This is documentation for an old release of NumPy (version 1.8.0). Read this page Search for this page in the documentation of the latest stable release (version > 1.17).
Statistics
Order statistics
amin(a[, axis, out, keepdims]) |
Return the minimum of an array or minimum along an axis. |
amax(a[, axis, out, keepdims]) |
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 |
ptp(a[, axis, out]) |
Range of values (maximum - minimum) along an axis. |
percentile(a, q[, axis, out, overwrite_input]) |
Compute the qth percentile of the data along the specified axis. |
Averages and variances
median(a[, axis, out, overwrite_input]) |
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. |
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 |
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 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, minlength]) |
Count number of occurrences of each value in array of non-negative ints. |
digitize(x, bins[, right]) |
Return the indices of the bins to which each value in input array belongs. |