Statistics

Order statistics

quantile(a, q[, axis, out, overwrite_input, ...])	Compute the q-th quantile of the data along the specified axis.
percentile(a, q[, axis, out, ...])	Compute the q-th percentile of the data along the specified axis.
nanquantile(a, q[, axis, out, ...])	Compute the q-th quantile of the data along the specified axis, while ignoring nan values.
nanpercentile(a, q[, axis, out, ...])	Compute the q-th percentile of the data along the specified axis, while ignoring nan values.

Averages and variances

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.
nanmean(a[, axis, dtype, out, keepdims, where])	Compute the arithmetic mean along the specified axis, ignoring NaNs.
var(a[, axis, dtype, out, ddof, keepdims, where])	Compute the variance along the specified axis.
median(a[, axis, out, overwrite_input, keepdims])	Compute the median along the specified axis.
nanmedian(a[, axis, out, overwrite_input, ...])	Compute the median along the specified axis, while ignoring NaNs

Correlating

cov(m[, y, rowvar, bias, ddof, fweights, ...])

Estimate a covariance matrix, given data and weights.

Histograms

bincount(x[, weights, minlength])	Count number of occurrences of each value in array of non-negative ints.
histogram(x[, bins, range, weights, density])	Compute the histogram of a dataset.
digitize(x, bins[, right])	Return the indices of the bins to which each value in input array belongs.