Plotting Bar Graph according to Group

Question

I have this Telco-Customer Churn dataset. After analyzing the churn rate according to different duration of tenure, I would like to visualize it like how it looked in the following figure, where only the number of churns is plotted against different 'bins' of tenure.

Below is what I have tried:

import pandas as pd
import matplotlib.pyplot as plt

user_data = pd.read_csv("https://github.com/WedamN/Telco-Churn-Prediction/blob/master/CustomerChurnData.csv")

# bin the tenure into every 6 months
user_data['tenure_bin'] = pd.cut(user_data['Tenure'], list(range(0, 73, 6)))

# some basic analysis
churn_rate_according_to_tenure = user_data.groupby('tenure_bin').Churn.value_counts('Yes')*100

# plot the results
churn_rate_according_to_tenure.plot().bar()
plt.show()

Here is the plot I obtained (which is kinda messy) where the 'Yes' and 'No' categories are showed. How can I fix this where I would only want to show only the 'Yes' category with the bars having the same color?

Answer 1

I think you need reshape if want both categories together by unstack:

print (churn_rate_according_to_tenure.unstack())
Churn              No        Yes
tenure_bin                      
(0, 6]      46.666667  53.333333
(6, 12]     64.113475  35.886525
(12, 18]    67.700730  32.299270
(18, 24]    75.420168  24.579832
(24, 30]    78.190255  21.809745
(30, 36]    78.553616  21.446384
(36, 42]    78.100264  21.899736
(42, 48]    83.812010  16.187990
(48, 54]    83.809524  16.190476
(54, 60]    87.378641  12.621359
(60, 66]    90.712743   9.287257
(66, 72]    94.703390   5.296610

---

churn_rate_according_to_tenure.unstack().plot.bar()

If want filter, select category - column:

churn_rate_according_to_tenure.unstack()['Yes'].plot.bar()