来自数据框 groupby 的条形图

Question

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

df = pd.read_csv("arrests.csv")
df = df.replace(np.nan,0)
df = df.groupby(['home_team'])['arrests'].mean()

我正在尝试为数据框创建条形图。 home_team 下是一堆队名。 被捕人数是指每个日期的逮捕人数。 我基本上按团队对数据进行了分组，该团队的平均逮捕人数。 我正在尝试为此创建一个条形图，但我不确定如何继续，因为一列没有标题。

数据

home_team,arrests
Arizona,5.0
Arizona,6.0
Arizona,9.0
Arizona,6.0
Arizona,3.0
Arizona,4.0
Arizona,1.0
Arizona,4.0
Arizona,0.0
Arizona,12.0
Arizona,4.0
Arizona,1.0
Arizona,3.0
Arizona,7.0
Arizona,3.0
Arizona,7.0
Arizona,7.0
Arizona,3.0
Arizona,7.0
Arizona,2.0
Arizona,3.0
Arizona,2.0
Arizona,4.0
Arizona,7.0
Arizona,4.0
Arizona,6.0
Arizona,4.0
Arizona,2.0
Arizona,1.0
Arizona,6.0
Arizona,2.0
Arizona,4.0
Arizona,3.0
Arizona,10.0
Arizona,3.0
Arizona,2.0
Arizona,2.0
Arizona,0.0
Arizona,5.0
Arizona,2.0
Baltimore,1.0
Baltimore,0.0
Baltimore,0.0
Baltimore,0.0
Baltimore,2.0
Baltimore,0.0
Baltimore,0.0
Baltimore,0.0
Baltimore,3.0
Baltimore,1.0
Baltimore,0.0
Baltimore,3.0
Baltimore,5.0
Baltimore,0.0
Baltimore,8.0
Baltimore,0.0
Baltimore,4.0
Baltimore,5.0
Baltimore,0.0
Baltimore,0.0
Baltimore,0.0
Baltimore,1.0
Baltimore,0.0
Baltimore,0.0
Baltimore,3.0
Baltimore,0.0
Baltimore,6.0
Baltimore,0.0
Baltimore,0.0
Baltimore,0.0
Baltimore,4.0
Carolina,0.0
Carolina,0.0
Carolina,0.0
Carolina,0.0
Carolina,0.0
Carolina,0.0
Carolina,2.0
Carolina,0.0
Carolina,1.0
Carolina,1.0
Carolina,1.0
Carolina,4.0
Carolina,1.0
Carolina,0.0
Carolina,0.0
Carolina,1.0
Carolina,1.0
Carolina,5.0
Carolina,1.0
Carolina,3.0
Carolina,3.0
Carolina,0.0
Carolina,2.0
Carolina,1.0
Carolina,1.0
Carolina,5.0
Carolina,1.0
Carolina,2.0
Carolina,1.0
Carolina,0.0
Carolina,0.0
Carolina,0.0
Carolina,0.0
Carolina,0.0
Carolina,4.0
Carolina,6.0
Carolina,2.0
Carolina,3.0
Carolina,0.0
Carolina,3.0
Chicago,1.0
Chicago,0.0
Chicago,1.0
Chicago,0.0
Chicago,0.0
Chicago,0.0
Chicago,0.0
Chicago,1.0
Chicago,0.0
Chicago,1.0
Chicago,1.0
Chicago,0.0
Chicago,3.0
Chicago,1.0
Chicago,0.0
Chicago,2.0
Chicago,0.0
Chicago,0.0
Chicago,0.0
Chicago,2.0
Chicago,0.0
Chicago,2.0
Chicago,1.0
Chicago,2.0
Chicago,1.0
Chicago,1.0
Chicago,0.0
Chicago,2.0
Chicago,1.0
Chicago,0.0
Chicago,2.0
Chicago,1.0
Cincinnati,3.0
Cincinnati,0.0
Cincinnati,1.0
Cincinnati,2.0
Cincinnati,3.0
Cincinnati,0.0
Cincinnati,0.0
Cincinnati,0.0
Cincinnati,3.0
Cincinnati,0.0
Cincinnati,0.0
Cincinnati,2.0
Cincinnati,4.0
Cincinnati,3.0
Cincinnati,3.0
Cincinnati,1.0
Cincinnati,3.0
Cincinnati,1.0
Cincinnati,0.0
Cincinnati,1.0
Cincinnati,0.0
Cincinnati,1.0
Cincinnati,0.0
Cincinnati,0.0
Cincinnati,4.0
Cincinnati,0.0
Cincinnati,1.0
Cincinnati,1.0
Cincinnati,1.0
