In this article we will learn about checking a specified row is in NumPy array or not. If the given list is present in a NumPy array as a row then the output is True else False. The list is present in a NumPy array means any row of that numpy array matches with the given list with all elements in given order. This can be done by using simple approach as checking for each row with the given list but this can be easily understood and implemented by using inbuilt library functions numpy.array.tolist().
Syntax: ndarray.tolist()
Parameters: none
Returns: The possibly nested list of array elements.
Examples :
Arr = [[1,2,3,4,5], [6,7,8,9,10], [11,12,13,14,15], [16,17,18,19,20]]
and the given lists are as follows :
lst = [1,2,3,4,5] True, as it matches with the row 0.
[16,17,20,19,18] False, as it doesn’t match with any row.
[3,2,5,-4,5] False, as it doesn’t match with any row.
[11,12,13,14,15] True, as it matches with the row 2.
Below is the implementation with an example :
Python3
# importing package import numpy # create numpy array arr = numpy.array([[1, 2, 3, 4, 5], [6, 7, 8, 9, 10], [11, 12, 13, 14, 15], [16, 17, 18, 19, 20] ]) # view array print(arr) # check for some lists print([1, 2, 3, 4, 5] in arr.tolist()) print([16, 17, 20, 19, 18] in arr.tolist()) print([3, 2, 5, -4, 5] in arr.tolist()) print([11, 12, 13, 14, 15] in arr.tolist()) |
Output :
[[ 1 2 3 4 5] [ 6 7 8 9 10] [11 12 13 14 15] [16 17 18 19 20]] True False False True
