# 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, interpolation, …]) Computes the q-th percentile of the data along the specified axis. `quantile`(a, q[, axis, out, interpolation, …]) 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.