Assign A New Column In Pandas In A Similar Way As In Pyspark

I have the following dataframe: df = pd.DataFrame([['A', 1],['B', 2],['C', 3]], columns=['index', 'result']) I would like to create a new column, for example multiply the column

Solution 1:

Use DataFrame.assign:

df = df.assign(result_multiplied = df['result']*2)

Or if column result is processing in code before is necessary lambda function for processing counted values in column result:

df = df.assign(result_multiplied = lambda x: x['result']*2)

Sample for see difference column result_multiplied is count by multiple original df['result'], for result_multiplied1 is used multiplied column after mul(2):

df = df.mul(2).assign(result_multiplied = df['result']*2,
                      result_multiplied1 = lambda x: x['result']*2)
print (df)
  index  result  result_multiplied  result_multiplied1
0    AA       2                  2                   4
1    BB       4                  4                   8
2    CC       6                  6                  12