
|       701 | Name4   |

Return only the final code in markdown codeblock format, without any additional text or explanation. 



inputs: input_0.csv
Task: Transform-by-input-output-table (source dataset: Scythe)

Your task is to create a data transformation pipeline in Python using pandas libraries.

Given input table(s) and a corresponding output table below, please write Python pandas code that can transform the input table into the given output table. Your code should save the resulting DataFrame to a CSV file named 'output.csv'. Ensure that the code is executable and can be run directly as is, in a Python environment with pandas installed.

Input Table:


Table #0
Filename: input_0.csv
Sample Rows in Markdown:
|   id |   data1 |   data2 |
|-----:|--------:|--------:|
|    1 |       1 |       4 |
|    2 |       1 |       5 |
|    3 |       2 |       6 |
|    4 |       2 |       7 |


Output Table:
|   data1 |   id |   data2 |
|--------:|-----:|--------:|
|       1 |    2 |       5 |
|       2 |    4 |       7 |

Return only the final code in markdown codeblock format, without any additional text or explanation. 



inputs: input_0.csv
Task: Transform-by-input-output-table (source dataset: Scythe)

Your task is to create a data transformation pipeline in Python using pandas libraries.

Given input table(s) and a corresponding output table below, please write Python pandas code that can transform the input table into the given output table. Your code should save the resulting DataFrame to a CSV file named 'output.csv'. Ensure that the code is executable and can be run directly as is, in a Python environment with pandas installed.

Input Table:


Table #0
Filename: input_0.csv
Sample Rows in Markdown:
|   StoreId |   ClientId |
|----------:|-----------:|
|         1 |          4 |
|         1 |          5 |
|         2 |          5 |
|         2 |          6 |
|         2 |          7 |
|         3 |          8 |


Output Table:
|   StoreId |
|----------:|
|         3 |

Return only the final code in markdown codeblock format, without any additional text or explanation. 



inputs: input_0.csv
Task: Transform-by-input-output-table (source dataset: Scythe)

Your task is to create a data transformation pipeline in Python using pandas libraries.

Given input table(s) and a corresponding output table below, please write Python pandas code that can transform the input table into the given output table. Your code should save the resulting DataFrame to a CSV file named 'output.csv'. Ensure that the code is executable and can be run directly as is, in a Python environment with pandas installed.

Input Table:


Table #0
Filename: input_0.csv
Sample Rows in Markdown:
|   Train | Dest   | Time   |
|--------:|:-------|:-------|
|       1 | HK     | 10:00  |
|       1 | SH     | 12:00  |
|       1 | SZ     | 14:00  |
|       2 | HK     | 13:00  |
|       2 | SH     | 09:00  |
|       2 | SZ     | 07:00  |


Output Table:
|   Train | Dest   | Time   |
|--------:|:-------|:-------|
|       1 | SZ     | 14:00  |
|       2 | HK     | 13:00  |

Return only the final code in markdown codeblock format, without any additional text or explanation. 



inputs: input_0.csv
Task: Transform-by-input-output-table (source dataset: Scythe)

Your task is to create a data transformation pipeline in Python using pandas libraries.

Given input table(s) and a corresponding output table below, please write Python pandas code that can transform the input table into the given output table. Your code should save the resulting DataFrame to a CSV file named 'output.csv'. Ensure that the code is executable and can be run directly as is, in a Python environment with pandas installed.

Input Table:


Table #0
Filename: input_0.csv
Sample Rows in Markdown:
|   PRO_ID | PRO_Date   |   PRO_Price |
|---------:|:-----------|------------:|
|      123 | 01/01/2016 |        2000 |
|      123 | 02/01/2016 |        2500 |
|      123 | 03/01/2016 |        1500 |
|      123 | 05/01/2016 |        3000 |
|      456 | 01/01/2016 |        2000 |
|      456 | 02/01/2016 |        2500 |
|      456 | 03/01/2016 |        1500 |
|      456 | 05/01/2016 |        3000 |
|      456 | 06/01/2016 |        3500 |
|      456 | 07/01/2016 |        3600 |


Output Table:
|   PRO_ID | Last_PRO_Date   |
|---------:|:----------------|
|      123 | 05/01/2016      |
|      456 | 06/01/2016      |

Return only the final code in markdown codeblock format, without any additional text or explanation. 



inputs: input_0.csv
Task: Transform-by-input-output-table (source dataset: Scythe)

Your task is to create a data transformation pipeline in Python using pandas libraries.

