Randomly select rows from DataFrame Pandas

Question

Okay this is somewhat tricky. I have a DataFrame of people and I want to randomly select 27% of them. I want to create a new Boolean column in that DataFrame that shows if that person was randomly selected.

Anyone have any idea how to do this?

Answer 1

The in-built sample function provides a frac argument to give the fraction contained in the sample.

If your DataFrame of people is people_df :

percent_sampled = 27
sample_df = people_df.sample(frac = percent_sampled/100)

people_df['is_selected'] = people_df.index.isin(sample_df.index)

Answer 2

n = len(df) 
idx = np.arange(n)
idx = random.shuffle(idx)
*selected_idx = idx[:int(0.27*n)] 
selected_df = df[df.index.isin(selected_idx)]

Answer 3

Defining a dataframe with 100 random numbers in column 0:

import random
import pandas as pd
import numpy as np
a = pd.DataFrame(range(100))
random.shuffle(a[0])

Using random.sample to choose 27 random numbers from the list, WITHOUT repetition: (replace 27 with 0.27*int(len(a[0]) if you want to define this as percentage)

choices = random.sample(list(a[0]),27)

Using np.where to assign boolean values to new column in dataframe:

a['Bool'] = np.where(a[0].isin(choices),True,False)