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Datasets:
aai510-group1
/
telco-customer-churn

Tasks:
Tabular Classification
Modalities:
Tabular
Text
Formats:
csv
Languages:
English
Size:
1K - 10K
Tags:
tabular-classification
churn-prediction
telecom
customer-retention
demographics
customer-service
Libraries:
Datasets
pandas
Dataset card Viewer Files Community
1
jonathanagustin commited on
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b16ab54
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1 Parent(s): 71ec0c6

Update README.md

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  1. README.md +168 -106
README.md CHANGED
@@ -14,112 +14,174 @@ size_categories:
14
  task_categories:
15
  - tabular-classification
16
  dataset_info:
17
- - config_name: default
18
- features:
19
- - name: Age
20
- dtype: int64
21
- - name: Avg Monthly GB Download
22
- dtype: int64
23
- - name: Avg Monthly Long Distance Charges
24
- dtype: float64
25
- - name: Churn
26
- dtype: int64
27
- - name: Churn Category
28
- dtype: string
29
- - name: Churn Reason
30
- dtype: string
31
- - name: Churn Score
32
- dtype: int64
33
- - name: City
34
- dtype: string
35
- - name: CLTV
36
- dtype: int64
37
- - name: Contract
38
- dtype: string
39
- - name: Country
40
- dtype: string
41
- - name: Customer ID
42
- dtype: string
43
- - name: Customer Status
44
- dtype: string
45
- - name: Dependents
46
- dtype: int64
47
- - name: Device Protection Plan
48
- dtype: int64
49
- - name: Gender
50
- dtype: string
51
- - name: Internet Service
52
- dtype: int64
53
- - name: Internet Type
54
- dtype: string
55
- - name: Lat Long
56
- dtype: string
57
- - name: Latitude
58
- dtype: float64
59
- - name: Longitude
60
- dtype: float64
61
- - name: Married
62
- dtype: int64
63
- - name: Monthly Charge
64
- dtype: float64
65
- - name: Multiple Lines
66
- dtype: int64
67
- - name: Number of Dependents
68
- dtype: int64
69
- - name: Number of Referrals
70
- dtype: int64
71
- - name: Offer
72
- dtype: string
73
- - name: Online Backup
74
- dtype: int64
75
- - name: Online Security
76
- dtype: int64
77
- - name: Paperless Billing
78
- dtype: int64
79
- - name: Partner
80
- dtype: int64
81
- - name: Payment Method
82
- dtype: string
83
- - name: Phone Service
84
- dtype: int64
85
- - name: Population
86
- dtype: int64
87
- - name: Premium Tech Support
88
- dtype: int64
89
- - name: Quarter
90
- dtype: string
91
- - name: Referred a Friend
92
- dtype: int64
93
- - name: Satisfaction Score
94
- dtype: int64
95
- - name: Senior Citizen
96
- dtype: int64
97
- - name: State
98
- dtype: string
99
- - name: Streaming Movies
100
- dtype: int64
101
- - name: Streaming Music
102
- dtype: int64
103
- - name: Streaming TV
104
- dtype: int64
105
- - name: Tenure in Months
106
- dtype: int64
107
- - name: Total Charges
108
- dtype: float64
109
- - name: Total Extra Data Charges
110
- dtype: int64
111
- - name: Total Long Distance Charges
112
- dtype: float64
113
- - name: Total Refunds
114
- dtype: float64
115
- - name: Total Revenue
116
- dtype: float64
117
- - name: Under 30
118
- dtype: int64
119
- - name: Unlimited Data
120
- dtype: int64
121
- - name: Zip Code
122
- dtype: string
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
123
  ---
124
  # Dataset Card for Telco Customer Churn
125
 
