python - Pandas DataFrame merge choosing the higher value -


i have 2 dataframes this: 

         1          2          3  0   61.579   0.000000  47.279861 1    0.000   0.000000   0.000000 2   62.700   9.180000  48.479861 3   56.100  40.180000  71.679861 4   73.100  50.930000  71.679861 5   88.300  37.930000  36.479861

i need merge them choosing each time higher value. values float. ideas? have loop on dataframes?

you need concat first , groupby index , aggregate max:

df1 = pd.dataframe({0:[4,5,4],                     1:[7,8,9]})  print (df1)    0  1 0  4  7 1  5  8 2  4  9   df2 = pd.dataframe({0:[8,5,6],                     1:[9,4,4]})  print (df2)    0  1 0  8  9 1  5  4 2  6  4  df = pd.concat([df1, df2]).groupby(level=0).max() print (df)    0  1 0  8  9 1  5  8 2  6  9

if need faster solution use numpy.where:

a = df1.values b = df2.values df = pd.dataframe(np.where(a > b, a, b), index=df1.index, columns=df1.columns) print (df)    0  1 0  8  9 1  5  8 2  6  9

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