## Python - How to extract elements from an array based on an array of indices?

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Let's say I have a list of elements `X`

and one of indices `Y`

.

X = [1, 2, 3, 4, 5, 6, 7] Y = [0, 3, 4]

Is there a function in Python that allows one to extract elements from `X`

based on the indices provided in `Y`

? After execution, `X`

would be:

X = [1, 4, 5]

X = [X[index] for index in Y]

This is a **list comprehension**; you can look up that topic to learn more.

**numpy.take,** numpy. take (a, indices, axis=None, out=None, mode='raise')[source]¶. Take elements from an array along an axis. When axis is not None, this function does the indicesarray_like (Nj…) The indices of the values to extract. Python. ndarray [index] 1. ndarray[index] It will return the element at given index only. Let’s use this to select an element at index 2 from Numpy Array we created above i.e. npArray, C++. # Select an element at index 2 (Index starts from 0) elem = npArray [2] print ('Element at 2nd index : ' , elem) 1.

The list comprehension provided by @Prune is the way to go in pure python. If you don't mind `numpy`

, it might be easier just use their indexing scheme:

import numpy as np >>> np.array(X)[Y] array([1, 4, 5])

**Fancy Indexing,** Fancy indexing is conceptually simple: it means passing an array of indices to access multiple array elements at once. For example, consider the following array:. Python numpy.where () is an inbuilt function that returns the indices of elements in an input array where the given condition is satisfied. Python’s numpy module provides a function to select elements based on condition. If you want to find the index in Numpy array, then you can use the numpy.where () function.

You can use `list.__getitem__`

with `map`

:

X = [1, 2, 3, 4, 5, 6, 7] Y = [0, 3, 4] res = list(map(X.__getitem__, Y)) # [1, 4, 5]

Or, if you are happy to use a 3rd party library, you can use NumPy:

import numpy as np X = np.array([1, 2, 3, 4, 5, 6, 7]) res = X[Y] # array([1, 4, 5])

**Python,** Python | Replace elements in second list with index of same element in first list · Python | Add list elements with a multi-list based on index · Python | Sorting list of Similar to arithmetic operations when we apply any comparison operator to Numpy Array, then it will be applied to each element in the array and a new bool Numpy Array will be created with values True or False. Suppose we have a Numpy Array i.e. #Create an Numpy Array containing elements from 5 to 30 but at equal interval of 2 arr = np.arange (5

**numpy.extract() in Python,** Array elements are extracted from the Indices having True value. Returns : Array elements that satisfy the condition. Using numpy.where (), elements of the NumPy array ndarray that satisfy the conditions can be replaced or performed specified processing. Here, the following contents will be described. Get the indices of the elements that satisfy the condition. If you want to extract or delete elements, rows and columns that satisfy the conditions, see the

**Python Numpy : Select an element or sub array by index from a ,** It will return a sub array from original array with elements from index first to last – 1. Let's use this to select different sub arrays from original array : Input array. User apply conditions on input_array elements condition : [array_like]Condition on the basis of which user extract elements. Applying condition on input_array, if we print condition, it will return an array filled with either True or False. Array elements are extracted from the Indices having True value.

**np.take - Numpy and Scipy,** Matlab post There are times where you have a lot of data in a vector or array and you want to extract a portion of the data for some analysis. In this article we will discuss how to select elements from a 2D Numpy Array . Elements to select can be a an element only or single/multiple rows & columns or an another sub 2D array. First of all, let’s import numpy module i.e. Now let’s create a 2d Numpy Array by passing a list of lists to numpy.array () i.e.