python - selecting a column value based on a different column value after applying Groupby -


i able work, not after apply groupby. in example want have last column contain lowest value column x. have popuymated df column called yminx abc column like. can't value of abc local (after groupby) min.

in [3]:  df out[3]:    symbol   x   y  yminx 0     ibm  12  27     58 1     ibm   1  58     58 2     ibm  13  39     58 3     ibm   4  45     58 4      gs   5  72     44 5      gs  15  54     44 6      gs  20  50     44 7      gs   4  90     44 8      gs  14  39     44 9      gs   2  44     44 10     gs   7  79     44 11     gs  12  27     44 12     gs  11  66     44  df['try']=df.groupby(['symbol'])['x'].transform('min') df['cond1'] = df['x'] == min(df['x'])                      df['abc']= np.select(df['cond1'],df['y'])       symbol   x   y  yminx  cond1  abc  try 0     ibm  12  27     58  false   58    1 1     ibm   1  58     58   true   58    1 2     ibm  13  39     58  false   58    1 3     ibm   4  45     58  false   58    1 4      gs   5  72     90  false   58    2 5      gs  15  54     90  false   58    2 6      gs  20  50     90  false   58    2 7      gs   4  90     90  false   58    2 8      gs  14  39     90  false   58    2 9      gs   2  44     90  false   58    2 10     gs   7  79     90  false   58    2 11     gs  12  27     90  false   58    2 12     gs  11  66     90  false   58    2

in output see 58 being selected nin ibm when gs same min carried on if groupby never referenced

i sure it's syntax thing stuck.

thanks help

john

one way work indices of minimum values. example:

>>> imin = df.groupby("symbol")["x"].transform("idxmin") >>> df["yminx"] = df.loc[imin, "y"].values >>> df    symbol   x   y  yminx 0     ibm  12  27     58 1     ibm   1  58     58 2     ibm  13  39     58 3     ibm   4  45     58 4      gs   5  72     44 5      gs  15  54     44 6      gs  20  50     44 7      gs   4  90     44 8      gs  14  39     44 9      gs   2  44     44 10     gs   7  79     44 11     gs  12  27     44 12     gs  11  66     44

(the values needed because result of df.loc has own index, , want ignore , care values instead.)


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