You can use the following methods to sort the rows of a pandas DataFrame based on the absolute value of a column:

**Method 1: Sort by Absolute Value (smallest abs. value shown first)**

df.reindex(df['my_column'].abs().sort_values().index)

**Method 2: Sort by Absolute Value (largest abs. value shown first)**

df.reindex(df['my_column'].abs().sort_values(ascending=False).index)

The following examples show how to use each method in practice with the following pandas DataFrame that contains information about various basketball players:

import pandas as pd #create DataFrame df = pd.DataFrame({'player': ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'], 'over_under': [4, -9, 2, 0, 1, 12, -4, -5]}) #view DataFrame print(df) player over_under 0 A 4 1 B -9 2 C 2 3 D 0 4 E 1 5 F 12 6 G -4 7 H -5

**Example 1: Sort by Absolute Value (smallest abs. value shown first)**

We can use the following syntax to sort the rows of the DataFrame based on the absolute value of the **over_under** column:

#sort DataFrame based on absolute value of over_under column df_sorted = df.reindex(df['over_under'].abs().sort_values().index) #view sorted DataFrame print(df_sorted) player over_under 3 D 0 4 E 1 2 C 2 0 A 4 6 G -4 7 H -5 1 B -9 5 F 12

Notice that the rows are sorted from smallest absolute value in the **over_under** column to largest absolute value.

**Example 2: Sort by Absolute Value (largest abs. value shown first)**

We can use the following syntax to sort the rows of the DataFrame based on the absolute value of the **over_under** column:

#sort DataFrame based on absolute value of over_under column df_sorted = df.reindex(df['over_under'].abs().sort_values(ascending=False).index) #view sorted DataFrame print(df_sorted) player over_under 5 F 12 1 B -9 7 H -5 0 A 4 6 G -4 2 C 2 4 E 1 3 D 0

Notice that the rows are sorted from largest absolute value in the **over_under** column to smallest absolute value.

**Note**: You can find the complete documentation for the pandas **sort_values()** function here.

**Additional Resources**

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

Pandas: How to Sort by Date

Pandas: How to Sort Columns by Name

Pandas: How to Sort by Both Index and Column