Cincinnati,10.0
Cincinnati,6.0
Cincinnati,0.0
Cincinnati,1.0
Cincinnati,1.0
Cincinnati,1.0
Cincinnati,0.0
Cincinnati,0.0
Cincinnati,0.0
Cincinnati,0.0
Cincinnati,0.0
Dallas,1.0
Dallas,1.0
Dallas,0.0
Dallas,1.0
Dallas,2.0
Dallas,0.0
Dallas,0.0
Dallas,0.0
Dallas,4.0
Dallas,6.0
Dallas,15.0
Dallas,0.0
Dallas,5.0
Dallas,15.0
Dallas,13.0
Dallas,0.0
Dallas,9.0
Dallas,0.0
Dallas,0.0
Dallas,0.0
Dallas,1.0
Dallas,8.0
Dallas,5.0
Dallas,9.0
Dallas,2.0
Dallas,7.0
Dallas,7.0
Dallas,3.0
Dallas,3.0
Dallas,2.0
Dallas,0.0
Dallas,1.0
Dallas,13.0
Dallas,3.0
Dallas,7.0
Dallas,8.0
Dallas,8.0
Dallas,5.0
Dallas,4.0
Dallas,1.0
Denver,2.0
Denver,0.0
Denver,0.0
Denver,0.0
Denver,2.0
Denver,0.0
Denver,0.0
Denver,0.0
Denver,4.0
Denver,1.0
Denver,4.0
Denver,0.0
Denver,0.0
Denver,0.0
Denver,3.0
Denver,0.0
Denver,5.0
Denver,8.0
Denver,11.0
Denver,5.0
Denver,2.0
Denver,5.0
Denver,1.0
Denver,3.0
Denver,1.0
Denver,1.0
Denver,7.0
Denver,6.0
Denver,6.0
Denver,1.0
Denver,4.0
Denver,7.0
Denver,3.0
Denver,2.0
Denver,0.0
Denver,4.0
Denver,3.0
Denver,3.0
Denver,1.0
Denver,0.0
Detroit,
Detroit,
Detroit,
Detroit,
Detroit,
Detroit,
Detroit,
Detroit,
Detroit,
Detroit,
Detroit,
Detroit,
Detroit,
Detroit,
Detroit,
Detroit,
Detroit,
Detroit,
Detroit,
Detroit,
Detroit,
Detroit,
Detroit,
Detroit,
Detroit,
Detroit,
Detroit,
Detroit,
Detroit,
Detroit,
Detroit,
Detroit,
Detroit,
Detroit,
Detroit,
Detroit,
Detroit,
Detroit,
Detroit,
Detroit,
Green Bay,8.0
Green Bay,0.0
Green Bay,3.0
Green Bay,6.0
Green Bay,1.0
Green Bay,4.0
Green Bay,21.0
Green Bay,3.0
Green Bay,4.0
Green Bay,15.0
Green Bay,3.0
Green Bay,1.0
Green Bay,9.0
Green Bay,2.0
Green Bay,18.0
Green Bay,9.0
Green Bay,1.0
Green Bay,8.0
Green Bay,6.0
Green Bay,13.0
Green Bay,6.0
Green Bay,8.0
Green Bay,7.0
Green Bay,16.0
Green Bay,8.0
Green Bay,4.0
Green Bay,1.0
Green Bay,15.0
Green Bay,3.0
Green Bay,8.0
Green Bay,11.0
Green Bay,6.0
Green Bay,13.0
Green Bay,4.0
Green Bay,4.0
Green Bay,13.0
Green Bay,8.0
Green Bay,2.0
Green Bay,5.0
Green Bay,11.0
Houston,2.0
Houston,2.0
Houston,1.0
Houston,0.0
Houston,0.0
Houston,2.0
Houston,2.0
Houston,0.0
Houston,6.0
Houston,1.0
Houston,4.0
Houston,1.0
Houston,1.0
Houston,1.0
Houston,1.0
Houston,3.0
Houston,2.0
Houston,0.0
Houston,1.0
Houston,1.0
Houston,2.0
Houston,1.0
Houston,0.0
Houston,0.0
Houston,1.0
Houston,0.0
Houston,0.0
Houston,0.0
Houston,1.0
Houston,0.0
Houston,0.0
Houston,0.0
Houston,1.0
Houston,1.0
Houston,0.0
Houston,0.0
Houston,1.0
Houston,1.0
Houston,0.0
Houston,0.0
Indianapolis,2.0
Indianapolis,11.0
Indianapolis,0.0
Indianapolis,3.0
Indianapolis,0.0
Indianapolis,7.0
Indianapolis,0.0
