DataFrame按列排序求助：含重复值时sort_values方法失效

Got it, let's break down what's happening here and get your DataFrame sorted correctly. The issue you're facing is almost certainly related to how you're using the inplace=True parameter in pandas' sort_values() method.

Why Your Current Code Isn't Working #

When you use inplace=True, the sort_values() method modifies your original DataFrame directly and returns None. So when you assign that result to sorted_data, you're actually setting sorted_data to None instead of the sorted DataFrame. That's why you aren't seeing your expected output!

Solution 1: Skip inplace=True (Recommended) #

The cleanest approach is to let sort_values() return a new sorted DataFrame, then assign that to your variable. This keeps your original DataFrame intact:

import pandas as pd

# Your original DataFrame
data = pd.DataFrame({'A': [2, 3, 2], 'B': [5, 9, 7]})

# Sort and store the result in a new variable
sorted_data = data.sort_values(by=['A'])

If you print sorted_data, you'll get exactly the output you want:

A  B
0  2  5
2  2  7
1  3  9

Solution 2: Use inplace=True Properly #

If you specifically want to modify the original DataFrame instead of creating a new one, just call the method without assigning the result (since it returns None):

data.sort_values(by=['A'], inplace=True)
# Now check the original 'data' variable
print(data)

This will update your original data to the sorted version.

Bonus: Ensure Exact Order with Multi-Column Sort #

To guarantee that rows with duplicate values in column A are sorted by column B (matching your expected result perfectly), you can sort by both columns at once:

sorted_data = data.sort_values(by=['A', 'B'])

This way, when A values are the same, pandas will sort those rows by B in ascending order (the default behavior).

内容的提问来源于stack exchange，提问作者user3789200