Make Most Columns None If Condition in Python

Question

I have a pandas dataframe with one boolean column. I want to set most of the columns to "None" if the boolean is False. I don't want to change the object that I am iterating over, but what is an elegant way to do this?

question from:https://stackoverflow.com/questions/65921003/make-most-columns-none-if-condition-in-python

Answer 1

You can use the apply function to iterate over the rows:

import pandas as pd
import random

df = pd.DataFrame(
   {"a": list(range(10)), 
    "b": list(range(10)), 
    "c": [random.choice((True, False)) for _ in range(10)]
})

def mask(row):
   if row["c"]:
      row["a"] = None
   return row

df.apply(mask, axis=1)

Yields the following result:

   a    b      c
0  0  0.0  False
1  1  1.0  False
2  2  NaN   True
3  3  3.0  False
4  4  NaN   True
5  5  NaN   True
6  6  NaN   True
7  7  NaN   True
8  8  NaN   True
9  9  NaN   True

Meanwhile the original dataframe is unchanged.

This is certainly not the fastest method, but its very flexible. If speed is an important factor you might also consider the where method.

cols_to_replace = ["a", "b"]
new_col_names = ["new_" + col for col in cols_to_replace]
df[new_col_names] = df[cols_to_replace].where(df["c"])