Built-in Functions

Published May 25, 2022

NumPy has many built-in functions for mathematical operations and array manipulation. Selected ones are listed below.

.amax(): Returns the maximum of a given array or maximum along an axis.
.amin(): Returns the minimum of an array or minimum along an axis.
.append(): Appends values to the end of an array.
.corrcoef(): Computes the Pearson correlation coefficient of two specified arrays.
.det(): Computes the determinant of a square matrix.
.dot(): Computes the dot product of two arrays.
.inv(): Inverts a given matrix and returns the inverted matrix.
.linspace(): Returns an array of evenly-spaced numbers over a given interval.
.log(): Returns an element-wise natural logarithm for an array.
.mean(): Computes the arithmetic mean along the specified axis.
.median(): Returns the median of the elements in a given array.
.norm(): Computes the norm of a matrix, either across the entire array or along a specified axis.
.percentile(): Calculates the Xth percentile of the given data.
.reshape(): Rearranges the data of an ndarray into a new shape.
.std(): Calculates the standard deviation of given data along a specified axis.
.sum(): Sums the elements of an array over a given axis.
.svd(): Performs the Singular Value Decomposition (SVD) on a matrix, breaking it down into singular vectors and singular values.
.transpose(): Reverses or permutes the axes of an ndarray.
.var(): Computes the variance of the array elements.