Read a small random sample from a big CSV file into a Python data frame

Question

The CSV file that I want to read does not fit into main memory. How can I read a few (~10K) random lines of it and do some simple statistics on the selected data frame?

Answer 1

Here is an algorithm that doesn't require counting the number of lines in the file beforehand, so you only need to read the file once.

Say you want m samples. First, the algorithm keeps the first m samples. When it sees the i-th sample (i > m), with probability m/i, the algorithm uses the sample to randomly replace an already selected sample.

By doing so, for any i > m, we always have a subset of m samples randomly selected from the first i samples.

See code below:

import random

n_samples = 10
samples = []

for i, line in enumerate(f):
    if i < n_samples:
        samples.append(line)
    elif random.random() < n_samples * 1. / (i+1):
            samples[random.randint(0, n_samples-1)] = line