Return multiple columns from pandas apply()

Question

I have a pandas DataFrame, df_test. It contains a column \'size\' which represents size in bytes. I\'ve calculated KB, MB, and GB using the following code:

Answer 1

Really cool answers! Thanks Jesse and jaumebonet! Just some observation in regards to:

• zip(* ...
• ... result_type="expand")

Although expand is kind of more elegant (pandifyed), zip is at least **2x faster. On this simple example bellow, I got 4x faster.

import pandas as pd

dat = [ [i, 10*i] for i in range(1000)]

df = pd.DataFrame(dat, columns = ["a","b"])

def add_and_sub(row):
    add = row["a"] + row["b"]
    sub = row["a"] - row["b"]
    return add, sub

df[["add", "sub"]] = df.apply(add_and_sub, axis=1, result_type="expand")
# versus
df["add"], df["sub"] = zip(*df.apply(add_and_sub, axis=1))