Sorting dataframe based on multiple columns and conditions

Question

I am trying to sort the following dataframe based on rolls descending first, followed by diff_vto ascending for positive values, finally by diff_vto ascending for negative values. This is the original dataframe:

    day  prob  vto  rolls  diff  diff_vto
0     1    10   14   27.0   0.0       -13
1     2    10   14   20.0   3.0       -12
2     3     7   14   16.0   4.0       -11
3     4     3   14   12.0  -3.0       -10
4     5     6   14   17.0   3.0        -9
5     6     3   14   14.0  -5.0        -8
6     7     8   14   14.0   5.0        -7
7     8     3   14    9.0   0.0        -6
8     9     3   14    9.0   0.0        -5
9    10     3   14   17.0   0.0        -4
10   11     3   14   22.0  -8.0        -3
11   12    11   14   27.0   3.0        -2
12   13     8   14   23.0   0.0        -1
13   14     8   14   25.0   1.0         0
14   15     7   14   27.0  -3.0         1

This is the code in case you wish to replicate it:

    import pandas as pd 
    a = {'day':[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15],'prob':[10,10,7,3,6,3,8,3,3,3,3,11,8,8,7],'vto':[14,14,14,14,14,14,14,14,14,14,14,14,14,14,14]}
    df = pd.DataFrame(a)
    df.loc[len(df)+1] = df.loc[0] #Add an extra 2 days for rolling rolling
    df.loc[len(df)+2] = df.loc[1] #Add an extra 2 days for rolling
    df['rolls'] = df['prob'].rolling(3).sum() 
    df['rolls'] = df['rolls'].shift(periods=-2) #Displace rolls to match the index + 2
    df['diff'] = df['prob'].diff(periods=-1) #Prob[i] - Prob[i+1]
    df['diff_vto'] = df['day'] - df['vto'] 
    df = df.head(15)
    print(df)

I want to be able to sort the dataframe, based on rolls (descending) followed by the minimum value of diff_vto when it's possitive (ascending), followed by the minimum value of diff_vto when it's negative (ascending). Based on the dataframe posted above, this would be the expected output:

    day  prob  vto  rolls  diff  diff_vto
14   15     7   14   27.0  -3.0         1
0     1    10   14   27.0   0.0       -13
11   12    11   14   27.0   3.0        -2
13   14     8   14   25.0   1.0         0
12   13     8   14   23.0   0.0        -1
10   11     3   14   22.0  -8.0        -3
1     2    10   14   20.0   3.0       -12
4     5     6   14   17.0   3.0        -9
9    10     3   14   17.0   0.0        -4
2     3     7   14   16.0   4.0       -11
5     6     3   14   14.0  -5.0        -8
6     7     8   14   14.0   5.0        -7
3     4     3   14   12.0  -3.0       -10
7     8     3   14    9.0   0.0        -6
8     9     3   14    9.0   0.0        -5

I have obviously tried applying .sort_values() but I can't get the conditional sorting to work on diff_vto because setting it to ascending will obviously place the negative values before the positive ones. Could I please get a suggestion? Thanks.

Answer 1

You want to sort by diff_vto>0 and abs(diff_vto), both decreasing:

df['pos'] = df['diff_vto'].gt(0)
df['abs'] = df['diff_vto'].abs()

df.sort_values(['rolls', 'pos', 'abs'], ascending=[False, False, False])

Output (you can drop pos and abs if needed):

    day  prob  vto  rolls  diff  diff_vto    pos  abs
14   15     7   14   27.0  -3.0         1   True    1
0     1    10   14   27.0   0.0       -13  False   13
11   12    11   14   27.0   3.0        -2  False    2
13   14     8   14   25.0   1.0         0  False    0
12   13     8   14   23.0   0.0        -1  False    1
10   11     3   14   22.0  -8.0        -3  False    3
1     2    10   14   20.0   3.0       -12  False   12
4     5     6   14   17.0   3.0        -9  False    9
9    10     3   14   17.0   0.0        -4  False    4
2     3     7   14   16.0   4.0       -11  False   11
5     6     3   14   14.0  -5.0        -8  False    8
6     7     8   14   14.0   5.0        -7  False    7
3     4     3   14   12.0  -3.0       -10  False   10
7     8     3   14    9.0   0.0        -6  False    6
8     9     3   14    9.0   0.0        -5  False    5