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Python pandas / matplotlib annotating labels above bar chart columns [duplicate]

How do I add the label for the value to display above the bars in the bargraph here:

import pandas as pd
import matplotlib.pyplot as plt

df=pd.DataFrame({'Users': [ 'Bob', 'Jim', 'Ted', 'Jesus', 'James'],
                 'Score': [10,2,5,6,7],})

df = df.set_index('Users')
df.plot(kind='bar',  title='Scores')

plt.show()
like image 720
ccsv Avatar asked May 11 '14 10:05

ccsv


2 Answers

A solution without accessing the DataFrame is to use the patches attribute:

ax = df.plot.bar(title="Scores")
for p in ax.patches:
    ax.annotate(str(p.get_height()), xy=(p.get_x(), p.get_height()))

Note you have to play around with the xy kwarg (2nd arg) to get the label position you desire.

Vertical Bars

I found this formatting to be the best in general:

ax.annotate("%.2f" % p.get_height(), (p.get_x() + p.get_width() / 2., p.get_height()), ha='center', va='center', xytext=(0, 10), textcoords='offset points')

Horizontal Bars

I found the following format to work well with horizontal bars:

ax.annotate("%.2f" % p.get_width(), (p.get_x() + p.get_width(), p.get_y()), xytext=(5, 10), textcoords='offset points')
like image 125
Kamil Sindi Avatar answered Oct 09 '22 22:10

Kamil Sindi


Capture the axis where the plot is drawn into, then manipulate it as a usual matplotlib object. Putting the value above the bar will be something like this:

ax = df.plot(kind='bar',  title='Scores', rot=0)
ax.set_ylim(0, 12)
for i, label in enumerate(list(df.index)):
    score = df.loc[label]['Score']
    ax.annotate(str(score), (i, score + 0.2))

enter image description here

like image 17
joemar.ct Avatar answered Oct 09 '22 20:10

joemar.ct