Given input table(s) and a corresponding output table below, please write Python pandas code that can transform the input table into the given output table. Your code should save the resulting DataFrame to a CSV file named 'output.csv'. Ensure that the code is executable and can be run directly as is, in a Python environment with pandas installed.

Input Table:


Table #0
Filename: input_0.csv
Sample Rows in Markdown:
|   id |   productId |   orderIndex |   rejected |
|-----:|------------:|-------------:|-----------:|
|    1 |           1 |            0 |          1 |
|    2 |           1 |            1 |          0 |
|    3 |           1 |            2 |          0 |
|    4 |           2 |            0 |          0 |
|    5 |           2 |            1 |          1 |
|    6 |           3 |            0 |          0 |


Output Table:
|   id |   productId |   orderIndex |   rejected |
|-----:|------------:|-------------:|-----------:|
|    2 |           1 |            1 |          0 |
|    4 |           2 |            0 |          0 |
|    6 |           3 |            0 |          0 |

Return only the final code in markdown codeblock format, without any additional text or explanation. 



inputs: input_0.csv
Task: Transform-by-input-output-table (source dataset: Scythe)

Your task is to create a data transformation pipeline in Python using pandas libraries.

Given input table(s) and a corresponding output table below, please write Python pandas code that can transform the input table into the given output table. Your code should save the resulting DataFrame to a CSV file named 'output.csv'. Ensure that the code is executable and can be run directly as is, in a Python environment with pandas installed.

Input Table:


Table #0
Filename: input_0.csv
Sample Rows in Markdown:
| X   | Y   |   Number | Value   |
|:----|:----|---------:|:--------|
| asd | xcv |     1111 | A1      |
| ads | xvc |     1111 | A1      |
| qwe | rtz |     2222 | A2      |
| qew | zrt |     2222 | A2      |


Output Table:
|   Number | Value   |
|---------:|:--------|
|     1111 | A1      |
|     2222 | A2      |

Return only the final code in markdown codeblock format, without any additional text or explanation. 



inputs: input_0.csv
Task: Transform-by-input-output-table (source dataset: Scythe)

Your task is to create a data transformation pipeline in Python using pandas libraries.

Given input table(s) and a corresponding output table below, please write Python pandas code that can transform the input table into the given output table. Your code should save the resulting DataFrame to a CSV file named 'output.csv'. Ensure that the code is executable and can be run directly as is, in a Python environment with pandas installed.

Input Table:


Table #0
Filename: input_0.csv
Sample Rows in Markdown:
|   Id | Alerts   | Alert_Date          |
|-----:|:---------|:--------------------|
|    1 | Alert1   | 05/11/2015 12:12:22 |
|    2 | Alert2   | 05/11/2015 12:12:22 |
|    3 | Alert1   | 05/12/2015 12:12:22 |
|    4 | Alert2   | 05/13/2015 12:12:22 |
|    5 | Alert2   | 05/14/2015 12:12:22 |
|    6 | Alert3   | 05/14/2015 12:12:22 |


Output Table:
| Alerts   | Alert_Date          |
|:---------|:--------------------|
| Alert1   | 05/12/2015 12:12:22 |
| Alert2   | 05/14/2015 12:12:22 |
| Alert3   | 05/14/2015 12:12:22 |

Return only the final code in markdown codeblock format, without any additional text or explanation. 



inputs: input_0.csv
Task: Transform-by-input-output-table (source dataset: Scythe)

Your task is to create a data transformation pipeline in Python using pandas libraries.

Given input table(s) and a corresponding output table below, please write Python pandas code that can transform the input table into the given output table. Your code should save the resulting DataFrame to a CSV file named 'output.csv'. Ensure that the code is executable and can be run directly as is, in a Python environment with pandas installed.

Input Table:


Table #0
Filename: input_0.csv
Sample Rows in Markdown:
|   id |   amount |   id_waiter |
|-----:|---------:|------------:|
|    1 |       20 |           1 |
|    2 |       25 |           2 |
|    3 |       50 |           2 |
|    4 |       20 |           1 |
|    5 |       60 |           1 |
|    6 |       10 |           2 |


Output Table:
|   waiter |   maxamount |   bill |
|---------:|------------:|-------:|
|        1 |          60 |      5 |
|        2 |          50 |      3 |

Return only the final code in markdown codeblock format, without any additional text or explanation. 



inputs: input_0.csv
Task: Transform-by-input-output-table (source dataset: Scythe)

Your task is to create a data transformation pipeline in Python using pandas libraries.

