pytutorial/numpy/statistics

Statistics

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The goal

There are other (more extensive) statistics packages like​

• scipy.stats​
• pingouin
• statsmodels

Questions to David Rotermund

Fisher Exact Test

The Fisher Exact Test is not part of the numpy package. But we need it in machine learning.

scipy.stats.fisher_exact(table, alternative='two-sided')

Perform a Fisher exact test on a 2x2 contingency table.

Order statistics

ptp(a[, axis, out, keepdims])	Range of values (maximum - minimum) along an axis.
percentile(a, q[, axis, out, ...])	Compute the q-th percentile of the data along the specified axis.
nanpercentile(a, q[, axis, out, ...])	Compute the qth percentile of the data along the specified axis, while ignoring nan values.
quantile(a, q[, axis, out, overwrite_input, ...])	Compute the q-th quantile of the data along the specified axis.
nanquantile(a, q[, axis, out, ...])	Compute the qth quantile of the data along the specified axis, while ignoring nan values.

Averages and variances

median(a[, axis, out, overwrite_input, keepdims])	Compute the median along the specified axis.
average(a[, axis, weights, returned, keepdims])	Compute the weighted average along the specified axis.
mean(a[, axis, dtype, out, keepdims, where])	Compute the arithmetic mean along the specified axis.
std(a[, axis, dtype, out, ddof, keepdims, where])	Compute the standard deviation along the specified axis.
var(a[, axis, dtype, out, ddof, keepdims, where])	Compute the variance along the specified axis.
nanmedian(a[, axis, out, overwrite_input, ...])	Compute the median along the specified axis, while ignoring NaNs.
nanmean(a[, axis, dtype, out, keepdims, where])	Compute the arithmetic mean along the specified axis, ignoring NaNs.
nanstd(a[, axis, dtype, out, ddof, ...])	Compute the standard deviation along the specified axis, while ignoring NaNs.
nanvar(a[, axis, dtype, out, ddof, ...])	Compute the variance along the specified axis, while ignoring NaNs.