Statistics — NumPy v2.2 Manual (original) (raw)
Order statistics#
| ptp(a[, axis, out, keepdims]) | Range of values (maximum - minimum) along an axis. |
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| percentile(a, q[, axis, out, ...]) | Compute the q-th 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. |
| 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. |
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| average(a[, axis, weights, returned, keepdims]) | Compute the weighted average along the specified axis. |
| mean(a[, axis, dtype, out, keepdims, where]) | 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, where]) | Compute the arithmetic mean along the specified axis, ignoring NaNs. |
| nanstd(a[, axis, dtype, out, ddof, ...]) | Compute the standard deviation along the specified axis, while ignoring NaNs. |
| nanvar(a[, axis, dtype, out, ddof, ...]) | Compute the variance along the specified axis, while ignoring NaNs. |
Correlating#
| corrcoef(x[, y, rowvar, bias, ddof, dtype]) | Return Pearson product-moment correlation coefficients. |
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| 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, density, weights]) | Compute the histogram of a dataset. |
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| histogram2d(x, y[, bins, range, density, ...]) | Compute the bi-dimensional histogram of two data samples. |
| histogramdd(sample[, bins, range, density, ...]) | 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. |