如何在图形中绘制pandas groupby值？

概述我有一个csv文件,其中包含性别和婚姻状态以及更多列,如下所示. Loan_ID,Gender,Married,Dependents,Education,Self_Employed,ApplicantIncome,CoapplicantIncome,LoanAmount,Loan_Amount_Term,Credit_History,Property_Area,Loan_StatusLP0010 我有一个csv文件,其中包含性别和婚姻状态以及更多列,如下所示.

Loan_ID,Gender,MarrIEd,Dependents,Education,Self_Employed,ApplicantIncome,CoapplicantIncome,LoanAmount,Loan_Amount_Term,Credit_History,Property_Area,Loan_StatusLP001002,Male,No,Graduate,5849,360,1,Urban,YLP001003,Yes,4583,1508,128,Rural,NLP001005,3000,66,YLP001006,Not Graduate,2583,2358,120,YLP001008,6000,141,YLP001011,2,5417,4196,267,Y

我想要数不.已婚男性和女性的结果如下图所示

以下是我使用的代码：

import csvimport pandas as pdimport numpy as npimport matplotlib.pyplot as pltif __name__ == '__main__':    x=[]    y=[]    df = pd.read_csv(        "/home/train.csv",usecols=[1,2]).dropna(subset=['Gender','MarrIEd'])  # Reading the dataset in a dataframe using Pandas    groups = df.groupby(['Gender','MarrIEd'])['MarrIEd'].apply(lambda x: x.count())    print(groups)

分组后我有以下结果：

Gender  MarrIEdFemale  No          80        Yes         31Male    No         130        Yes        357

我想要一个如下图表

解决方法 您可以使用 groupby size然后使用 Series.plot.bar：

Difference between count and size.

groups = df.groupby(['Gender','MarrIEd']).size()groups.plot.bar()

另一种解决方案是为重塑或crosstab添加unstack：

print (df.groupby(['Gender','MarrIEd']).size().unstack(fill_value=0))MarrIEd   No  YesGender           Female    80   31Male     130  357df.groupby(['Gender','MarrIEd']).size().unstack(fill_value=0).plot.bar()

要么：

pd.crosstab(df['Gender'],df['MarrIEd']).plot.bar()

总结

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