Around:
numpy.all (array, axis = no, out = no, keepdims = class numpy._globals._NoValue at 0x40ba726c): checks whether all array elements along the specified axis are True.
Parameters:
array: [array_like] Input array or object whose elements, we need to test. axis: [int or tuple of ints, optional] Axis along which array elements are evaluated. The default (axis = None) is to perform a logical AND over all the dimensions of the input array. Axis may be negative, in which case it counts from the last to the first axis. out: [ndarray, optional] Output array with same dimensions as Input array, placed with result keepdmis: [boolean, optional] If this is set to True, the axes which are reduced are left in the result as dimensions with size one. With this option, the result will broadcast correctly against the input array. If the default value is passed, then keepdims will not be passed through to the all method of subclasses of ndarray, however any nondefault value will be. If the subclasses sum method does not implement keepdims any exceptions will be raised.
Return:
A new Boolean array as per 'out' parameter
Code 1:
# Python program illustrating
# numpy.all () method
import
numpy as geek
# Axis = NULL
# True False
# True true
# True: False = False
print
(
" Bool Value with axis = NONE : "
, geek.
all
([[
True
,
False
], [
True
,
True
]]))
# Axis = 0
# True False
# True True
# True: False
print
(
"Bool Value with axis = 0 :"
, geek.
all
([[
True
,
False
], [
True
,
True
]], axis
=
0
))
print
(
"Bool:"
, geek.
all
([

1
,
4
,
5
]))
# Not a number (NaN), positive infinity and negative infinity
# evaluate to True because they are not zero.
print
(
"Bool:"
, geek.
all ([
1.0
, geek.nan]))
print
(
"Bool Value:"
, geek.
all
([[
0
,
0
], [
0
,
0
]]))
Output:
Bool Value with axis = NONE: False Bool Value with axis = 0: [True False] Bool: True Bool: True Bool Value: False
Code 2:

Output:
Bool Value : [False False] Bool Value: [False False] VisibleDeprecationWarning: using a boolean instead of an integer will result in an error in the future return umr_all (a, axis, dtype, out, keepdims)
Links:
https:// docs.s cipy.org/doc/numpydev/reference/generated/numpy.all.html#numpy.all
Notes:
These codes are not will work for online ID. Please run them on your systems to see how they work.
,
This article is provided by Mohit Gupta_OMG
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