ptp(a[, axis, out, keepdims])
Range of values (maximum - minimum) along an axis.
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.
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.
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.
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.
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