來自數據框 groupby 的條形圖

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()

我正在嘗試為數據框創建條形圖。 home_team 下是一堆隊名。 被捕人數是指每個日期的逮捕人數。 我基本上按團隊對數據進行了分組，該團隊的平均逮捕人數。 我正在嘗試為此創建一個條形圖，但我不確定如何繼續，因為一列沒有標題。

數據

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

從鏈接復制數據並運行df = pd.read_clipboard()

使用pandas.DataFrame.plot

更新到pandas v1.2.4和matplotlib v3.3.4

然后使用你的代碼

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 寫的很好，我剛剛完善了他的答案:)

## 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()