 
14
  task_categories:
15
  - tabular-classification
16
  dataset_info:
17
+ - config_name: default
18
+ features:
19
+ - name: Age
20
+ dtype: int64
21
+ feature_type: Value
22
+ - name: Avg Monthly GB Download
23
+ dtype: int64
24
+ feature_type: Value
25
+ - name: Avg Monthly Long Distance Charges
26
+ dtype: float64
27
+ feature_type: Value
28
+ - name: Churn
29
+ dtype: int64
30
+ feature_type: ClassLabel
31
+ - name: Churn Category
32
+ dtype: string
33
+ feature_type: ClassLabel
34
+ - name: Churn Reason
35
+ dtype: string
36
+ feature_type: ClassLabel
37
+ - name: Churn Score
38
+ dtype: int64
39
+ feature_type: Value
40
+ - name: City
41
+ dtype: string
42
+ feature_type: Value
43
+ - name: CLTV
44
+ dtype: int64
45
+ feature_type: Value
46
+ - name: Contract
47
+ dtype: string
48
+ feature_type: Value
49
+ - name: Country
50
+ dtype: string
51
+ feature_type: Value
52
+ - name: Customer ID
53
+ dtype: string
54
+ feature_type: Value
55
+ - name: Customer Status
56
+ dtype: string
57
+ feature_type: Value
58
+ - name: Dependents
59
+ dtype: int64
60
+ feature_type: Value
61
+ - name: Device Protection Plan
62
+ dtype: int64
63
+ feature_type: Value
64
+ - name: Gender
65
+ dtype: string
66
+ feature_type: Value
67
+ - name: Internet Service
68
+ dtype: int64
69
+ feature_type: Value
70
+ - name: Internet Type
71
+ dtype: string
72
+ feature_type: Value
73
+ - name: Lat Long
74
+ dtype: string
75
+ feature_type: Value
76
+ - name: Latitude
77
+ dtype: float64
78
+ feature_type: Value
79
+ - name: Longitude
80
+ dtype: float64
81
+ feature_type: Value
82
+ - name: Married
83
+ dtype: int64
84
+ feature_type: Value
85
+ - name: Monthly Charge
86
+ dtype: float64
87
+ feature_type: Value
88
+ - name: Multiple Lines
89
+ dtype: int64
90
+ feature_type: Value
91
+ - name: Number of Dependents
92
+ dtype: int64
93
+ feature_type: Value
94
+ - name: Number of Referrals
95
+ dtype: int64
96
+ feature_type: Value
97
+ - name: Offer
98
+ dtype: string
99
+ feature_type: Value
100
+ - name: Online Backup
101
+ dtype: int64
102
+ feature_type: Value
103
+ - name: Online Security
104
+ dtype: int64
105
+ feature_type: Value
106
+ - name: Paperless Billing
107
+ dtype: int64
108
+ feature_type: Value
109
+ - name: Partner
110
+ dtype: int64
111
+ feature_type: Value
112
+ - name: Payment Method
113
+ dtype: string
114
+ feature_type: Value
115
+ - name: Phone Service
116
+ dtype: int64
117
+ feature_type: Value
118
+ - name: Population
119
+ dtype: int64
120
+ feature_type: Value
121
+ - name: Premium Tech Support
122
+ dtype: int64
123
+ feature_type: Value
124
+ - name: Quarter
125
+ dtype: string
126
+ feature_type: Value
127
+ - name: Referred a Friend
128
+ dtype: int64
129
+ feature_type: Value
130
+ - name: Satisfaction Score
131
+ dtype: int64
132
+ feature_type: Value
133
+ - name: Senior Citizen
134
+ dtype: int64
135
+ feature_type: Value
136
+ - name: State
137
+ dtype: string
138
+ feature_type: Value
139
+ - name: Streaming Movies
140
+ dtype: int64
141
+ feature_type: Value
142
+ - name: Streaming Music
143
+ dtype: int64
144
+ feature_type: Value
145
+ - name: Streaming TV
146
+ dtype: int64
147
+ feature_type: Value
148
+ - name: Tenure in Months
149
+ dtype: int64
150
+ feature_type: Value
151
+ - name: Total Charges
152
+ dtype: float64
153
+ feature_type: Value
154
+ - name: Total Extra Data Charges
155
+ dtype: int64
156
+ feature_type: Value
157
+ - name: Total Long Distance Charges
158
+ dtype: float64
159
+ feature_type: Value
160
+ - name: Total Refunds
161
+ dtype: float64
162
+ feature_type: Value
163
+ - name: Total Revenue
164
+ dtype: float64
165
+ feature_type: Value
166
+ - name: Under 30
167
+ dtype: int64
168
+ feature_type: Value
169
+ - name: Unlimited Data
170
+ dtype: int64
171
+ feature_type: Value
172
+ - name: Zip Code
173
+ dtype: string
174
+ feature_type: Value
175
+ splits:
176
+ - name: train
177
+ num_bytes: 400104
178
+ num_examples: 4225
179
+ - name: test
180
+ num_bytes: 183950
181
+ num_examples: 1409
182
+ - name: val
183
+ num_bytes: 184050
184
+ num_examples: 1409
185
  ---
186
  # Dataset Card for Telco Customer Churn
187