[英]How to plot pandas groupby values in a graph?
I have a csv file which contains Gender and Marriage status along with few more columns like below. 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_Status
LP001002,Male,No,0,Graduate,No,5849,0,,360,1,Urban,Y
LP001003,Male,Yes,1,Graduate,No,4583,1508,128,360,1,Rural,N
LP001005,Male,Yes,0,Graduate,Yes,3000,0,66,360,1,Urban,Y
LP001006,Male,Yes,0,Not Graduate,No,2583,2358,120,360,1,Urban,Y
LP001008,Male,No,0,Graduate,No,6000,0,141,360,1,Urban,Y
LP001011,Male,Yes,2,Graduate,Yes,5417,4196,267,360,1,Urban,Y
I want to count no. 我想要数不。 of married Males and Females and show the same in graph as shown below 已婚男性和女性的结果如下图所示
Below is the code I am using : 以下是我使用的代码:
import csv
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
if __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)
After group by I have following result : 分组后我有以下结果:
Gender Married
Female No 80
Yes 31
Male No 130
Yes 357
I want a chart like below 我想要一个如下图表
You can use groupby
+ size
and then use Series.plot.bar
: 您可以使用groupby
+ size
然后使用Series.plot.bar
:
Difference between count and size . 计数和大小之间的差异 。
groups = df.groupby(['Gender','Married']).size()
groups.plot.bar()
Another solution is add unstack
for reshape or crosstab
: 另一个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 Yes
Gender
Female 80 31
Male 130 357
df.groupby(['Gender','Married']).size().unstack(fill_value=0).plot.bar()
Or: 要么:
pd.crosstab(df['Gender'],df['Married']).plot.bar()
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