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。在 home_team 下是一堆团队名称。每个日期都有许多人被捕。我基本上按团队对数据进行了分组，并对该团队的平均逮捕次数进行了分组。我正在尝试为此创建一个条形图，但不确定如何继续，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

从您的链接复制数据并运行df = pd.read_clipboard()

使用pandas.DataFrame.plot绘图

更新为pandas v1.2.4 和matplotlib v3.3.4

然后使用您的代码

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 写的不错，我刚刚对他的回答做了改进:)

## 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()