Given input table(s) and a corresponding output table below, please write Python pandas code that can transform the input table into the given output table. Your code should save the resulting DataFrame to a CSV file named 'output.csv'. Ensure that the code is executable and can be run directly as is, in a Python environment with pandas installed.

Input Table:


Table #0
Filename: input_0.csv
Sample Rows in Markdown:
|   ID |   P_Id | room   |
|-----:|-------:|:-------|
|    1 |      8 | A      |
|    2 |      8 | A      |
|    3 |      8 | B      |
|    4 |      9 | B      |
|    5 |      9 | B      |
|    6 |     10 | C      |
|    7 |     10 | C      |
|    8 |     10 | D      |


Output Table:
|   ID |
|-----:|
|    9 |

Return only the final code in markdown codeblock format, without any additional text or explanation. 



inputs: input_0.csv
Task: Transform-by-input-output-table (source dataset: Scythe)

Your task is to create a data transformation pipeline in Python using pandas libraries.

Given input table(s) and a corresponding output table below, please write Python pandas code that can transform the input table into the given output table. Your code should save the resulting DataFrame to a CSV file named 'output.csv'. Ensure that the code is executable and can be run directly as is, in a Python environment with pandas installed.

Input Table:


Table #0
Filename: input_0.csv
Sample Rows in Markdown:
|   acct_id |   Bill_Id | Bill_dt    |   alt_bill_id |
|----------:|----------:|:-----------|--------------:|
|     12345 |    123451 | 2014-01-02 |           101 |
|     12345 |    123452 | 2014-01-02 |           102 |
|     12346 |    123461 | 2014-01-02 |           103 |
|     12347 |    123471 | 2014-01-02 |           104 |


Output Table:
|   acct_id |   Bill_Id | Bill_dt    |   alt_bill_id |
|----------:|----------:|:-----------|--------------:|
|     12345 |    123452 | 2014-01-02 |           102 |
|     12346 |    123461 | 2014-01-02 |           103 |
|     12347 |    123471 | 2014-01-02 |           104 |

Return only the final code in markdown codeblock format, without any additional text or explanation. 



inputs: input_0.csv
Task: Transform-by-input-output-table (source dataset: Scythe)

Your task is to create a data transformation pipeline in Python using pandas libraries.

Given input table(s) and a corresponding output table below, please write Python pandas code that can transform the input table into the given output table. Your code should save the resulting DataFrame to a CSV file named 'output.csv'. Ensure that the code is executable and can be run directly as is, in a Python environment with pandas installed.

Input Table:


Table #0
Filename: input_0.csv
Sample Rows in Markdown:
| comp   | Sub-comp   |   Lognum |   id | Firname   | LAstname   |
|:-------|:-----------|---------:|-----:|:----------|:-----------|
| AK     | AK-G       |        0 | 3897 | ABC       | DEF        |
| AK     | AK-G       |        0 | 5432 | mark      | ray        |
| MC     | MC-A       |        0 | 1234 | john      | steve      |
| MC     | MC-A       |        0 | 5678 | dan       | pitcher    |
| MC     | MC-A       |        0 | 9843 | james     | robin      |
| MC     | MC-A       |       84 | 1234 | john      | steve      |
| MC     | MC-A       |       84 | 5678 | dan       | pitcher    |
| MC     | MC-A       |       84 | 9843 | james     | robin      |


Output Table:
| comp   | Sub-comp   |   Lognum |   id | Firname   | LAstname   |
|:-------|:-----------|---------:|-----:|:----------|:-----------|
| AK     | AK-G       |        0 | 3897 | ABC       | DEF        |
| AK     | AK-G       |        0 | 5432 | mark      | ray        |
| MC     | MC-A       |       84 | 1234 | john      | steve      |
| MC     | MC-A       |       84 | 5678 | dan       | pitcher    |
| MC     | MC-A       |       84 | 9843 | james     | robin      |

Return only the final code in markdown codeblock format, without any additional text or explanation. 



inputs: input_0.csv
Task: Transform-by-input-output-table (source dataset: Scythe)

Your task is to create a data transformation pipeline in Python using pandas libraries.

