If the ndarray object is a structured array the fields of the array can be accessed by indexing the array with strings, dictionary-like. Indexing x['field-name'] returns a new view to the array, …

This page tackles common examples. For an in-depth look into indexing, refer to Indexing on ndarrays. Access specific/arbitrary rows and columns# Use Basic indexing features like Slicing …

Jun 22, 2021 · Indexing x['field-name'] returns a new view to the array, which is of the same shape as x (except when the field is a sub-array) but of data type x.dtype['field-name'] and contains …

To get the indices of unique values in a NumPy array (an array of first index positions of unique values in the array), just pass the return_index argument in np.unique() as well as your array. …

Return an array representing the indices of a grid. Compute an array where the subarrays contain index values 0, 1, … varying only along the corresponding axis. Parameters: dimensions …

Jan 31, 2021 · Index arrays¶ NumPy arrays may be indexed with other arrays (or any other sequence- like object that can be converted to an array, such as lists, with the exception of …

There are 6 general mechanisms for creating arrays: Conversion from other Python structures (i.e. lists and tuples) Intrinsic NumPy array creation functions (e.g. arange, ones, zeros, etc.) …

Indexing arrays# Arrays can be indexed using an extended Python slicing syntax, array[selection]. Similar syntax is also used for accessing fields in a structured data type.

Arrays support the iterator protocol and can be iterated over like Python lists. See the Indexing, slicing and iterating section in the Quickstart guide for basic usage and examples. The …

One can index and assign to a structured array with a multi-field index, where the index is a list of field names.