Cluster Sampling in Pandas (With Examples)


Researchers often take samples from a population and use the data from the sample to draw conclusions about the population as a whole.

One commonly used sampling method is cluster sampling, in which a population is split into clusters and all members of some clusters are chosen to be included in the sample.

This tutorial explains how to perform cluster sampling on a pandas DataFrame in Python.

Example: Cluster Sampling in Pandas

Suppose a company that gives city tours wants to survey its customers. Out of ten tours they give one day, they randomly select four tours and ask every customer to rate their experience on a scale of 1 to 10.

The following code shows how to create a pandas DataFrame to work with:

import pandas as pd
import numpy as np

#make this example reproducible
np.random.seed(0)

#create DataFrame
df = pd.DataFrame({'tour': np.repeat(np.arange(1,11), 20),
                   'experience': np.random.normal(loc=7, scale=1, size=200)})

#view first six rows of DataFrame
df.head()

  tour experience
1    1   6.373546
2    1   7.183643
3    1   6.164371
4    1   8.595281
5    1   7.329508
6    1   6.179532

And the following code shows how obtain a sample of customers by randomly selecting four tours and including every member in those tours in the sample:

#randomly choose 4 tour groups out of the 10
clusters = np.random.choice(np.arange(1,11), size=4, replace=False)

#define sample as all members who belong to one of the 4 tour groups
cluster_sample = df[df['tour'].isin(clusters)]

#view first six rows of sample
cluster_sample.head()

tour	experience
40	3	5.951447
41	3	5.579982
42	3	5.293730
43	3	8.950775
44	3	6.490348 

#find how many observations came from each tour group
cluster_sample['tour'].value_counts()

10    20
6     20
5     20
3     20
Name: tour, dtype: int64

From the output we can see that:

  • 20 customers from tour group #10 were included in the sample.
  • 20 customers from tour group #6 were included in the sample.
  • 20 customers from tour group #5 were included in the sample.
  • 20 customers from tour group #3 were included in the sample.

Thus, this sample is composed of 80 total customers that came from 4 different tour groups.

Additional Resources

Understanding Different Types of Sampling Methods
Stratified Sampling in Pandas
Systematic Sampling in Pandas

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