Indianapolis,2.0
Indianapolis,1.0
Indianapolis,0.0
Indianapolis,3.0
Indianapolis,2.0
Indianapolis,4.0
Indianapolis,5.0
Indianapolis,1.0
Indianapolis,0.0
Indianapolis,0.0
Indianapolis,4.0
Indianapolis,2.0
Indianapolis,10.0
Indianapolis,1.0
Indianapolis,3.0
Indianapolis,0.0
Indianapolis,2.0
Indianapolis,4.0
Indianapolis,0.0
Indianapolis,0.0
Indianapolis,5.0
Indianapolis,3.0
Indianapolis,1.0
Indianapolis,4.0
Indianapolis,0.0
Indianapolis,3.0
Indianapolis,0.0
Indianapolis,2.0
Indianapolis,0.0
Indianapolis,2.0
Indianapolis,0.0
Indianapolis,3.0
Indianapolis,1.0
Jacksonville,4.0
Jacksonville,4.0
Jacksonville,2.0
Jacksonville,3.0
Jacksonville,1.0
Jacksonville,6.0
Jacksonville,3.0
Jacksonville,1.0
Jacksonville,5.0
Jacksonville,1.0
Jacksonville,2.0
Jacksonville,0.0
Jacksonville,0.0
Jacksonville,0.0
Jacksonville,1.0
Jacksonville,1.0
Jacksonville,3.0
Jacksonville,0.0
Jacksonville,2.0
Jacksonville,3.0
Jacksonville,3.0
Jacksonville,0.0
Jacksonville,1.0
Jacksonville,3.0
Jacksonville,3.0
Jacksonville,0.0
Jacksonville,3.0
Jacksonville,0.0
Jacksonville,0.0
Jacksonville,1.0
Jacksonville,1.0
Jacksonville,2.0
Jacksonville,0.0
Jacksonville,1.0
Jacksonville,0.0
Jacksonville,2.0
Jacksonville,2.0
Kansas City,0.0
Kansas City,1.0
Kansas City,2.0
Kansas City,3.0
Kansas City,1.0
Kansas City,0.0
Kansas City,2.0
Kansas City,2.0
Kansas City,0.0
Kansas City,0.0
Kansas City,0.0
Kansas City,4.0
Kansas City,0.0
Kansas City,1.0
Kansas City,1.0
Kansas City,0.0
Kansas City,4.0
Kansas City,4.0
Kansas City,0.0
Kansas City,2.0
Kansas City,3.0
Kansas City,4.0
Kansas City,4.0
Kansas City,0.0
Kansas City,1.0
Kansas City,5.0
Kansas City,2.0
Kansas City,1.0
Kansas City,2.0
Kansas City,5.0
Kansas City,8.0
Kansas City,3.0
Kansas City,2.0
Kansas City,0.0
Kansas City,1.0
Kansas City,0.0
Kansas City,1.0
Kansas City,0.0
Kansas City,2.0
Miami,1.0
Miami,4.0
Miami,0.0
Miami,3.0
Miami,0.0
Miami,4.0
Miami,2.0
Miami,5.0
Miami,3.0
Miami,0.0
Miami,0.0
Miami,0.0
Miami,4.0
Miami,3.0
Miami,1.0
Miami,3.0
Miami,2.0
Miami,4.0
Miami,4.0
Miami,5.0
Miami,4.0
Miami,1.0
Miami,2.0
Miami,7.0
Miami,5.0
Miami,1.0
Miami,1.0
Miami,2.0
Miami,2.0
Miami,0.0
Miami,1.0
New England,4.0
New England,6.0
New England,7.0
New England,2.0
New England,12.0
New England,6.0
New England,3.0
New England,1.0
New England,9.0
New England,6.0
New England,4.0
New England,5.0
New England,3.0
New England,7.0
New England,7.0
New England,2.0
New England,14.0
New England,1.0
New England,6.0
New England,1.0
New England,2.0
New England,4.0
New England,5.0
New England,4.0
New England,7.0
New England,7.0
New England,7.0
New England,6.0
