熊猫没有绘制数据透视表输出？

Question

I have a data frame with variables Credit_History (0 or 1) and Loan_Status (Y or N). Temp1 just shows my count of rows labeled 0 or 1. Temp2 is where I want to code the Y or N to 0 or 1, then average it.

temp1 = df['Credit_History'].value_counts(ascending=True)
temp2 = df.pivot_table(values='Loan_Status',index=
['Credit_History'],aggfunc=lambda x: x.map({'Y':1,'N':0}).mean())

print ('Frequency Table for Credit History:')
print (temp1)
print ('\nProbility of getting loan for each Credit History class:') 
print (temp2)

When I plot, I would expect a 1 row by 2 column area. But it looks like a 2 row by 2 column area that contains 3 plots. Temp2 is being plotted 2 times, but one is blank other than axis titles. I'm assuming I'm declaring something wrong when I'm creating the temp2 object... enter image description here

import matplotlib.pyplot as plt
fig = plt.figure(figsize=(12,4))
ax1 = fig.add_subplot(121)
ax1.set_xlabel('Credit_History')
ax1.set_ylabel('Count of Applicants')
ax1.set_title('Applicants by Credit_History')
temp1.plot(kind='bar')


ax2 = fig.add_subplot(122)
temp2.plot(kind = 'bar')
ax2.set_xlabel('Credit_History')
ax2.set_ylabel('Probability of getting loan')
ax2.set_title('Probability of getting loan by credit history')

Answer 1

Consider laying out the dimensions of plot and then assign axes to pandas plots:

fig, axs = plt.subplots(nrows = 1, ncols=2, figsize=(12,4))

temp1.plot(kind='bar', title='Applicants by Credit_History', ax=axs[0])             
axs[0].set_xlabel('Credit_History')
axs[0].set_ylabel('Count of Applicants')

temp2.plot(kind = 'bar', title='Probability of getting loan by credit history', ax=axs[1])
axs[1].set_xlabel('Credit_History')
axs[1].set_ylabel('Probability of getting loan')

fig.tight_layout()
plt.show()
plt.clf()
plt.close()

Output (using random data)