Descriptive statistics in Python

Summarizing a sample with NumPy's stats functions.

import numpy as np

samples = np.array([12, 15, 15, 18, 21, 24, 24, 30])

average = np.mean(samples)
middle = np.median(samples)
spread = np.std(samples)
p90 = np.percentile(samples, 90)

counts, edges = np.histogram(samples, bins=4)
unique, freq = np.unique(samples, return_counts=True)

How it works

1. mean, median, and std describe the center and spread.
2. percentile finds the 90th percentile.
3. histogram and unique count distributions.

Keywords and builtins used here

• as

The run, in numbers

Lines

11

Characters to type

287

Tokens

90

Three-star pace

105 tpm

At the three-star pace of 105 tokens a minute, this run takes about 51 seconds.

Type this snippet

Step 3 of 4 in Math & shapes, step 5 of 22 in NumPy.

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Descriptive statistics in other languages

• R