Python Shows Only One Figure Output-CodePudding

I use the below given code. It works fine but shows only the last code's output. I want to see all figures when the code is run. How can i achieve this?

by_marry_data = data.groupby('Marital_Status')['Churn_Flag'].mean()

by_marry_data.plot(kind='bar', ylabel='Churn Ratio')

by_income_data = data.groupby('Income_Category')['Churn_Flag'].mean()

by_income_data.plot(kind='bar', ylabel='Churn Ratio')


by_gender_data = data.groupby('Gender')['Churn_Flag'].mean()

by_gender_data.plot(kind='bar', ylabel='Churn Ratio')

CodePudding user response：

If they are in the same script or cell you need to put plt.show() after each plot, unless you want the data to plot on the same figure.

by_marry_data = data.groupby('Marital_Status')['Churn_Flag'].mean()
by_marry_data.plot(kind='bar', ylabel='Churn Ratio')
plt.show();

by_income_data = data.groupby('Income_Category')['Churn_Flag'].mean()
by_income_data.plot(kind='bar', ylabel='Churn Ratio')
plt.show();

by_gender_data = data.groupby('Gender')['Churn_Flag'].mean()
by_gender_data.plot(kind='bar', ylabel='Churn Ratio')
plt.show();

CodePudding user response：

I think you are trying to draw subplots, for example as in: Creating multiple subplots using plt.subplots.

If you want to draw each plot in an horizontal row, you could use something like:

import matplotlib.pyplot as plt

plt.subplot(1, 3, 1)
by_marry_data.plot(kind='bar', ylabel='Churn Ratio')

plt.subplot(1, 3, 2)
by_income_data.plot(kind='bar', ylabel='Churn Ratio')

plt.subplot(1, 3, 3)
by_gender_data.plot(kind='bar', ylabel='Churn Ratio')

Also, you can switch from horizontal to vertical swapping first two arguments in each plt.subplot calls above.

CodePudding user response：

Try as said below.

May be call reset_index() on each groupby. Then get those dataframes and plot (rough code. Not tested below)

by_marry_data = data.reset_index().groupby('Marital_Status')['Churn_Flag'].mean()
by_income_data = data.reset_index().groupby('Income_Category')['Churn_Flag'].mean()
by_gender_data = data.reset_index().groupby('Gender')['Churn_Flag'].mean()

Now get axis from first plot and assign further.

ax = by_marry_data.plot(kind='bar', ylabel='Churn Ratio')
by_income_data.plot(ax=ax)
by_gender_data.plot(ax=ax)