Given input table(s) and a corresponding output table below, please write Python pandas code that can transform the input table into the given output table. Your code should save the resulting DataFrame to a CSV file named 'output.csv'. Ensure that the code is executable and can be run directly as is, in a Python environment with pandas installed.

Input Table:


Table #0
Filename: input_0.csv
Sample Rows in Markdown:
| NAME   |   SCORE |
|:-------|--------:|
| willy  |       1 |
| willy  |       2 |
| willy  |       3 |
| zoe    |       4 |
| zoe    |       5 |
| zoe    |       6 |


Output Table:
| NAME   |   SCORE |
|:-------|--------:|
| willy  |       2 |
| willy  |       3 |
| zoe    |       5 |
| zoe    |       6 |

Return only the final code in markdown codeblock format, without any additional text or explanation. 



inputs: input_0.csv
Task: Transform-by-input-output-table (source dataset: Scythe)

Your task is to create a data transformation pipeline in Python using pandas libraries.

Given input table(s) and a corresponding output table below, please write Python pandas code that can transform the input table into the given output table. Your code should save the resulting DataFrame to a CSV file named 'output.csv'. Ensure that the code is executable and can be run directly as is, in a Python environment with pandas installed.

Input Table:


Table #0
Filename: input_0.csv
Sample Rows in Markdown:
|   Product_ID |   Client_ID |
|-------------:|------------:|
|            1 |           2 |
|            1 |           3 |
|            2 |           2 |
|            3 |           2 |


Output Table:
|   c1 |
|-----:|
|    2 |
|    3 |

Return only the final code in markdown codeblock format, without any additional text or explanation. 



inputs: input_0.csv
Task: Transform-by-input-output-table (source dataset: Scythe)

Your task is to create a data transformation pipeline in Python using pandas libraries.

Given input table(s) and a corresponding output table below, please write Python pandas code that can transform the input table into the given output table. Your code should save the resulting DataFrame to a CSV file named 'output.csv'. Ensure that the code is executable and can be run directly as is, in a Python environment with pandas installed.

Input Table:


Table #0
Filename: input_0.csv
Sample Rows in Markdown:
| attendee_id   | others1   |
|:--------------|:----------|
| abcd          | A         |
| ghij          | B         |
| defg          | C         |


Table #1
Filename: input_1.csv
Sample Rows in Markdown:
| attendee_id   | others2   |   event_id |
|:--------------|:----------|-----------:|
| wxyz          | D         |          1 |
| mlno          | E         |          2 |
| defg          | F         |          3 |
| defg          | G         |          2 |
| abcd          | H         |          1 |


Output Table:
| attendee_id   | others1   | others2   |   event_id |
|:--------------|:----------|:----------|-----------:|
| defg          | C         | F         |          3 |

Return only the final code in markdown codeblock format, without any additional text or explanation. 



inputs: input_0.csv
input_1.csv
Task: Transform-by-input-output-table (source dataset: Scythe)

Your task is to create a data transformation pipeline in Python using pandas libraries.

Given input table(s) and a corresponding output table below, please write Python pandas code that can transform the input table into the given output table. Your code should save the resulting DataFrame to a CSV file named 'output.csv'. Ensure that the code is executable and can be run directly as is, in a Python environment with pandas installed.

Input Table:


Table #0
Filename: input_0.csv
Sample Rows in Markdown:
|   deal_id |   status_id | timestamp           |
|----------:|------------:|:--------------------|
|      1226 |           1 | 2009-08-17 09:29:00 |
|      1226 |           2 | 2009-08-17 17:01:56 |
|      1226 |           2 | 2009-08-18 12:10:07 |
|      1226 |           3 | 2009-08-18 12:10:25 |
|      1226 |           4 | 2009-08-17 15:52:19 |
|      1227 |           1 | 2009-08-17 09:56:31 |
|      1227 |           2 | 2009-08-17 14:31:25 |


Output Table:
|   c1 |   c2 | c3                  |
|-----:|-----:|:--------------------|
| 1226 |    3 | 2009-08-18 12:10:25 |
| 1227 |    2 | 2009-08-17 14:31:25 |

Return only the final code in markdown codeblock format, without any additional text or explanation. 



inputs: input_0.csv
Task: Transform-by-input-output-table (source dataset: Scythe)

Your task is to create a data transformation pipeline in Python using pandas libraries.

