Product of an array

Write a NumPy program to calculate the product of an array.

[3, 5, 1]

15

Approach

1. np.prod.

Solution

import numpy as npprint(np.prod([3, 5, 1]))

15

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Is an array empty?

Write a NumPy program to check whether an array is empty.

[4, 8, 0], []

[4 8 0] Array is not empty
[] Array is empty

Approach

1. Check a.size == 0.

Solution

import numpy as npfor a in [np.array([4, 8, 0]), np.array([])]:    print(a, "Array is empty" if a.size == 0 else "Array is not empty")

[4 8 0] Array is not empty
[] Array is empty

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Frequency of unique values

Write a NumPy program to count how often each unique value appears.

[8, 6, 7, 0, 7, 8, 6, 6]

[[0 6 7 8]
 [1 3 2 2]]

Approach

1. np.unique(..., return_counts=True).

Solution

import numpy as npvalues, counts = np.unique([8, 6, 7, 0, 7, 8, 6, 6], return_counts=True)print(np.vstack((values, counts)))

[[0 6 7 8]
 [1 3 2 2]]

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Magnitude of a vector

Write a NumPy program to get the magnitude (length) of a vector.

[3, 5, 1]

5.92

Approach

1. np.linalg.norm.

Solution

import numpy as npprint(round(float(np.linalg.norm([3, 5, 1])), 2))

5.92

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Drop rows with NaN

Write a NumPy program to remove rows that contain NaN.

[[4, nan, 8], [2, 4, 6]]

[[2. 4. 6.]]

Approach

1. Keep rows where no element is NaN.

Solution

import numpy as npa = np.array([[4, np.nan, 8], [2, 4, 6]])print(a[~np.isnan(a).any(axis=1)])

[[2. 4. 6.]]

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Replace negative values

Write a NumPy program to replace negative values with 1.

[[4, 8, -5], [2, -9, 6]]

[[4 8 1]
 [2 1 6]]

Approach

1. Assign through a mask.

Solution

import numpy as npa = np.array([[4, 8, -5], [2, -9, 6]])a[a < 0] = 1print(a)

[[4 8 1]
 [2 1 6]]

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Float array to integers

Write a NumPy program to convert an array of floats to integers.

[[6.7, 5.2], [9.4, 2.7]]

[[6 5]
 [9 2]]
[[7 5]
 [9 3]]

Approach

1. astype(int) truncates; round first if needed.

Solution

import numpy as npa = np.array([[6.7, 5.2], [9.4, 2.7]])print(a.astype(int))print(np.rint(a).astype(int))

[[6 5]
 [9 2]]
[[7 5]
 [9 3]]

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Access by column

Write a NumPy program to print each column of an array.

[[4, 8, 0], [2, 0, 6]]

Column 1: [4 2]
Column 2: [8 0]
Column 3: [0 6]

Approach

1. a[:, j] selects column j.

Solution

import numpy as npa = np.array([[4, 8, 0], [2, 0, 6]])for j in range(a.shape[1]):    print(f"Column {j + 1}:", a[:, j])

Column 1: [4 2]
Column 2: [8 0]
Column 3: [0 6]

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Square every element

Write a NumPy program to print the squares of all elements.

[2, 6, 3, 1]

[ 4 36  9  1]

Approach

1. a ** 2 or np.square.

Solution

import numpy as npprint(np.square(np.array([2, 6, 3, 1])))

[ 4 36  9  1]

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Print every element

Write a NumPy program to print every element of a 2-D array.

[[4, 8, 0], [2, 0, 6]]

4 8 0 2 0 6 

Approach

1. np.nditer or ravel().

Solution

import numpy as npa = np.array([[4, 8, 0], [2, 0, 6]])for x in np.nditer(a):    print(x, end=" ")print()

4 8 0 2 0 6 

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