How to Plot a Pandas Series (With Examples)

There are two common ways to plot the values in a pandas Series:

Method 1: Create Line Plot from pandas Series

import pandas as pd
import matplotlib.pyplot as plt

plt.plot(my_series.index, my_series.values)

Method 2: Create Histogram from pandas Series

import pandas as pd
import matplotlib.pyplot as plt

my_series.plot(kind='hist')

The following examples show how to use each method in practice.

Example 1: Create Line Plot from pandas Series

The following code shows how to create a line plot from a pandas Series:

import pandas as pd
import matplotlib.pyplot as plt

#create pandas Series
my_series = pd.Series([2, 2, 2, 3, 3, 4, 5, 7, 8, 9, 12, 12, 14, 15, 16, 16, 18,
                       19, 22, 22, 22, 25, 26, 27, 30, 33, 33, 33, 34, 35])

#create line plot to visualize values in Series
plt.plot(my_series.index, my_series.values)

The x-axis shows the index values of the pandas Series and the y-axis shows the actual values in the Series.

You can also use various functions from pandas and matplotlib to customize the appearance of the line as well as the axis labels and title of the plot:

#create customized line plot
plt.plot(my_series.index, my_series.values, color='red', linewidth=2.5)

#add axis labels and title
plt.xlabel('Index')
plt.ylabel('Values')
plt.title('Line Plot of Pandas Series')

pandas plot Series as line chart

Example 2: Create Histogram from pandas Series

The following code shows how to create a histogram from a pandas Series:

import pandas as pd
import matplotlib.pyplot as plt

#create pandas Series
my_series = pd.Series([2, 2, 2, 3, 3, 4, 5, 7, 8, 9, 12, 12, 14, 15, 16, 16, 18,
                       19, 22, 22, 22, 25, 26, 27, 30, 33, 33, 33, 34, 35])

#create histogram visualize distribution of values in Series
my_series.plot(kind='hist')

The x-axis shows the values of the pandas Series and the y-axis shows the frequency of the values.

You can also use various functions from pandas and matplotlib to customize the appearance of the histogram as well as the number of bins used in the histogram:

#create histogram with 15 bins
my_series.plot(kind='hist', edgecolor='black', color='gold', bins=15)

#add axis labels and title
plt.xlabel('Values')
plt.title('Histogram of Pandas Series')