Python Data Analysis Cookbook

NumPy

The following creates a NumPy array with evenly spaced values within a specified range:

numpy.arange([start,] stop[, step,], dtype=None)

The following argument returns the indices that would sort the input array:

numpy.argsort(a, axis=-1, kind='quicksort', order=None)

The following creates a NumPy array from an array-like sequence, such as a Python list:

numpy.array(object, dtype=None, copy=True, order=None, subok=False, ndmin=0)

The following argument calculates the dot product of two arrays:

numpy.dot(a, b, out=None)

The following argument returns the identity matrix:

numpy.eye(N, M=None, k=0, dtype=<type 'float'>)

The following argument loads NumPy arrays or pickled objects from .npy, .npz or pickles. A memory-mapped array is stored in the filesystem ...