matplotlib: plot multiple columns of pandas data frame on the bar chart

Question

I am using the following code to plot a bar-chart:

import matplotlib.pyplot as pls 
my_df.plot(x=\'my_timestampe\', y=\'col_A\', kind=\'bar\') 
plt.show()


        

Answer 1

Although the accepted answer works fine, since v0.21.0rc1 it gives a warning

UserWarning: Pandas doesn't allow columns to be created via a new attribute name

Instead, one can do

df[["X", "A", "B", "C"]].plot(x="X", kind="bar")

Answer 2

You can plot several columns at once by supplying a list of column names to the plot's y argument.

df.plot(x="X", y=["A", "B", "C"], kind="bar")

This will produce a graph where bars are sitting next to each other.

In order to have them overlapping, you would need to call plot several times, and supplying the axes to plot to as an argument ax to the plot.

import pandas as pd
import matplotlib.pyplot as plt
import numpy as np

y = np.random.rand(10,4)
y[:,0]= np.arange(10)
df = pd.DataFrame(y, columns=["X", "A", "B", "C"])

ax = df.plot(x="X", y="A", kind="bar")
df.plot(x="X", y="B", kind="bar", ax=ax, color="C2")
df.plot(x="X", y="C", kind="bar", ax=ax, color="C3")

plt.show()