New England,1.0
New England,2.0
New England,6.0
New England,2.0
New England,4.0
New England,0.0
New England,3.0
New England,6.0
New England,2.0
New England,9.0
New England,3.0
New England,2.0
New York Giants,18.0
New York Giants,15.0
New York Giants,19.0
New York Giants,23.0
New York Giants,26.0
New York Giants,35.0
New York Giants,31.0
New York Giants,21.0
New York Giants,39.0
New York Giants,6.0
New York Giants,12.0
New York Giants,16.0
New York Giants,20.0
New York Giants,23.0
New York Giants,14.0
New York Giants,15.0
New York Giants,21.0
New York Giants,12.0
New York Giants,19.0
New York Giants,29.0
New York Giants,16.0
New York Giants,46.0
New York Giants,29.0
New York Giants,10.0
New York Giants,16.0
New York Giants,22.0
New York Giants,24.0
New York Giants,20.0
New York Giants,23.0
New York Giants,33.0
New York Giants,9.0
New York Giants,28.0
New York Giants,18.0
New York Giants,24.0
New York Giants,26.0
New York Giants,35.0
New York Giants,22.0
New York Giants,39.0
New York Giants,31.0
New York Giants,14.0
New York Jets,34.0
New York Jets,23.0
New York Jets,28.0
New York Jets,20.0
New York Jets,30.0
New York Jets,12.0
New York Jets,14.0
New York Jets,31.0
New York Jets,22.0
New York Jets,18.0
New York Jets,15.0
New York Jets,10.0
New York Jets,16.0
New York Jets,38.0
New York Jets,11.0
New York Jets,18.0
New York Jets,17.0
New York Jets,22.0
New York Jets,20.0
New York Jets,29.0
New York Jets,11.0
New York Jets,26.0
New York Jets,8.0
New York Jets,10.0
New York Jets,12.0
New York Jets,27.0
New York Jets,22.0
New York Jets,18.0
New York Jets,25.0
New York Jets,14.0
New York Jets,20.0
New York Jets,28.0
New York Jets,7.0
New York Jets,26.0
New York Jets,28.0
New York Jets,15.0
New York Jets,44.0
New York Jets,27.0
New York Jets,30.0
New York Jets,32.0
Oakland,12.0
Oakland,15.0
Oakland,7.0
Oakland,12.0
Oakland,28.0
Oakland,15.0
Oakland,19.0
Oakland,19.0
Oakland,17.0
Oakland,25.0
Oakland,16.0
Oakland,17.0
Oakland,19.0
Oakland,7.0
Oakland,24.0
Oakland,8.0
Oakland,10.0
Oakland,15.0
Oakland,20.0
Oakland,14.0
Oakland,13.0
Oakland,20.0
Oakland,21.0
Oakland,10.0
Oakland,18.0
Oakland,30.0
Oakland,25.0
Oakland,49.0
Oakland,21.0
Oakland,11.0
Oakland,18.0
Oakland,21.0
Oakland,16.0
Oakland,22.0
Oakland,19.0
Oakland,15.0
Oakland,10.0
Philadelphia,2.0
Philadelphia,5.0
Philadelphia,5.0
Philadelphia,2.0
Philadelphia,2.0
Philadelphia,2.0
Philadelphia,1.0
Philadelphia,2.0
Philadelphia,2.0
Philadelphia,6.0
Philadelphia,1.0
Philadelphia,0.0
Philadelphia,4.0
Philadelphia,1.0
Philadelphia,1.0
Philadelphia,1.0
Philadelphia,2.0
Philadelphia,2.0
Philadelphia,1.0
