CODEWITHSUNDEEP
pythonpython-3.xpandasdataframematplotlib
JAB
JAB

Reputation: 12799

How to plot columns on x axis and use index as y axis using pandas?

I have a data frame with 60 columns. I want the columns to be plotted on the X axis, and the index to be plotted on the y-axis.

    df.plot()

The above code puts the index on the x-axis by default. I am unable to work out how to switch the axes. Any help appreciated.

Upvotes: 11

Views: 21544

Answers (1)

Nipun Batra
Nipun Batra

Reputation: 11387

Maybe you can plot the DataFrame transposed.

Creating a DataFrame with 10 columns and 5 rows.

In [1]: import pandas as pd
In [2]: import numpy as np
In [3]: df = pd.DataFrame(np.random.rand(5,10))
In [4]: df
Out[4]: 
          0         1         2         3         4         5         6  \
0  0.221466  0.375541  0.318416  0.695447  0.117332  0.836268  0.326673   
1  0.439128  0.546087  0.380608  0.599192  0.553365  0.739253  0.984701   
2  0.189311  0.799067  0.322041  0.171035  0.595848  0.106069  0.940712   
3  0.971887  0.416420  0.945873  0.828611  0.055950  0.690107  0.526104   
4  0.643041  0.800376  0.010879  0.677169  0.268208  0.151503  0.062268   

          7         8         9  
0  0.690805  0.741308  0.487934  
1  0.827711  0.284417  0.878259  
2  0.734911  0.597626  0.256107  
3  0.583156  0.398342  0.406590  
4  0.247892  0.990469  0.611637 

In [8]: df.plot()

enter image description here

In [9]: df.T.plot()

enter image description here

The following are the contents of the DataFrame transposed.

In [10]: df.T
Out[10]: 
          0         1         2         3         4
0  0.221466  0.439128  0.189311  0.971887  0.643041
1  0.375541  0.546087  0.799067  0.416420  0.800376
2  0.318416  0.380608  0.322041  0.945873  0.010879
3  0.695447  0.599192  0.171035  0.828611  0.677169
4  0.117332  0.553365  0.595848  0.055950  0.268208
5  0.836268  0.739253  0.106069  0.690107  0.151503
6  0.326673  0.984701  0.940712  0.526104  0.062268
7  0.690805  0.827711  0.734911  0.583156  0.247892
8  0.741308  0.284417  0.597626  0.398342  0.990469
9  0.487934  0.878259  0.256107  0.406590  0.611637

Upvotes: 18

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