Python Dataframe - 如何按数字和字母（升序）和字符串长度（降序）对值进行排序

Question

I want to sort 1 column in the dataframe by following logic:

1. Numeric goes first - by ascending order;
2. Alphabet follows - by ascending order;
3. Lastly, string length - by descending order.

Example dataframe - using name column to sort and eventually adding an 'Order' column too:

import pandas as pd
df_1 = pd.DataFrame({'name': ['3D', '3DD', 'AC', 'AC-', 'BE', '2C','BED'], 'score': [2, 4, 2, 3, 10, 8, 2]})

I have tried sort_values() per below,

df_1['Len'] = df_1['name'].apply(lambda x: len(x))
df_1.sort_values(by=['name', 'Len'], ascending=[True, False], inplace=True,ignore_index=True)
df_1.drop(columns=['Len'], inplace=True)
df_1['Order'] = df_1.index+1

however, giving me this result - basically the string length by descending sorting didn't work:

   name score   Order
0   2C  8   1
1   3D  2   2
2   3DD 4   3
3   AC  2   4
4   AC- 3   5
5   BE  10  6
6   BED 2   7

Based on my above sorting logics, this is the desired results:

  name  score   Order
0   2C  8   1
1   3DD 4   2
2   3D  2   3
3   AC- 3   4
4   AC  2   5
5   BED 2   6
6   BE  10  7

Thank you!

Answer 1

You can fill the names to have the same length using the last element of the ASCII table so pandas will know how to sort automatically.

          name
0           2C
1           3D
2          3DD
3           AC
4          AC-
5           BE
6          BED

max_length = max(df.name.str.len())

df.loc['sort_name']=df.name.str.pad(max_length,'right','~')

df.sort_values('sort_name', inplace=True, ignore_index=True)
  name sort_name
0   2C       2C~
2  3DD       3DD
1   3D       3D~
4  AC-       AC-
3   AC       AC~
6  BED       BED
5   BE       BE~

This will take the maximum length of the column as the number to pad.

After you have sorted the dataframe you can delete the column with

df = df.drop('sort_name', axis=1)