Convert upper triangular matrix to lower triangular matrix in Pandas Dataframe

Question

I tried using transpose and adding some twists to it but it didn't workout

Convert Upper:

 Data : 
     0         1         2      3  
0  5         NaN       NaN      NaN
1  1         NaN       NaN      NaN
2  0.21      0.31      0.41     0.51   
3  0.32      0.42      0.52     NaN
4  0.43      0.53      NaN      NaN
5  0.54      NaN       NaN      Nan

to:

 Data : 
     0         1         2      3  
0  5         NaN       NaN      NaN
1  1         NaN       NaN      NaN
2  0.21      NaN       NaN      NaN   
3  0.31      0.32      NaN      NaN
4  0.41      0.42      0.43     NaN
5  0.51      0.52      0.53     0.54

without effecting the first two rows

jezrael · Accepted Answer · 2019-04-23T14:14:22.803

3

I believe you need justify with sort with exclude first 2 rows:

arr = justify(df.values[2:,:], invalid_val=np.nan, side='down', axis=0)
df.values[2:,:] = np.sort(arr, axis=1)

print (df)
      0     1     2     3
0  5.00   NaN   NaN   NaN
1  1.00   NaN   NaN   NaN
2  0.21   NaN   NaN   NaN
3  0.31  0.32   NaN   NaN
4  0.41  0.42  0.43   NaN
5  0.51  0.52  0.53  0.54

edited Apr 23 '19 at 14:14

answered Apr 23 '19 at 14:09

jezrael

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Is there a way to do it vice versa too? – Rookie Apr 23 '19 at 14:35
@Rookie - Try `df.values[2:,:] = justify(df.values[2:,:].T, invalid_val=np.nan, side='left', axis=1)` – jezrael Apr 23 '19 at 14:39

score 2 · Answer 2 · answered Apr 23 '19 at 14:08

IIUC you can first index the dataframe from row 2 onwards and swap with the transpose, and then you can use justify so that all NaNs are at the top:

df.iloc[2:,:] = df.iloc[2:,:].T.values
pd.Dataframe(justify(df.values.astype(float), invalid_val=np.nan, side='down', axis=0))

   0         1         2      3  
0  5         NaN       NaN      NaN
1  1         NaN       NaN      NaN
2  0.21      NaN       NaN      NaN   
3  0.31      0.32      NaN      NaN
4  0.41      0.42      0.43     NaN
5  0.51      0.52      0.53     0.54

Convert upper triangular matrix to lower triangular matrix in Pandas Dataframe

2 Answers2