因此，我将按照本教程进行操作：https://www.analyticsvidhya.com/blog/2016/01/complete-tutorial-learn-data-science-python-scratch-2/
我遇到了一个我很难解决的问题。我的目标是并排输出两个子图，左图来自temp1数据帧，右图来自temp2表：
temp1：
Frequency Table for Credit History:
0.0 89
1.0 475
Name: Credit_History, dtype: int64
temp2：
Probility of getting loan for each Credit History class:
Loan_Status
Credit_History
0.0 0.078652
1.0 0.795789
这是代码块：
import matplotlib.pyplot as plt
fig = plt.figure(figsize=(8,4))
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")
这是我得到的输出：
我原本希望并排有两个子图，但是我右边的第二个子图是空的，而temp2图则在其下的第三个图中输出。
有任何想法吗？我发现matplotlib非常不直观，因此任何建议都值得赞赏！
编辑：我尝试与此代码块进行修补：
import matplotlib.pyplot as plt
fig = plt.figure(figsize=(8,4))
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.plot(temp2) # new attempt
ax2.set_xlabel('Credit_History')
ax2.set_ylabel('Probability of getting loan')
ax2.set_title("Probability of getting loan by credit history")
这使我更接近所需的格式，仅我想要条形图而不是折线
最佳答案
temp2.plot(kind = 'bar')是熊猫内置图形函数，因此请使用plt.bar(X, y)。
像这样 ：
（我使用此数据框，例如3行）
print(df)
sepal length (cm) petal length (cm) target
0 5.1 1.4 setosa
1 7.0 4.7 versicolor
2 6.3 6.0 virginica
所以
fig = plt.figure(figsize=(8,4))
ax1 = fig.add_subplot(121)
ax1.bar(df['target'], df['sepal length (cm)'])
ax1.set_xlabel('Credit_History')
ax1.set_ylabel('Count of Applicants')
ax1.set_title("Applicants by Credit_History")
ax2 = fig.add_subplot(122)
ax2.bar(df['target'], df['petal length (cm)'])
ax2.set_xlabel('Credit_History')
ax2.set_ylabel('Probability of getting loan')
ax2.set_title("Probability of getting loan by credit history")
plt.show()
编辑
我找到了你的数据集。问题很简单。
这是由于两种类型之间的差异。
print(type(temp1))
print(type(temp2))
<class 'pandas.core.series.Series'>
<class 'pandas.core.frame.DataFrame'>
因此，更改类型可以解决问题。
如果您将两种类型都更改为数据框，请使用我的第一条评论。
如果将两种类型都更改为Series，请使用此功能。
fig = plt.figure(figsize=(8,4))
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') # seiries
ax2 = fig.add_subplot(122)
ax2.set_xlabel('Credit_History')
ax2.set_ylabel('Probability of getting loan')
ax2.set_title("Probability of getting loan by credit history")
temp2['Loan_Status'].plot(kind = 'bar') # to seiries
plt.show()