python - ValueError In Pandas -


i have data frame 15 columns suppose out of want 6. performing aggregate , group throwing error. 

def my_compute_function(my_input):      df = pd.dataframe(my_input)     df2 = df[(df['d'] == "validated")]     df2[['a','e','f']] = df2[['a','e','f']].apply(pd.to_numeric)      df3=df2[['a','b','c','d','e','f']].groupby(['b','c','d']).agg({'a':      'max','e': 'max','f': 'max'}).reset_index()      return df3

so want 6 columns a,b,c,d,e,f.
when adding line 

df2[['a','e','f']]=df2[['a','e','f']].apply(pd.to_numeric)

it throwing error valueerror: can not infer schema empty dataset.

for me working perfectly, .copy necessary:

df = pd.dataframe({ 'd':['validated','validated','a'],  'e':['4','8','8'],  'a':['4','5','8'], 'f':['4','9','8'], 'b':['a','a','r'], 'c':['b','b','b']})  df2=df[(df['d'] == "validated")].copy() print (df2)     b  c          d  e  f 0  4   b  validated  4  4 1  5   b  validated  8  9  #for replace ',' '.'  df2[['a','e','f']]=df2[['a','e','f']].replace(',','.', regex=true).apply(pd.to_numeric) df3=df2.groupby(['b','c','d']).agg({'a':'max','e': 'max','f': 'max'}).reset_index() print (df3)    b  c          d   f  e 0   b  validated  5  9  8

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