Question 15
Consider the given Table 1: Banking data for the given subquestions stored as pandas dataframe in variable df
>>> import pandas as pd>>> df = pd.read_csv('dataset.csv')>>> print(df)| Age | Job | Marital | Education | Balance | Housing | Contact |
|---|---|---|---|---|---|---|
| 21 | unemployed | married | secondary | 77387 | no | telephone |
| 49 | management | married | tertiary | 2037 | no | nan |
| 72 | self-employed | married | tertiary | 132 | no | cellular |
| 31 | blue-collar | married | secondary | 298 | yes | nan |
| 28 | admin | single | secondary | 2831 | yes | nan |
| 39 | technician | single | secondary | 15 | yes | cellular |
| 32 | blue-collar | married | primary | 131 | yes | nan |
| 59 | management | married | tertiary | 5314 | no | cellular |
| 27 | technician | single | secondary | 155 | yes | cellular |
| 47 | blue-collar | married | primary | 259 | no | cellular |
Table 1: Banking Data
Based on the above data, answer the given subquestions.