Categorical association in Python

A contingency table, a chi-square test, and Fisher's exact for small counts.

import numpy as np
from scipy import stats

table = np.array([[30, 10], [18, 22]])

result = stats.chi2_contingency(table)
print(round(result.statistic, 3), f"{result.pvalue:.5f}", result.dof)
print(result.expected_freq.round(1))

small = np.array([[8, 2], [1, 5]])
odds, p = stats.fisher_exact(small)
print(round(odds, 3), round(p, 5))

How it works

1. chi2_contingency returns the statistic, p, dof and expected counts.
2. The expected table is what the test compares against.
3. fisher_exact is right when any expected count is tiny.

Keywords and builtins used here

• as
• print
• round

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Step 3 of 4 in Hypothesis tests, step 6 of 23 in Scientific computing with SciPy.

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