Given input table(s) and a corresponding output table below, please write Python pandas code that can transform the input table into the given output table. Your code should save the resulting DataFrame to a CSV file named 'output.csv'. Ensure that the code is executable and can be run directly as is, in a Python environment with pandas installed.

Input Table:


Table #0
Filename: input_0.csv
Sample Rows in Markdown:
| BOMcat   |   BOM | AltBOM   |   Counter | ChangeNo     | DeID   | DID   | PreCounter   |   Baseqty |
|:---------|------:|:---------|----------:|:-------------|:-------|:------|:-------------|----------:|
| M        |  7882 | A        |        26 | GUC320140101 | X      |       |              |   100     |
| M        |  7882 | B        |         1 | GUC320140101 | X      |       |              |   100.5   |
| M        |  7882 | B        |       307 | GUC320141225 | X      |       | 1            |   100.5   |
| M        |  9772 | 01       |       600 | GUC120140904 | X      |       | 397          |   116.188 |
| M        |  9772 | 01       |       601 | GUC120150504 | X      |       | 600          |   116.488 |
| M        |  9772 | 01       |      1021 | GUC120150703 | X      |       | 601          |   116.488 |


Output Table:
| BOMcat   |   BOM | AltBOM   |   Counter | ChangeNo     | DeID   | DID   | PreCounter   |   Baseqty |
|:---------|------:|:---------|----------:|:-------------|:-------|:------|:-------------|----------:|
| M        |  7882 | A        |        26 | GUC320140101 | X      |       |              |   100     |
| M        |  7882 | B        |       307 | GUC320141225 | X      |       | 1            |   100.5   |
| M        |  9772 | 01       |      1021 | GUC120150703 | X      |       | 601          |   116.488 |

Return only the final code in markdown codeblock format, without any additional text or explanation. 



inputs: input_0.csv
Task: Transform-by-input-output-table (source dataset: Scythe)

Your task is to create a data transformation pipeline in Python using pandas libraries.

Given input table(s) and a corresponding output table below, please write Python pandas code that can transform the input table into the given output table. Your code should save the resulting DataFrame to a CSV file named 'output.csv'. Ensure that the code is executable and can be run directly as is, in a Python environment with pandas installed.

Input Table:


Table #0
Filename: input_0.csv
Sample Rows in Markdown:
|   ID | DESC         |
|-----:|:-------------|
|  100 | DESCRIPTION0 |
|  101 | DESCRIPTION1 |


Table #1
Filename: input_1.csv
Sample Rows in Markdown:
|   ID |   LINK | LAST_DATE   |
|-----:|-------:|:------------|
|    1 |    100 | 12/12/2012  |
|    2 |    100 | 12/13/2012  |
|    3 |    100 | 12/14/2013  |
|    4 |    101 | 12/12/2012  |
|    5 |    101 | 12/13/2012  |
|    6 |    101 | 12/14/2013  |


Output Table:
|   c1 | c2           | c3         |
|-----:|:-------------|:-----------|
|  100 | DESCRIPTION0 | 12/14/2013 |
|  101 | DESCRIPTION1 | 12/14/2013 |

Return only the final code in markdown codeblock format, without any additional text or explanation. 



inputs: input_0.csv
input_1.csv
Task: Transform-by-input-output-table (source dataset: Scythe)

Your task is to create a data transformation pipeline in Python using pandas libraries.

Given input table(s) and a corresponding output table below, please write Python pandas code that can transform the input table into the given output table. Your code should save the resulting DataFrame to a CSV file named 'output.csv'. Ensure that the code is executable and can be run directly as is, in a Python environment with pandas installed.

Input Table:


Table #0
Filename: input_0.csv
Sample Rows in Markdown:
|   ID |   X |   Y |
|-----:|----:|----:|
|    1 |  25 |  24 |
|    2 |  24 |  25 |
|    3 |  75 |   1 |
|    4 |   9 |  10 |
|    5 |  10 |   9 |


Output Table:
|   ID |   X |   Y |
|-----:|----:|----:|
|    2 |  24 |  25 |
|    3 |  75 |   1 |
|    5 |  10 |   9 |

Return only the final code in markdown codeblock format, without any additional text or explanation. 



inputs: input_0.csv
Task: Transform-by-input-output-table (source dataset: Scythe)

Your task is to create a data transformation pipeline in Python using pandas libraries.

