This is documentation for an old release of NumPy (version 1.17). Read this page Search for this page in the documentation of the latest stable release (version 2.2).

Statistics

Order statistics

amin(a[, axis, out, keepdims, initial, where])	Return the minimum of an array or minimum along an axis.
amax(a[, axis, out, keepdims, initial, where])	Return the maximum of an array or maximum along an axis.
nanmin(a[, axis, out, keepdims])	Return minimum of an array or minimum along an axis, ignoring any NaNs.
nanmax(a[, axis, out, keepdims])	Return the maximum of an array or maximum along an axis, ignoring any NaNs.
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])	Compute the weighted average along the specified axis.
mean(a[, axis, dtype, out, keepdims])	Compute the arithmetic mean along the specified axis.
std(a[, axis, dtype, out, ddof, keepdims])	Compute the standard deviation along the specified axis.
var(a[, axis, dtype, out, ddof, keepdims])	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])	Compute the arithmetic mean along the specified axis, ignoring NaNs.
nanstd(a[, axis, dtype, out, ddof, keepdims])	Compute the standard deviation along the specified axis, while ignoring NaNs.
nanvar(a[, axis, dtype, out, ddof, keepdims])	Compute the variance along the specified axis, while ignoring NaNs.

Correlating

corrcoef(x[, y, rowvar, bias, ddof])	Return Pearson product-moment correlation coefficients.
correlate(a, v[, mode])	Cross-correlation of two 1-dimensional sequences.
cov(m[, y, rowvar, bias, ddof, fweights, …])	Estimate a covariance matrix, given data and weights.

Histograms

histogram(a[, bins, range, normed, weights, …])	Compute the histogram of a set of data.
histogram2d(x, y[, bins, range, normed, …])	Compute the bi-dimensional histogram of two data samples.
histogramdd(sample[, bins, range, normed, …])	Compute the multidimensional histogram of some data.
bincount(x[, weights, minlength])	Count number of occurrences of each value in array of non-negative ints.
histogram_bin_edges(a[, bins, range, weights])	Function to calculate only the edges of the bins used by the histogram function.
digitize(x, bins[, right])	Return the indices of the bins to which each value in input array belongs.