How to plot multiple pandas columns

Several column names may be provided to the y argument of the pandas plotting function. Those should be specified in a list, as follows.

df.plot(x="year", y=["action", "comedy"])

Complete example:

import matplotlib.pyplot as plt
import pandas as pd

df = pd.DataFrame({"year": [1914,1915,1916,1919,1920],
                   "action" : [2.6,3.4,3.25,2.8,1.75],
                   "comedy" : [2.5,2.9,3.0,3.3,3.4] })
df.plot(x="year", y=["action", "comedy"])
plt.show()

• When using pandas.DataFrame.plot, it's only necessary to specify a column to the x parameter.
  • The caveat is, the rest of the columns with numeric values will be used for y.
  • The following code contains extra columns to demonstrate. Note, 'date' is left as a string. However, if 'date' is converted to a datetime dtype, the plot API will also plot the 'date' column on the y-axis.
• If the dataframe includes many columns, some of which should not be plotted, then specify the y parameter as shown in this answer, but if the dataframe contains only columns to be plotted, then specify only the x parameter.
• In cases where the index is to be used as the x-axis, it's not necessary to specify x=.

import pandas as pd

# test data
data = {'year': [1914, 1915, 1916, 1919, 1920],
        'action': [2.67, 3.43, 3.26, 2.82, 1.75],
        'comedy': [2.53, 2.93, 3.02, 3.37, 3.45],
        'test1': ['a', 'b', 'c', 'd', 'e'],
        'date': ['1914-01-01', '1915-01-01', '1916-01-01', '1919-01-01', '1920-01-01']}

# create the dataframe
df = pd.DataFrame(data)

# display(df)
   year  action  comedy test1        date
0  1914    2.67    2.53     a  1914-01-01
1  1915    3.43    2.93     b  1915-01-01
2  1916    3.26    3.02     c  1916-01-01
3  1919    2.82    3.37     d  1919-01-01
4  1920    1.75    3.45     e  1920-01-01

# plot the dataframe
df.plot(x='year', figsize=(10, 5), grid=True)