Statistics

Order statistics

amin(a[, axis, out, keepdims])

Returns the minimum of an array or the minimum along an axis.

amax(a[, axis, out, keepdims])

Returns the maximum of an array or the maximum along an axis.

nanmin(a[, axis, out, keepdims])

Returns the minimum of an array along an axis ignoring NaN.

nanmax(a[, axis, out, keepdims])

Returns the maximum of an array along an axis ignoring NaN.

ptp(a[, axis, out, keepdims])

Returns the range of values (maximum - minimum) along an axis.

percentile(a, q[, axis, out, …])

Computes the q-th percentile of the data along the specified axis.

quantile(a, q[, axis, out, overwrite_input, …])

Computes the q-th quantile of the data along the specified axis.

Averages and variances

median(a[, axis, out, overwrite_input, keepdims])

Compute the median along the specified axis.

average(a[, axis, weights, returned])

Returns the weighted average along an axis.

mean(a[, axis, dtype, out, keepdims])

Returns the arithmetic mean along an axis.

std(a[, axis, dtype, out, ddof, keepdims])

Returns the standard deviation along an axis.

var(a[, axis, dtype, out, ddof, keepdims])

Returns the variance along an axis.

nanmedian(a[, axis, out, overwrite_input, …])

Compute the median along the specified axis, while ignoring NaNs.

nanmean(a[, axis, dtype, out, keepdims])

Returns the arithmetic mean along an axis ignoring NaN values.

nanstd(a[, axis, dtype, out, ddof, keepdims])

Returns the standard deviation along an axis ignoring NaN values.

nanvar(a[, axis, dtype, out, ddof, keepdims])

Returns the variance along an axis ignoring NaN values.

Correlations

corrcoef(a[, y, rowvar, bias, ddof])

Returns the Pearson product-moment correlation coefficients of an array.

correlate(a, v[, mode])

Returns the cross-correlation of two 1-dimensional sequences.

cov(a[, y, rowvar, bias, ddof])

Returns the covariance matrix of an array.

Histograms

histogram(x[, bins, range, weights, density])

Computes the histogram of a set of data.

histogram2d(x, y[, bins, range, weights, …])

Compute the bi-dimensional histogram of two data samples.

histogramdd(sample[, bins, range, weights, …])

Compute the multidimensional histogram of some data.

bincount(x[, weights, minlength])

Count number of occurrences of each value in array of non-negative ints.

digitize(x, bins[, right])

Finds the indices of the bins to which each value in input array belongs.