Lesson 11

Append, Insert, and Delete

Add values with np.append and np.insert and remove them with np.delete, on 1-D arrays and on whole rows or columns of 2-D arrays.

Intermediate25 min

Append, Insert, and Delete hero Module 23 Lesson 11

An ndarray has a fixed size. np.append, np.insert, and np.delete never change the array you pass in. Each builds and returns a new one, so assign the result to a name.

A 3 by 4 array with column 1 marked for deletion

np.append

np.append(arr, values) adds values at the end. Without an axis, a 2-D array is flattened first. With axis=0, the new rows must have the same number of columns.

python

import numpy as np

arr = np.array([11, 2, 6, 7])
longer = np.append(arr, 10)
print(longer)
print(arr)
print(np.append(arr, [20, 30]))

m = np.array([[1, 2], [3, 4]])
print(np.append(m, [[5, 6]]))
print(np.append(m, [[5, 6]], axis=0))

Output:

text

[11  2  6  7 10]
[11  2  6  7]
[11  2  6  7 20 30]
[1 2 3 4 5 6]
[[1 2]
 [3 4]
 [5 6]]

np.insert

np.insert(arr, index, value) puts the value before that index. A list of indices refers to positions in the original array. Add an axis to insert a whole row or column.

python

import numpy as np

a = np.array([10, 20, 30, 40])
print(np.insert(a, 1, 35))
print(np.insert(a, [1, 3], [15, 35]))

m = np.array([[1, 2], [3, 4]])
print(np.insert(m, 1, [9, 9], axis=0))
print(np.insert(m, 0, 0, axis=1))

Output:

text

[10 35 20 30 40]
[10 15 20 30 35 40]
[[1 2]
 [9 9]
 [3 4]]
[[0 1 2]
 [0 3 4]]

np.delete on 1-D

np.delete(arr, index) removes one position. Pass a list to remove several at once.

python

import numpy as np

arr = np.array([4, 5, 6, 7, 8, 9, 10, 11])
print(np.delete(arr, 2))
print(np.delete(arr, [1, 2, 3]))

Output:

text

[ 4  5  7  8  9 10 11]
[ 4  8  9 10 11]

np.delete on 2-D

axis=0 removes rows and axis=1 removes columns. With no axis, the array is flattened first and the index counts across every value.

python

import numpy as np

m = np.array([[11, 12, 13, 14],
              [21, 22, 23, 24],
              [31, 32, 33, 34]])
print(np.delete(m, 1, axis=1))
print(np.delete(m, [2, 3], axis=1))
print(np.delete(m, 0, axis=0))
print(np.delete(m, 2))

Output:

text

[[11 13 14]
 [21 23 24]
 [31 33 34]]
[[11 12]
 [21 22]
 [31 32]]
[[21 22 23 24]
 [31 32 33 34]]
[11 12 14 21 22 23 24 31 32 33 34]

Adding many values

Each np.append copies the whole array. When you collect values one at a time, add them to a list and convert once at the end.

python

import numpy as np

squares = []
for m in range(1, 6):
    squares.append(m * m)
arr = np.array(squares)
print(arr)

Output:

text

[ 1  4  9 16 25]

Key takeaways

append, insert, and delete return a new array
Without an axis, a 2-D array is flattened first
axis=0 works on rows, axis=1 on columns
Collect many values in a list, then convert once
Next: Splitting Arrays
Previous: Filtering Arrays

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Append, Insert, and Delete Quiz

Does np.append change the array you pass in?

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