Pandas sort_values method not sorting Pandas DataFrame

Question

I am trying to sort a dataframe, but the sort_values method seems not to be working. I have checked other stackoverflow posts on the same issue, but they do not seem to help me.

Code.py

    var_df = pd.DataFrame(columns=['Variable','Remaining values','Degrees'])
    var_df.loc[0] = ['V1', 1, 2]
    var_df.loc[1] = ['V2', 2, 3]
    var_df.loc[2] = ['V3', 2, 1]
    var_df.loc[3] = ['V4', 4, 5]
    var_df.loc[4] = ['V5', 5, 4]
    var_df.loc[5] = ['V6', 5, 7]
    var_df.loc[6] = ['V7', 6, 1]
    
    print(var_df)
    print('\n------------\n')
    
    new_var_df = var_df.sort_values(by=['Remaining values', 'Degrees'], inplace=True, ascending=[True, False])
    new_var_df = var_df.reset_index(drop=True)
    print(new_var_df)

When I print out var_df, and new_var_df, they have the same output:

   Variable Remaining values Degrees
0       V1                1       2
1       V2                2       3
2       V3                2       1
3       V4                4       5
4       V6                5       7
5       V5                5       4
6       V7                6       1

This is the output I am expecting after sorting

Im not sure if it is a typo or just the same code you are using, but you are creating the new_var_df by sorting var_df, then overwriting the new_var_df by resetting index on var_df, so you are getting the same dataframe. Shouldn't it be new_var_df=new_var_df.reset_index(drop=True)? — Yashar
– Yashar, Commented Oct 31, 2020 at 19:49
@Yashar, thanks a lot. That was the problem. I was resetting the index of the wrong DataFrame(var_df) — David.B
– David.B, Commented Nov 1, 2020 at 13:01

BENY · Accepted Answer · 2020-10-31 15:03:53Z

2

Assign then you do not need inplace

new_var_df = var_df.sort_values(by=['Remaining values', 'Degrees'], ascending=[True, False])

answered Oct 31, 2020 at 15:03

BENY

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3 Comments

BENY Over a year ago

@David.B look at your original df , it is already order by by=['Remaining values', 'Degrees'], ascending=[True, False]

David.B Over a year ago

I dont know if it already doing that. please check the question. i added the output i'm actually looking for

BENY Over a year ago

@David.B check you expected output and compared with original df , still the same

David.B · Accepted Answer · 2020-11-01 13:04:39Z

0

Thanks @Yashar.

The problem was caused by a typo on my end. I was resetting the index of the wrong DataFrame(var_df), instead of new_var_df.

I solved it by changing this new_var_df = var_df.reset_index(drop=True) to

new_var_df = new_var_df.reset_index(drop=True)

answered Nov 1, 2020 at 13:04

David.B

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