Philadelphia,18.0
Philadelphia,3.0
Philadelphia,3.0
Philadelphia,10.0
Philadelphia,12.0
Philadelphia,3.0
Philadelphia,3.0
Philadelphia,1.0
Philadelphia,1.0
Philadelphia,1.0
Philadelphia,5.0
Philadelphia,2.0
Philadelphia,4.0
Philadelphia,5.0
Philadelphia,0.0
Philadelphia,2.0
Philadelphia,2.0
Philadelphia,0.0
Philadelphia,1.0
Philadelphia,5.0
Philadelphia,3.0
Pittsburgh,15.0
Pittsburgh,19.0
Pittsburgh,24.0
Pittsburgh,12.0
Pittsburgh,21.0
Pittsburgh,9.0
Pittsburgh,16.0
Pittsburgh,10.0
Pittsburgh,25.0
Pittsburgh,18.0
Pittsburgh,23.0
Pittsburgh,25.0
Pittsburgh,52.0
Pittsburgh,31.0
Pittsburgh,30.0
Pittsburgh,3.0
Pittsburgh,37.0
Pittsburgh,56.0
Pittsburgh,16.0
Pittsburgh,19.0
Pittsburgh,34.0
Pittsburgh,6.0
Pittsburgh,10.0
Pittsburgh,7.0
Pittsburgh,9.0
Pittsburgh,10.0
Pittsburgh,11.0
Pittsburgh,22.0
Pittsburgh,25.0
Pittsburgh,9.0
Pittsburgh,10.0
Pittsburgh,17.0
Pittsburgh,4.0
Pittsburgh,1.0
Pittsburgh,8.0
Pittsburgh,3.0
Pittsburgh,8.0
Pittsburgh,7.0
Pittsburgh,3.0
Pittsburgh,5.0
San Diego,15.0
San Diego,37.0
San Diego,29.0
San Diego,30.0
San Diego,69.0
San Diego,41.0
San Diego,30.0
San Diego,0.0
San Diego,23.0
San Diego,47.0
San Diego,45.0
San Diego,40.0
San Diego,31.0
San Diego,19.0
San Diego,12.0
San Diego,60.0
San Diego,29.0
San Diego,40.0
San Diego,13.0
San Diego,16.0
San Diego,24.0
San Diego,19.0
San Diego,36.0
San Diego,8.0
San Diego,20.0
San Diego,8.0
San Diego,18.0
San Diego,19.0
San Diego,19.0
San Diego,19.0
San Diego,17.0
San Diego,17.0
San Diego,18.0
San Diego,14.0
San Diego,13.0
San Diego,13.0
San Diego,17.0
San Diego,8.0
San Diego,14.0
San Diego,36.0
San Francisco,3.0
San Francisco,4.0
San Francisco,3.0
San Francisco,1.0
San Francisco,0.0
San Francisco,4.0
San Francisco,4.0
San Francisco,10.0
San Francisco,1.0
San Francisco,7.0
San Francisco,2.0
San Francisco,6.0
San Francisco,8.0
San Francisco,1.0
San Francisco,12.0
San Francisco,5.0
San Francisco,5.0
San Francisco,6.0
San Francisco,1.0
San Francisco,6.0
San Francisco,1.0
San Francisco,3.0
San Francisco,6.0
San Francisco,0.0
San Francisco,35.0
San Francisco,20.0
San Francisco,33.0
San Francisco,25.0
San Francisco,24.0
San Francisco,30.0
San Francisco,25.0
San Francisco,18.0
San Francisco,28.0
San Francisco,14.0
San Francisco,24.0
San Francisco,18.0
San Francisco,22.0
San Francisco,12.0
San Francisco,9.0
San Francisco,18.0
Seattle,0.0
Seattle,0.0
Seattle,0.0
Seattle,0.0
Seattle,0.0
Seattle,1.0
Seattle,0.0
Seattle,1.0
Seattle,0.0
Seattle,3.0
Seattle,2.0
Seattle,5.0
Seattle,1.0
Seattle,2.0
Seattle,4.0
Seattle,0.0
Seattle,2.0
Seattle,1.0
Seattle,0.0
Seattle,2.0
Seattle,0.0
Seattle,1.0
