DATAvisual3.py

#!/usr/bin/env python
# coding: utf-8

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import numpy as np  


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import pandas as pd


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import matplotlib.pyplot as plt


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data_bank = pd.read_csv('bank.csv')  # read the banl data using pandas


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data_bank.head(10)


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plt.bar(data_bank.Age,data_bank.Balance,color='red',label='age and Balance',)
plt.title('age vs Balance')
plt.xlabel("Age")
plt.ylabel('Balance')


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plt.scatter(data_bank.Age,data_bank.EstimatedSalary,color='red',label='Age and EstimatedSalary',)
plt.title('Age vs EstimatedSalary')
plt.xlabel("Age")
plt.ylabel('EstimatedSalary')


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data_bank.groupby('Geography').size().plot('pie',shadow=True, label='Geography',explode=[0.08,0,0] ,autopct='%d%%')


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plt.bar(data_bank.Geography,data_bank.Tenure,color='red',label='Geography and Gender',)
plt.title('Geography vs Gender')
plt.xlabel("Geography")
plt.ylabel('Gender')


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data_bank.groupby('Gender').size().plot('pie',shadow=True, label='Gender',explode=[0.08,0] ,autopct='%d%%')


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