How to filter an array using NUmpy?

Question

ICSM Computer · Answer

To filter (select) values from a NumPy array, you use
boolean indexing — create a boolean condition and apply it to the array.
Basic Example
import numpy as np
arr = np.array([1, 2, 3, 4, 5, 6])
filtered = arr[arr andgt; 3]
print(filtered)
Output
[4 5 6]
Filter Using Multiple Conditions
Use and (AND), | (OR), and ~ (NOT).
Parentheses are required.
arr = np.array([10, 20, 30, 40, 50])
filtered = arr[(arr andgt;= 20) and (arr andlt;= 40)]
print(filtered)
Output:
[20 30 40]
Filter with Another Array of Booleans
arr = np.array([5, 10, 15, 20])
mask = np.array([True, False, True, False])
filtered = arr[mask]
print(filtered)
Output:
[ 5 15 ]
Filter Strings
names = np.array(["Bob", "Alice", "John", "Anna"])
filtered = names[names == "Anna"]
print(filtered)
To 
filter strings containing a substring:
filtered = names[np.char.find(names, "n") andgt;= 0]   # find returns -1 if not found
print(filtered)
Filter 2D Arrays
arr = np.array([[1, 2, 3],
                [4, 5, 6],
                [7, 8, 9]])
filtered = arr[arr andgt; 5]
print(filtered)
Output:
[6 7 8 9]
Replace filtered values instead of selecting
arr = np.array([10, 20, 30, 40])
arr[arr andgt; 25] = 0
print(arr)
Output:
[10 20  0  0]
Get indexes of matches
arr = np.array([3, 7, 2, 9, 7])
idx = np.where(arr == 7)
print(idx)
Result:
(array([1, 4], dtype=int64),)
Summary
Goal
Code
Select values
arr[arr andgt; 3]
Select with conditions
arr[(arr andgt;= 10) and (arr andlt;= 20)]
Boolean mask
arr[mask]
Replace selected
arr[arr andgt; 10] = 0
Get indexes
np.where(arr == x)
and

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How to filter an array using NUmpy?

ICSM Computer

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1 Answers

Basic Example

Filter Using Multiple Conditions

Filter with Another Array of Booleans

Filter Strings

Filter 2D Arrays

Replace filtered values instead of selecting

Get indexes of matches

Summary

Liked By

Goal	Code
Select values	`arr[arr > 3]`
Select with conditions	`arr[(arr >= 10) & (arr <= 20)]`
Boolean mask	`arr[mask]`
Replace selected	`arr[arr > 10] = 0`
Get indexes	`np.where(arr == x)`