numpy.any() in Python

numpy.count() in Python

Last Updated : 10 Oct, 2019

numpy.core.defchararray.count(arr, substring, start=0, end=None): Counts for the non-overlapping occurrence of sub-string in the specified range.

Parameters: arr : array-like or string to be searched. substring : substring to search for. start, end : [int, optional] Range to search in. Returns : An integer array with the number of non-overlapping occurrences of sub-string.

Code #1:

Python3 1==

# Python Program illustrating 
# numpy.char.count() method 

import numpy as np 

# 2D array 
arr = ['vdsdsttetteteAAAa', 'AAAAAAAaattttds', 'AAaaxxxxtt', 'AAaaXDSDdscz']

print ("arr : ", arr)

print ("Count of 'tt'", np.char.count(arr, 'tt'))
print ("Count of 'tt'", np.char.count(arr, 'tt', start = 0))
print ("Count of 'tt'", np.char.count(arr, 'tt', start = 8))

Output:

arr :  ['vdsdsttetteteAAAa', 'AAAAAAAaattttds', 'AAaaxxxxtt', 'AAaaXDSDdscz']
Count of 'tt' [2 2 1 0]
Count of 'tt' [2 2 1 0]
Count of 'tt' [1 2 1 0]

Code #2:

Python3 1==

# Python Program illustrating 
# numpy.char.count() method 
import numpy as np 

# 2D array 
arr = ['vdsdsttetteteAAAa', 'AAAAAAAaattttds', 'AAaaxxxxtt', 'AAaaXDSDdscz']

print ("arr : ", arr)

print ("Count of 'Aa'", np.char.count(arr, 'Aa'))
print ("Count of 'Aa'", np.char.count(arr, 'Aa', start = 8))

Output:

arr :  ['vdsdsttetteteAAAa', 'AAAAAAAaattttds', 'AAaaxxxxtt', 'AAaaXDSDdscz']

Count of 'Aa' [1 1 1 1]
Count of 'Aa' [1 0 0 0]

numpy.any() in Python

mohit gupta_omg :)

Improve

Article Tags :

Practice Tags :

python

Similar Reads

numpy.bincount() in Python

In an array of +ve integers, the numpy.bincount() method counts the occurrence of each element. Each bin value is the occurrence of its index. One can also set the bin size accordingly. Syntax : numpy.bincount(arr, weights = None, min_len = 0) Parameters : arr : [array_like, 1D]Input array, having p

numpy.any() in Python

The numpy.any() function tests whether any array elements along the mentioned axis evaluate to True. Syntax :Â numpy.any(a, axis = None, out = None, keepdims = class numpy._globals._NoValue at 0x40ba726c) Parameters :Â array :[array_like]Input array or object whose elements, we need to test. axis :

numpy.all() in Python

The numpy.all() function tests whether all array elements along the mentioned axis evaluate to True. Syntax: numpy.all(array, axis = None, out = None, keepdims = class numpy._globals._NoValue at 0x40ba726c) Parameters :Â array :[array_like]Input array or object whose elements, we need to test. axis

Numpy size() function | Python

numpy.size() function in Python is used to count the number of elements in a NumPy array. You can use it to get the total count of all elements, or to count elements along a specific axis, such as rows or columns in a multidimensional array. This makes it useful when quickly trying to understand the

NumPy Array in Python

NumPy (Numerical Python) is a powerful library for numerical computations in Python. It is commonly referred to multidimensional container that holds the same data type. It is the core data structure of the NumPy library and is optimized for numerical and scientific computation in Python. Table of C

Numpy count_nonzero method | Python

numpy.count_nonzero() function counts the number of non-zero values in the array arr. Syntax : numpy.count_nonzero(arr, axis=None) Parameters : arr : [array_like] The array for which to count non-zeros. axis : [int or tuple, optional] Axis or tuple of axes along which to count non-zeros. Default is

numpy.nansum() in Python

numpy.nansum()function is used when we want to compute the sum of array elements over a given axis treating Not a Numbers (NaNs) as zero. Syntax : numpy.nansum(arr, axis=None, dtype=None, out=None, keepdims='no value') Parameters : arr : [array_like] Array containing numbers whose sum is desired. If

numpy.nonzero() in Python

numpy.nonzero()function is used to Compute the indices of the elements that are non-zero. It returns a tuple of arrays, one for each dimension of arr, containing the indices of the non-zero elements in that dimension. The corresponding non-zero values in the array can be obtained with arr[nonzero(ar

numpy.fromstring() function â€“ Python

numpy.fromstring() function create a new one-dimensional array initialized from text data in a string. Syntax : numpy.fromstring(string, dtype = float, count = -1, sep = ' ') Parameters : string : [str] A string that contained the data. dtype : [data-type, optional] Data-type of the array. Default d

Python List count() method

The count() method is used to find the number of times a specific element occurs in a list. It is very useful in scenarios where we need to perform frequency analysis on the data.Let's look at a basic example of the count() method.Pythona = [1, 2, 3, 1, 2, 1, 4] c = a.count(1) print(c)Output3 Explan