Given input table(s) and a corresponding output table below, please write Python pandas code that can transform the input table into the given output table. Your code should save the resulting DataFrame to a CSV file named 'output.csv'. Ensure that the code is executable and can be run directly as is, in a Python environment with pandas installed.

Input Table:


Table #0
Filename: input_0.csv
Sample Rows in Markdown:
|   Uniq |   Value |   Time | Person   |
|-------:|--------:|-------:|:---------|
|      1 |       6 |    180 | Bob      |
|      2 |       8 |    170 | Bob      |
|      3 |       4 |     45 | Claire   |
|      4 |       4 |     90 | Claire   |


Output Table:
| Person   |   Duration |   Value |   Uniq |
|:---------|-----------:|--------:|-------:|
| Bob      |        350 |       8 |      2 |
| Claire   |        135 |       4 |      3 |

Return only the final code in markdown codeblock format, without any additional text or explanation. 



inputs: input_0.csv
Task: Transform-by-input-output-table (source dataset: Scythe)

Your task is to create a data transformation pipeline in Python using pandas libraries.

Given input table(s) and a corresponding output table below, please write Python pandas code that can transform the input table into the given output table. Your code should save the resulting DataFrame to a CSV file named 'output.csv'. Ensure that the code is executable and can be run directly as is, in a Python environment with pandas installed.

Input Table:


Table #0
Filename: input_0.csv
Sample Rows in Markdown:
| time_stamp          |   count |
|:--------------------|--------:|
| 2010-06-15 23:35:28 |       1 |
| 2010-06-15 23:35:30 |       1 |
| 2010-06-15 23:35:30 |       1 |
| 2010-06-15 23:35:30 |     942 |
| 2010-06-15 23:35:30 |     180 |
| 2010-06-15 23:35:30 |       4 |
| 2010-06-15 23:35:30 |      52 |
| 2010-06-15 23:35:30 |      12 |
| 2010-06-15 23:35:30 |       1 |
| 2010-06-15 23:35:30 |       1 |


Output Table:
| c1                  |   c2 |
|:--------------------|-----:|
| 2010-06-15 23:35:00 |    1 |
| 2010-06-15 23:35:30 | 7544 |
| 2010-06-17 10:39:35 |  450 |

Return only the final code in markdown codeblock format, without any additional text or explanation. 



inputs: input_0.csv
Task: Transform-by-input-output-table (source dataset: Scythe)

Your task is to create a data transformation pipeline in Python using pandas libraries.

Given input table(s) and a corresponding output table below, please write Python pandas code that can transform the input table into the given output table. Your code should save the resulting DataFrame to a CSV file named 'output.csv'. Ensure that the code is executable and can be run directly as is, in a Python environment with pandas installed.

Input Table:


Table #0
Filename: input_0.csv
Sample Rows in Markdown:
| firstname   | lastname   |   nb_payments |
|:------------|:-----------|--------------:|
| a           | b          |            10 |
| a           | b          |            20 |
| b           | a          |            30 |
| b           | a          |            40 |
| b           | b          |            50 |


Output Table:
| firstname   | lastname   |   top3 |
|:------------|:-----------|-------:|
| b           | a          |     70 |
| b           | b          |     50 |
| a           | b          |     30 |

Return only the final code in markdown codeblock format, without any additional text or explanation. 



inputs: input_0.csv
Task: Transform-by-input-output-table (source dataset: Scythe)

Your task is to create a data transformation pipeline in Python using pandas libraries.

Given input table(s) and a corresponding output table below, please write Python pandas code that can transform the input table into the given output table. Your code should save the resulting DataFrame to a CSV file named 'output.csv'. Ensure that the code is executable and can be run directly as is, in a Python environment with pandas installed.

Input Table:


Table #0
Filename: input_0.csv
Sample Rows in Markdown:
|   id |   way | time   |
|-----:|------:|:-------|
|    1 |     1 | 00:01  |
|    2 |     1 | 00:02  |
|    3 |     2 | 00:03  |
|    4 |     2 | 00:04  |
|    5 |     2 | 00:05  |
|    6 |     3 | 00:06  |
|    7 |     3 | 00:07  |
|    8 |     1 | 00:08  |
|    9 |     1 | 00:09  |


Output Table:
|   id |   way | from   | to    |
|-----:|------:|:-------|:------|
|    1 |     1 | 00:01  | 00:02 |
|    3 |     2 | 00:03  | 00:05 |
|    6 |     3 | 00:06  | 00:07 |
|    8 |     1 | 00:08  | 00:09 |

Return only the final code in markdown codeblock format, without any additional text or explanation. 



inputs: input_0.csv
Task: Transform-by-input-output-table (source dataset: Scythe)

Your task is to create a data transformation pipeline in Python using pandas libraries.

