## Divide Numpy array by Scalar where Array-Element is below a certain value

divide array by scalar python

numpy divide matrix by vector

numpy divide by zero

element wise division of two numpy arrays

element wise division python list

numpy divide each column by it's sum

np.divide vs /

I have a numpy array like

[[1, 2, 3], [4, 5, 6], [7, 8, 9]]

Now I want divide every Element which is less than 5 by 2. The Result should be

[[0.5, 1, 1.5], [2, 5, 6], [7, 8, 9]]

How can I do that?

Use `numpy.where`

:

np.where(arr<5, arr/2, arr)

Output:

array([[0.5, 1. , 1.5], [2. , 5. , 6. ], [7. , 8. , 9. ]])

**numpy.divide — NumPy v1.19 Manual,** Returns a true division of the inputs, element-wise. Instead of the Elsewhere, the out array will retain its original value. outndarray or scalar. NumPy Array Object Exercises, Practice and Solution: Write a NumPy program to divide each row by a vector element.

You can do this by logical indexing:

>>> import numpy as np >>> x = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]], dtype = float) >>> x[x<5] = x[x<5]/2 >>> x array([[0.5, 1. , 1.5], [2. , 5. , 6. ], [7. , 8. , 9. ]])

**numpy.divide() in Python,** numpy.divide(arr1, arr2, out = None, where = True, casting Array element from first array is divided by elements from second where : [array_like, optional]True value means to calculate the anything incorrect by clicking on the "Improve Article" button below. @geeksforgeeks, Some rights reserved. Iterating over list of tuples. As is typical, you can do this a number of ways. This function returns an array of unique elements in the input array. So I have created a NumPy array: import numpy as np. If I have two arrays as shown below: a = numpy. When an array is no longer needed in the program, it can be … Online Read. array([[1,2,3.

Here's what you could do

x[x<5] = x[x<5]/2

**numpy.true_divide() in Python,** Array element from first array is divided by the elements from second that position, False value means to leave the value in the output alone. Return : If inputs are scalar then scalar; otherwise array with arr1 / arr2(element- wise) i.e. find anything incorrect by clicking on the "Improve Article" button below. Equivalent to x1 / x2 in terms of array-broadcasting. Behavior on division by zero can be changed using seterr. In Python 2, when both x1 and x2 are of an integer type, divide will behave like floor_divide. In Python 3, it behaves like true_divide. Examples

numpy.where

For example, if your array is named `np_array`

numpy.where(np_array >=5, np_array, np_array/2)

See the documentation here

**numpy.divide — NumPy v1.13 Manual,** This is documentation for an old release of NumPy (version 1.13.0). Divide arguments element-wise. If not provided or None, a freshly-allocated array is returned. A tuple Values of True indicate to calculate the ufunc at that position, values of False indicate to leave the value in the output alone. y : ndarray or scalar. Fill the array with a scalar value. flatten ([order]) Return a copy of the array collapsed into one dimension. getfield (dtype[, offset]) Returns a field of the given array as a certain type. item (*args) Copy an element of an array to a standard Python scalar and return it. itemset (*args) Insert scalar into an array (scalar is cast to array

**Python Numpy – Divide all the elements of array by a constant,** Pass array and constant as operands to the division operator as shown below. b = a / c. where a is input array and c is a constant. b is the� RuntimeWarning: invalid value encountered in true_divide On the other hand, 1 / my_array. If 1 divided by 0, you will also get a warning: [ inf 1. 0.5 0.33333333 0.25 0.2 0.16666667 0.14285714 0.125 0.11111111 0.1 ] RuntimeWarning: divide by zero encountered in true_divide In this case, it will show infinity instead of nan.

**NumPy: Divide each row by a vector element,** NumPy Array Object Exercises, Practice and Solution: Write a NumPy program to divide each row by a vector element. Python: Use Get() to Retrieve a Value in a Dictionary >>> number_dict This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License. (An array scalar is an instance of the types/classes float32, float64, etc., whereas a 0-dimensional array is an ndarray instance containing precisely one array scalar.) If axis is an integer, then the operation is done over the given axis (for each 1-D subarray that can be created along the given axis).

**NumPy Cheat Sheet — Python for Data Science – Dataquest,** Includes importing, exporting, filtering, sorting, scalar and vector maths and more. np.arange(0,10,3) | Array of values from 0 to less than 10 with step 3 (eg [0,3,6, 9] ) np.full((2 arr.sort(axis=0) | Sorts specific axis of arr np.divide(arr,4) | Divide each array element by 4 (returns np.nan for division by zero) (An array scalar is an instance of the types/classes float32, float64, etc., whereas a 0-dimensional array is an ndarray instance containing precisely one array scalar.) If axis is an integer, then the operation is done over the given axis (for each 1-D subarray that can be created along the given axis).