Statistics

Extremal values

amin(a[, axis, out])	Return the minimum of an array or minimum along an axis.
amax(a[, axis, out])	Return the maximum of an array or maximum along an axis.
nanmax(a[, axis])	Return the maximum of an array or maximum along an axis ignoring any NaNs.
nanmin(a[, axis])	Return the minimum of an array or minimum along an axis ignoring any NaNs.
ptp(a[, axis, out])	Range of values (maximum - minimum) along an axis.

Averages and variances

average(a[, axis, weights, returned])	Compute the weighted average along the specified axis.
mean(a[, axis, dtype, out])	Compute the arithmetic mean along the specified axis.
median(a[, axis, out, overwrite_input])	Compute the median along the specified axis.
std(a[, axis, dtype, out, ddof])	Compute the standard deviation along the specified axis.
var(a[, axis, dtype, out, ddof])	Compute the variance along the specified axis.

Correlating

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

Histograms

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