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()
I'm trying to create a bar graph for dataframe. Under home_team are a bunch of team names. Under arrests are a number of arrests at each date. I've basically grouped the data by teams with the average arrests for that team. I'm trying to create a bar graph for this but am not sure how to proceed since one column doesn't have a header.
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
grouped bar charts are Bar charts in which multiple sets of data items are compared, with a single color used to denote a specific series across all sets. As with basic Bar charts, both vertical and horizontal versions of grouped bar charts are available.
copying data from your link and running df = pd.read_clipboard()
Plot using pandas.DataFrame.plot
Updated to pandas v1.2.4
and matplotlib v3.3.4
then using your code
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))
Good one by @piRSuared, and I just beautified their answer :)
## 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()
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