In Python, we can use the DataFrame.sort_values() function to sort a DataFrame. In this article, we will discuss how to sort a DataFrame by a column using Python pandas.

We can use the following Python code to sort a DataFrame by a column.

import pandas

list1 = [[10, 21, 13, 14], [50, 60, 75, 82], [19, 10, 11, 126], [13, 140, 125, 16]]
df1 = pandas.DataFrame(list1, index=["Row 1", "Row 2", "Row 3", "Row 4"], columns=["Column 1", "Column 2", "Column 3", "Column 4"])
print("df1 before sorting: \n", df1)

df1.sort_values(by=["Column 2"], ascending=True, inplace=True)
print("df1 after sorting by Column 2: \n", df1)

The output of the above program will be:

df1 before sorting: 
        Column 1  Column 2  Column 3  Column 4
Row 1        10        21        13        14
Row 2        50        60        75        82
Row 3        19        10        11       126
Row 4        13       140       125        16

df1 after sorting by Column 2: 
        Column 1  Column 2  Column 3  Column 4
Row 3        19        10        11       126
Row 1        10        21        13        14
Row 2        50        60        75        82
Row 4        13       140       125        16

Here, the “by” parameter in the DataFrame.sort_values() function indicates the label of the column by which the DataFrame should be sorted.

df1.sort_values(by=["Column 2"], ascending=True, inplace=True)

The ascending=True parameter indicates that the soring should be done in ascending order. If we are sorting in descending order, then the ascending parameter should be False.

And the inplace=True parameter indicates that no new DataFrame is created after the sorting. Instead, the existing DataFrame is updated.