Creating multiple pandas columns from function returning dict

I have a function that returns a dict object and I would like to take advantage of pandas/numpy's ability to perform columnwise operations/vectorization for this function across every row of a dataframe. The inputs for the function are specified in the dataframe and I want the outputs of the function to become new columns on the existing dataframe. Below is an example.

def func(a, b, c):      return {          "a_calc": a * 2,           "b_calc": b * 3,           "c_calc": c * 4      }  

df = pd.DataFrame([{"a":1, "b":2, "c": 3}, {"a": 4, "b": 5, "c": 6}])     a  b  c  0  1  2  3  1  4  5  6  

Desired Output:

   a  b  c  a_calc  b_calc  c_calc  0  1  2  3       2       6      12  1  4  5  6       8      15      24  

I was reading this answer and it got most of the way there but I couldn't quite figure out how to do it for when the function returns a dict object with the desired column names as the keys within the dict.

https://stackoverflow.com/questions/66978570/creating-multiple-pandas-columns-from-function-returning-dict April 07, 2021 at 09:53AM