Given input table(s) and a corresponding output table below, please write Python pandas code that can transform the input table into the given output table. Your code should save the resulting DataFrame to a CSV file named 'output.csv'. Ensure that the code is executable and can be run directly as is, in a Python environment with pandas installed.

Input Table:


Table #0
Filename: input_0.csv
Sample Rows in Markdown:
|   zone_id | zone_name           |   time_start |
|----------:|:--------------------|-------------:|
|       391 | America/Los_Angeles |   2147397247 |
|       391 | America/Los_Angeles |   1425808800 |
|       391 | America/Los_Angeles |   2140678800 |
|       391 | America/Los_Angeles |      9972000 |
|       392 | America/Metlakatla  |   2147397247 |
|       392 | America/Metlakatla  |    436352400 |
|       392 | America/Metlakatla  |      9972000 |
|       393 | America/Anchorage   |   2147397247 |
|       393 | America/Anchorage   |   2140682400 |
|       393 | America/Anchorage   |   2120122800 |


Output Table:
|   c1 | c2                  |         c3 |
|-----:|:--------------------|-----------:|
|  391 | America/Los_Angeles | 1425808800 |
|  392 | America/Metlakatla  |  436352400 |
|  393 | America/Anchorage   | 1425812400 |

Return only the final code in markdown codeblock format, without any additional text or explanation. 



inputs: input_0.csv
Task: Transform-by-input-output-table (source dataset: Scythe)

Your task is to create a data transformation pipeline in Python using pandas libraries.

Given input table(s) and a corresponding output table below, please write Python pandas code that can transform the input table into the given output table. Your code should save the resulting DataFrame to a CSV file named 'output.csv'. Ensure that the code is executable and can be run directly as is, in a Python environment with pandas installed.

Input Table:


Table #0
Filename: input_0.csv
Sample Rows in Markdown:
| Name          |   GoalsScored |   GoalsSaved |
|:--------------|--------------:|-------------:|
| John Smith    |            15 |           12 |
| John Doe      |            12 |           20 |
| Bob John      |             7 |            6 |
| John Bob      |            10 |           30 |
| Bobby Johnson |            25 |           30 |


Table #1
Filename: input_1.csv
Sample Rows in Markdown:
| takenplayername   |
|:------------------|
| Bob John          |
| Bobby Johnson     |


Output Table:
| name     |
|:---------|
| John Bob |

Return only the final code in markdown codeblock format, without any additional text or explanation. 



inputs: input_0.csv
input_1.csv
Task: Transform-by-input-output-table (source dataset: Scythe)

Your task is to create a data transformation pipeline in Python using pandas libraries.

Given input table(s) and a corresponding output table below, please write Python pandas code that can transform the input table into the given output table. Your code should save the resulting DataFrame to a CSV file named 'output.csv'. Ensure that the code is executable and can be run directly as is, in a Python environment with pandas installed.

Input Table:


Table #0
Filename: input_0.csv
Sample Rows in Markdown:
|   id | text   |
|-----:|:-------|
|    1 | Blah   |
|    2 | Blah2  |
|    3 | Blah3  |


Table #1
Filename: input_1.csv
Sample Rows in Markdown:
|   id |   parent |   feature |
|-----:|---------:|----------:|
|    1 |        1 |       123 |
|    2 |        1 |        35 |
|    3 |        2 |        15 |


Output Table:
|   p.id | p.text   | c.id   | c.parent   | c.feature   |
|-------:|:---------|:-------|:-----------|:------------|
|      1 | Blah     | 1      | 1          | 123         |
|      2 | Blah2    | 3      | 2          | 15          |
|      3 | Blah3    | null   | null       | null        |

Return only the final code in markdown codeblock format, without any additional text or explanation. 



inputs: input_0.csv
input_1.csv
Task: semantic-transform (source dataset: SEMA-join)

Your task is to perform semantic data transformation on a given column of input values. You will first be shown a pair of example input/output columns, to learn the desired semantic transformations as demonstrated by the input/output columns. Then you will be given a new input column, where the goal is to generate output values corresponding to each value in the new input column, following the same transformation relationship demonstrated in the example input/output columns. 

