A **rolling median **is the median of a certain number of previous periods in a time series.

To calculate the rolling median for a column in a pandas DataFrame, we can use the following syntax:

#calculate rolling median of previous 3 periods df['column_name'].rolling(3).median()

The following example shows how to use this function in practice.

**Example : Calculate Rolling Median of Column**

Suppose we have the following pandas DataFrame:

import pandas as pd #create DataFrame df = pd.DataFrame({'month': [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], 'leads': [13, 15, 16, 15, 17, 20, 22, 24, 25, 26, 23, 24], 'sales': [22, 24, 23, 27, 26, 26, 27, 30, 33, 32, 27, 25]}) #view DataFrame df month leads sales 0 1 13 22 1 2 15 24 2 3 16 23 3 4 15 27 4 5 17 26 5 6 20 26 6 7 22 27 7 8 24 30 8 9 25 33 9 10 26 32 10 11 23 27 11 12 24 25

We can use the following syntax to create a new column that contains the rolling median of ‘sales’ for the previous 3 periods:

#calculate 3-month rolling median df['sales_rolling3'] = df['sales'].rolling(3).median() #view updated data frame df month leads sales sales_rolling3 0 1 13 22 NaN 1 2 15 24 NaN 2 3 16 23 23.0 3 4 15 27 24.0 4 5 17 26 26.0 5 6 20 26 26.0 6 7 22 27 26.0 7 8 24 30 27.0 8 9 25 33 30.0 9 10 26 32 32.0 10 11 23 27 32.0 11 12 24 25 27.0

We can manually verify that the rolling median sales displayed for month 3 is the median of the previous 3 months:

- Median of 22, 24, 23 =
**23.0**

Similarly, we can verify the rolling median sales of month 4:

- Median of 24, 23, 27 =
**24.0**

We can use similar syntax to calculate the rolling 6-month median:

#calculate 6-month rolling median df['sales_rolling6'] = df['sales'].rolling(6).median() #view updated data frame df month leads sales sales_rolling3 sales_rolling6 0 1 13 22 NaN NaN 1 2 15 24 NaN NaN 2 3 16 23 23.0 NaN 3 4 15 27 24.0 NaN 4 5 17 26 26.0 NaN 5 6 20 26 26.0 25.0 6 7 22 27 26.0 26.0 7 8 24 30 27.0 26.5 8 9 25 33 30.0 27.0 9 10 26 32 32.0 28.5 10 11 23 27 32.0 28.5 11 12 24 25 27.0 28.5

**Additional Resources**

The following tutorials explain how to perform other common operations in pandas:

How to Calculate a Rolling Mean in Pandas

How to Calculate Rolling Correlation in Pandas

How to Calculate Percent Change in Pandas