The 5 Sampling Algorithms every Data Scientist need to know

Data Science is the study of algorithms.

I grapple through with many algorithms on a day to day basis so I thought of listing some of the most common and most used algorithms one will end up using in this new DS Algorithm series.

This post is about some of the most common sampling techniques one can use while working with data.

Simple Random Sampling

Say you want to select a subset of a population in which each member of the subset has an equal probability of being chosen.

Below we select 100 sample points from a dataset.

sample_df = df.sample(100)