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[英]pandas apply User defined function to grouped dataframe on multiple columns
[英]apply user defined function to pandas dataframe specific columns and add new columns to dataframe
我创建了一个名为polar(X_relative, Y_relative, Z_relative)
的 function,它采用如图所示的这 3 个 arguments,结果是新的 arguments,它们是(azimuth_angle, tilt_angle)
。 I want to apply this function to a pandas dataframe where the function arguments are certain columns in the dataframe and would like to add the output arguments of the functions (azimuth_angle, tilt_angle)
as new coulmns in the dataframe where the function is calculated for each row .
dataframe columns: X , Y, Z , X_relative , Y_relative , Z_relative
dataframe coulmns I expect after applying the function: X , Y, Z , X_relative , Y_relative , Z_relative , azimuth_angle , tilt_angle
将polar
的回归包装成一个系列:
return pd.Series([azimuth_angle, tilt_angle])
然后使用apply
:
df[['azimuth_angle', 'tilt_angle']] = df.apply(lambda x: polar(x.X_relative, x.Y_relative, x.Z_relative), axis = 1)
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