Seattle,1.0
Seattle,1.0
Seattle,0.0
Seattle,1.0
Seattle,0.0
Seattle,0.0
Seattle,0.0
Seattle,0.0
Seattle,1.0
Seattle,0.0
Seattle,0.0
Seattle,1.0
Seattle,1.0
Seattle,1.0
Seattle,0.0
Seattle,0.0
Seattle,0.0
Seattle,0.0
Tampa Bay,0.0
Tampa Bay,2.0
Tampa Bay,1.0
Tampa Bay,1.0
Tampa Bay,2.0
Tampa Bay,2.0
Tampa Bay,2.0
Tampa Bay,1.0
Tampa Bay,2.0
Tampa Bay,0.0
Tampa Bay,1.0
Tampa Bay,1.0
Tampa Bay,2.0
Tampa Bay,1.0
Tampa Bay,0.0
Tampa Bay,2.0
Tampa Bay,0.0
Tampa Bay,2.0
Tampa Bay,0.0
Tampa Bay,1.0
Tampa Bay,0.0
Tampa Bay,2.0
Tampa Bay,1.0
Tampa Bay,1.0
Tampa Bay,0.0
Tampa Bay,0.0
Tampa Bay,0.0
Tampa Bay,0.0
Tampa Bay,0.0
Tampa Bay,1.0
Tampa Bay,0.0
Tampa Bay,1.0
Tampa Bay,0.0
Tampa Bay,1.0
Tampa Bay,0.0
Tampa Bay,1.0
Tampa Bay,0.0
Tampa Bay,1.0
Tampa Bay,1.0
Tennessee,0.0
Tennessee,0.0
Tennessee,0.0
Tennessee,0.0
Tennessee,1.0
Tennessee,0.0
Tennessee,1.0
Tennessee,2.0
Tennessee,0.0
Tennessee,1.0
Tennessee,3.0
Tennessee,0.0
Tennessee,0.0
Tennessee,0.0
Tennessee,4.0
Tennessee,0.0
Tennessee,1.0
Tennessee,0.0
Tennessee,0.0
Tennessee,3.0
Tennessee,0.0
Tennessee,3.0
Tennessee,7.0
Tennessee,0.0
Tennessee,0.0
Tennessee,6.0
Tennessee,8.0
Tennessee,0.0
Tennessee,1.0
Tennessee,0.0
Tennessee,2.0
Tennessee,3.0
Tennessee,8.0
Tennessee,3.0
Tennessee,3.0
Tennessee,4.0
Tennessee,7.0
Tennessee,0.0
Tennessee,0.0
Tennessee,12.0
Washington,1.0
Washington,2.0
Washington,1.0
Washington,2.0
Washington,7.0
Washington,0.0
Washington,2.0
Washington,2.0
Washington,5.0
Washington,3.0
Washington,3.0
Washington,2.0
Washington,5.0
Washington,5.0
Washington,4.0
Washington,7.0
Washington,7.0
Washington,2.0
Washington,1.0
Washington,3.0
Washington,4.0
Washington,2.0
Washington,0.0
Washington,7.0
Washington,2.0
Washington,3.0
Washington,0.0
Washington,4.0
Washington,0.0
Washington,3.0
Washington,5.0
Washington,1.0
Washington,0.0
Washington,0.0
Washington,1.0
Washington,2.0
Washington,2.0
Washington,2.0
Washington,4.0
Washington,1.0

Answer 1

从链接复制数据并运行df = pd.read_clipboard()

使用pandas.DataFrame.plot

更新到pandas v1.2.4和matplotlib v3.3.4

然后使用你的代码

df = df.replace(np.nan, 0)
dfg = df.groupby(['home_team'])['arrests'].mean()

dfg.plot(kind='bar', title='Arrests', ylabel='Mean Arrests',
         xlabel='Home Team', figsize=(6, 5))

Answer 2

@piRSuared 写的很好，我刚刚完善了他的答案:)

## referenced to the answer by @piRSquared
df = df.replace(np.nan,0)
df = df.groupby(['home_team'])['arrests'].mean()

ax = df.plot(kind='bar', figsize=(10,6), color="indigo", fontsize=13);
ax.set_alpha(0.8)
ax.set_title("My Bar Plot", fontsize=22)
ax.set_ylabel("Some Heading on Y-Axis", fontsize=15);
plt.show()