I want to use the apply function that: - Takes 2 columns as inputs - Outputs two new columns based on a function.
An example is with this add_multiply function.
#function with 2 column inputs and 2 outputs
def add_multiply (a,b):
return (a+b, a*b )
#example dataframe
df = pd.DataFrame({'col1': [1, 2], 'col2': [3, 4]})
#this doesn't work
df[['add', 'multiply']] = df.apply(lambda x: add_multiply(x['col1'], x['col2']), axis=1)
ideal result:
col1 col2 add multiply
1 3 4 3
2 4 6 8
Select each column of DataFrame df through the syntax df["column_name"] and add them together to get a pandas Series containing the sum of each row. Create a new column in the DataFrame through the syntax df["new_column"] and set it equal to this Series to add it to the DataFrame.
In pandas you can add/append a new column to the existing DataFrame using DataFrame. insert() method, this method updates the existing DataFrame with a new column. DataFrame. assign() is also used to insert a new column however, this method returns a new Dataframe after adding a new column.
You can add result_type='expand'
in the apply
:
‘expand’ : list-like results will be turned into columns.
df[['add', 'multiply']]=df.apply(lambda x: add_multiply(x['col1'], x['col2']),axis=1,
result_type='expand')
Or call a dataframe constructor:
df[['add', 'multiply']]=pd.DataFrame(df.apply(lambda x: add_multiply(x['col1'],
x['col2']), axis=1).tolist())
col1 col2 add multiply
0 1 3 4 3
1 2 4 6 8
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