BankChurners.csv文档
时间: 2023-08-22 17:07:20 浏览: 40
`BankChurners.csv` 是 `BankChurners.xlsx` 数据集的 CSV 格式文档。该文档包含了与 `BankChurners.xlsx` 相同的数据,但是以逗号分隔的方式来表示。
以下是 `BankChurners.csv` 文件中数据的前几行:
```
CLIENTNUM,Attrition_Flag,Customer_Age,Gender,Dependent_count,Education_Level,Marital_Status,Income_Category,Card_Category,Months_on_book,Total_Relationship_Count,Months_Inactive_12_mon,Contacts_Count_12_mon,Credit_Limit,Total_Revolving_Bal,Avg_Open_To_Buy,Total_Amt_Chng_Q4_Q1,Total_Trans_Amt,Total_Trans_Ct,Total_Ct_Chng_Q4_Q1,Avg_Utilization_Ratio
768805383,0,45,M,3,High School,Married,$60K - $80K,Blue,39,5,1,3,12691,777,11914,1.335,1144,42,1.625,0.061
818770008,0,49,F,5,Graduate,Single,Less than $40K,Blue,44,6,1,2,8256,864,7392,1.541,1291,33,3,0.105
713982108,0,51,M,3,Graduate,Married,$40K - $60K,Blue,36,4,1,0,3418,0,3418,2.594,1887,20,2.333,0
769911858,0,40,F,3,High School,Unknown,$40K - $60K,Blue,34,3,4,1,3313,2517,796,1.405,1171,20,-1.333,0.760
709106358,0,40,M,3,Graduate,Married,$60K - $80K,Blue,21,5,1,0,4716,0,4716,0.356,816,28,1.2,0.000
...
```
可以使用Python中的`pandas`库来读取该文件:
```python
import pandas as pd
data = pd.read_csv('BankChurners.csv')
```
然后就可以使用`data`变量来访问数据集中的内容了。