Multiply all rows in a Pandas DataFrame by dictionary

Question

Say I have a DataFrame call it one like this:

non_multiply_col col_1 col_2
A Name           1     3

and a dict like this call it two:

{'col_1': 4, 'col_2': 5}

is there a way that I can multiply all rows of one by the values in two for the columns as defined by two's keys so the result would be:

non_multiply_col col_1 col_2
A Name           4     15

I tried using multiply, but I'm not really looking to join on anything specific. Maybe I'm not understanding how to use multiply correctly.

Thanks

Answer 1

mul/multiply works fine if the dictionary is converted to a Series:

d = {'col_1': 4, 'col_2': 5}

df.mul(pd.Series(d), axis=1)

#   col_1   col_2
#0      4      15

In case you have more columns in the data frame than the dictionary:

df = pd.DataFrame([{'col_1': 1, 'col_2': 3, 'col_3': 4}])   
d = {'col_1': 4, 'col_2': 5}

cols_to_update = d.keys()  # you might need cols_to_update = list(d.keys()) in python 3
# multiply the selected columns and update
df[cols_to_update] = df[cols_to_update].mul(pd.Series(d), axis=1)[cols_to_update]
df

    col_1   col_2   col_3
#0      4      15       4

I happen to find this work as well, not sure if there is any caveat about this usage:

df[d.keys()] *= pd.Series(d)