No explanation is needed, and do not generate code. Simply return your answer in JSON format: {"output": [<output column>]}.

Eample Input Column:

| source   |
|:---------|
| Garnet   |
| Amethyst |
| Pearl    |
| Zircon   |
| Opal     |

Eample Output Column:
| target   |
|:---------|
| January  |
| February |
| June     |
| December |
| October  |

Test Input Column:
| source      |
|:------------|
| Aquamarine  |
| Diamond     |
| Emerald     |
| Alexandrite |
| Ruby        |
| Peridot     |
| Sapphire    |
| Tourmaline  |
| Topaz       |
| Citrine     |



label: March
April
May
June
July
August
September
October
November
November
Task: semantic-transform (source dataset: SEMA-join)

Your task is to perform semantic data transformation on a given column of input values. You will first be shown a pair of example input/output columns, to learn the desired semantic transformations as demonstrated by the input/output columns. Then you will be given a new input column, where the goal is to generate output values corresponding to each value in the new input column, following the same transformation relationship demonstrated in the example input/output columns. 

No explanation is needed, and do not generate code. Simply return your answer in JSON format: {"output": [<output column>]}.

Eample Input Column:

| source    |
|:----------|
| Guinea    |
| Tuvalu    |
| Zambia    |
| Argentina |
| Mali      |

Eample Output Column:
| target   |
|:---------|
| GN       |
| TV       |
| ZM       |
| AR       |
| ML       |

Test Input Column:
| source              |
|:--------------------|
| Afghanistan         |
| Albania             |
| Algeria             |
| American Samoa      |
| Andorra             |
| Angola              |
| Anguilla            |
| Antarctica          |
| Antigua and Barbuda |
| Armenia             |



label: AF
AL
DZ
AS
AD
AO
AI
AQ
AG
AM
Task: semantic-transform (source dataset: SEMA-join)

Your task is to perform semantic data transformation on a given column of input values. You will first be shown a pair of example input/output columns, to learn the desired semantic transformations as demonstrated by the input/output columns. Then you will be given a new input column, where the goal is to generate output values corresponding to each value in the new input column, following the same transformation relationship demonstrated in the example input/output columns. 

No explanation is needed, and do not generate code. Simply return your answer in JSON format: {"output": [<output column>]}.

Eample Input Column:

| source            |
|:------------------|
| Toyota            |
| Royal Dutch Shell |
| BP                |
| Walmart           |
| Volkswagen        |

Eample Output Column:
| target      |
|:------------|
| Automobiles |
| Petroleum   |
| Petroleum   |
| Retail      |
| Automobiles |

Test Input Column:
| source                               |
|:-------------------------------------|
| Sinopec                              |
| China National Petroleum Corporation |
| ExxonMobil                           |
| State Grid Corporation of China      |
| Glencore                             |



label: Petroleum
Petroleum
Petroleum
Power
Commodities
Task: semantic-transform (source dataset: SEMA-join)

Your task is to perform semantic data transformation on a given column of input values. You will first be shown a pair of example input/output columns, to learn the desired semantic transformations as demonstrated by the input/output columns. Then you will be given a new input column, where the goal is to generate output values corresponding to each value in the new input column, following the same transformation relationship demonstrated in the example input/output columns. 

No explanation is needed, and do not generate code. Simply return your answer in JSON format: {"output": [<output column>]}.

Eample Input Column:

| source              |
|:--------------------|
| Panasonic           |
| Dell                |
| Samsung Electronics |
| LG Electronics      |
| Hitachi             |

Eample Output Column:
| target             |
|:-------------------|
| Osaka, Japan       |
| Austin, TX, USA    |
| Seoul, South Korea |
| Seoul, South Korea |
| Tokyo, Japan       |

Test Input Column:
| source     |
|:-----------|
| Apple Inc. |
| Foxconn    |
| HP         |
| IBM        |
| Microsoft  |
| Amazon.com |
| Sony       |
| Google     |
| Toshiba    |
| Intel      |



label: Cupertino, CA, USA
New Taipei, Taiwan
Palo Alto, CA, USA
Armonk, NY, USA
Redmond, WA, USA
Seattle, WA, USA
Tokyo, Japan
Mountain View, CA, USA
Tokyo, Japan
Santa Clara, CA, USA