# Statistics¶

## Order statistics¶

 `amin`(a[, axis, out, keepdims, initial]) Return the minimum of an array or minimum along an axis. `amax`(a[, axis, out, keepdims, initial]) 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 qth 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…versionadded:: 1.15.0. `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.