Pandas Error: DataFrame object has no attribute ‘sort’

Updated: February 21, 2024 By: Guest Contributor Post a comment

The Problem

Pandas is a powerful data manipulation library in Python, but sometimes those new to it or even experienced users can run into errors that may seem perplexing at first. One such error is DataFrame object has no attribute 'sort'. This error message is quite straightforward but solving it requires understanding why it happens and what alternatives are available.

Reason for the Error

This error occurs because the sort method no longer exists in the Pandas DataFrame API. It was deprecated and eventually removed. Users trying to use sort directly on a DataFrame will encounter this error. The correct method to use is sort_values() for sorting by values or sort_index() for sorting by the index.

Solution 1: Use sort_values() to Sort DataFrame by Columns

The sort_values() method is the right approach when you want to sort your DataFrame based on the values of one or more columns. It’s highly customizable and includes parameters for specifying the sorting order and whether to sort in place.

  • Step 1: Identify the column(s) you want to sort by.
  • Step 2: Decide on the sorting order (ascending or descending).
  • Step 3: Use the sort_values() method on your DataFrame.


import pandas as pd
data = {'Name': ['Tom', 'Nick', 'Julia', 'Bridget'], 'Age': [25, 30, 22, 35]}
df = pd.DataFrame(data)
sorted_df = df.sort_values(by='Age')

Notes: This method allows sorting by multiple columns as well, and you can specify different sorting orders for each column. However, remember that sort_values() returns a new DataFrame by default unless you set inplace=True.

Solution 2: Use sort_index() to Sort DataFrame by Index

If your DataFrame’s organization relies heavily on its index, using sort_index() could be more appropriate. This method sorts the DataFrame based on its index values, which can be particularly useful after filtering or grouping operations that might leave the index in a non-sequential order.

  • Step 1: Decide on the sorting order for the index (ascending or descending).
  • Step 2: Use the sort_index() method on your DataFrame.


import pandas as pd
data = {'Name': ['Tom', 'Nick', 'Julia', 'Bridget'], 'Age': [25, 30, 22, 35]}
df = pd.DataFrame(data, index=[2, 1, 3, 0])
sorted_df = df.sort_index()

Notes: Like sort_values(), sort_index() also offers an inplace parameter. Although sorting by index is less common than by values, it’s invaluable when needed, and understanding it offers greater flexibility in managing DataFrames.