Pandas: How to Find the Difference Between Two Rows

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You can use the DataFrame.diff() function to find the difference between two rows in a pandas DataFrame.

This function uses the following syntax:

DataFrame.diff(periods=1, axis=0)

where:

• periods: The number of previous rows for calculating the difference.
• axis: Find difference over rows (0) or columns (1).

The following examples show how to use this function in practice.

Example 1: Find Difference Between Each Previous Row

Suppose we have the following pandas DataFrame:

import pandas as pd

#create DataFrame
df = pd.DataFrame({'period': [1, 2, 3, 4, 5, 6, 7, 8],
                   'sales': [12, 14, 15, 15, 18, 20, 19, 24],
                   'returns': [2, 2, 3, 3, 5, 4, 4, 6]})

#view DataFrame
df

	period	sales	returns
0	1	12	2
1	2	14	2
2	3	15	3
3	4	15	3
4	5	18	5
5	6	20	4
6	7	19	4
7	8	24	6

The following code shows how to find the difference between every current row in a DataFrame and the previous row:

#add new column to represent sales differences between each row
df['sales_diff'] = df['sales'].diff()

#view DataFrame
df

        period	sales	returns	 sales_diff
0	1	12	2	 NaN
1	2	14	2	 2.0
2	3	15	3	 1.0
3	4	15	3	 0.0
4	5	18	5	 3.0
5	6	20	4	 2.0
6	7	19	4	-1.0
7	8	24	6	 5.0

Note that we can also find the difference between several rows prior. For example, the following code shows how to find the difference between each current row and the row that occurred three rows earlier:

#add new column to represent sales differences between current row and 3 rows earlier
df['sales_diff'] = df['sales'].diff(periods=3)

#view DataFrame
df

        period	sales	returns	 sales_diff
0	1	12	2	 NaN
1	2	14	2	 NaN
2	3	15	3	 NaN
3	4	15	3	 3.0
4	5	18	5	 4.0
5	6	20	4	 5.0
6	7	19	4	 4.0
7	8	24	6	 6.0

Example 2: Find Difference Based on Condition

We can also filter the DataFrame to show rows where the difference between the current row and the previous row is less than or greater than some value.

For example, the following code returns only the rows where the value in the current row is less than the value in the previous row:

import pandas as pd

#create DataFrame
df = pd.DataFrame({'period': [1, 2, 3, 4, 5, 6, 7, 8],
                   'sales': [12, 14, 15, 13, 18, 20, 19, 24],
                   'returns': [2, 2, 3, 3, 5, 4, 4, 6]})

#find difference between each current row and the previous row
df['sales_diff'] = df['sales'].diff()

#filter for rows where difference is less than zero
df = df[df['sales_diff']0]

#view DataFrame
df

        period	sales	returns	 sales_diff
3	4	13	3	 -2.0
6	7	19	4	 -1.0

Additional Resources

How to Find Unique Values in Multiple Columns in Pandas
How to Filter a Pandas DataFrame by Column Values
How to Select Rows by Index in a Pandas DataFrame