The Python Oracle

Add x and y labels to a pandas plot

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Chapters
00:00 Question
00:43 Accepted answer (Score 23)
01:02 Answer 2 (Score 436)
01:46 Answer 3 (Score 62)
02:11 Answer 4 (Score 32)
02:48 Thank you

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Full question
https://stackoverflow.com/questions/2148...

Accepted answer links:
[image]: https://i.stack.imgur.com/zPRPM.png

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Content licensed under CC BY-SA
https://meta.stackexchange.com/help/lice...

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Tags
#python #pandas #dataframe #matplotlib

#avk47


ANSWER 1

Score 447


The df.plot() function returns a matplotlib.axes.AxesSubplot object. You can set the labels on that object.

ax = df2.plot(lw=2, colormap='jet', marker='.', markersize=10, title='Video streaming dropout by category')
ax.set_xlabel("x label")
ax.set_ylabel("y label")

enter image description here

Or, more succinctly: ax.set(xlabel="x label", ylabel="y label").

Alternatively, the index x-axis label is automatically set to the Index name, if it has one. so df2.index.name = 'x label' would work too.



ANSWER 2

Score 64


You can use do it like this:

import matplotlib.pyplot as plt 
import pandas as pd

plt.figure()
values = [[1, 2], [2, 5]]
df2 = pd.DataFrame(values, columns=['Type A', 'Type B'], 
                   index=['Index 1', 'Index 2'])
df2.plot(lw=2, colormap='jet', marker='.', markersize=10,
         title='Video streaming dropout by category')
plt.xlabel('xlabel')
plt.ylabel('ylabel')
plt.show()

Obviously you have to replace the strings 'xlabel' and 'ylabel' with what you want them to be.



ANSWER 3

Score 33


If you label the columns and index of your DataFrame, pandas will automatically supply appropriate labels:

import pandas as pd
values = [[1, 2], [2, 5]]
df = pd.DataFrame(values, columns=['Type A', 'Type B'], 
                  index=['Index 1', 'Index 2'])
df.columns.name = 'Type'
df.index.name = 'Index'
df.plot(lw=2, colormap='jet', marker='.', markersize=10, 
        title='Video streaming dropout by category')

enter image description here

In this case, you'll still need to supply y-labels manually (e.g., via plt.ylabel as shown in the other answers).



ANSWER 4

Score 31


It is possible to set both labels together with axis.set function. Look for the example:

import pandas as pd
import matplotlib.pyplot as plt
values = [[1,2], [2,5]]
df2 = pd.DataFrame(values, columns=['Type A', 'Type B'], index=['Index 1','Index 2'])
ax = df2.plot(lw=2,colormap='jet',marker='.',markersize=10,title='Video streaming dropout by category')
# set labels for both axes
ax.set(xlabel='x axis', ylabel='y axis')
plt.show()

enter image description here