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numpy filtering

Innocent Iguana answered on September 4, 2022 Popularity 8/10 Helpfulness 5/10

answer numpy filtering

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numpy filtering

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# Way 1 : Filtering using indexing

some_array[some_array[:, 1 ] % 2 == 0 ] 

# Way 2 : Filtering using 'where' keyword

row_ind, column_ind = np.where(some_array[:, 1] % 2 == 0)
np.where(some_array[:, 1] % 2 == 0, "", some_array) # Replacing values

Popularity 8/10 Helpfulness 5/10 Language python

Source: Grepper

Tags: filtering numpy python

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Contributed on Nov 16 2023

Innocent Iguana

0 Answers Avg Quality 2/10

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import numpy as np

arr = np.array([41, 42, 43, 44])
x = [True, False, True, False]
# return items where true matches
arr = arr[x]
print(arr)
# output [41 43]

# Create an empty list
filter_arr = []

# go through each element in arr
for element in arr:
    # if the element is higher than 42, set the value to True, otherwise False:
    if element > 42:
        filter_arr.append(True)
    else:
        filter_arr.append(False)

arr = arr[filter_arr]

print(filter_arr)
# output [False, True]

print(arr)
# output [43]

Popularity 9/10 Helpfulness 1/10 Language python

Source: codefreelance.net

Tags: filter fi

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Contributed on Sep 04 2022

Jerome Scott

0 Answers Avg Quality 2/10

numpy filtering

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