Numbers greater than a value

Write a NumPy program to extract numbers greater than 6.

[[6, 5], [10, 9], [7, 8]]

[10  9  7  8]

Approach

1. A boolean mask.

Solution

import numpy as npa = np.array([[6, 5], [10, 9], [7, 8]])print(a[a > 6])

[10  9  7  8]

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Sort rows by the first column

Write a NumPy program to sort the rows of an array by the first column.

[[6, 5], [10, 9], [7, 8]]

[[ 6  5]
 [ 7  8]
 [10  9]]

Approach

1. argsort on the column gives the row order.

Solution

import numpy as npa = np.array([[6, 5], [10, 9], [7, 8]])print(a[a[:, 0].argsort()])

[[ 6  5]
 [ 7  8]
 [10  9]]

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Sort each row

Write a NumPy program to sort each row in ascending order.

[[6, 5], [10, 9], [8, 7]]

[[ 5  6]
 [ 9 10]
 [ 7  8]]

Approach

1. np.sort(a, axis=1).

Solution

import numpy as npprint(np.sort(np.array([[6, 5], [10, 9], [8, 7]]), axis=1))

[[ 5  6]
 [ 9 10]
 [ 7  8]]

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Transpose a matrix

Write a NumPy program to swap the rows and columns of a matrix.

[[5, 6], [7, 8], [9, 10]]

[[ 5  7  9]
 [ 6  8 10]]

Approach

1. .T.

Solution

import numpy as npprint(np.array([[5, 6], [7, 8], [9, 10]]).T)

[[ 5  7  9]
 [ 6  8 10]]

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One-dimensional array

Write a NumPy program to create a one-dimensional array.

[65 90  1  3  5] 1

Approach

1. np.array with a flat list.

Solution

import numpy as npa = np.array([65, 90, 1, 3, 5])print(a, a.ndim)

[65 90  1  3  5] 1

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Find missing data

Write a NumPy program to find the missing (NaN) values in an array.

[[1, 5, nan], [8, nan, 9]]

[[False False  True]
 [False  True False]]
2 missing

Approach

1. np.isnan().

Solution

import numpy as npa = np.array([[1, 5, np.nan], [8, np.nan, 9]])print(np.isnan(a))print(np.isnan(a).sum(), "missing")

[[False False  True]
 [False  True False]]
2 missing

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Array to list

Write a NumPy program to convert an array into a list.

[[3, 0], [6, 4]]

[[3, 0], [6, 4]]

Approach

1. .tolist() gives plain Python ints.

Solution

import numpy as npprint(np.array([[3, 0], [6, 4]]).tolist())

[[3, 0], [6, 4]]

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List to array

Write a NumPy program to convert a list into an array.

[[3, 0], [6, 4]]

[[3 0]
 [6 4]]

Approach

1. np.array().

Solution

import numpy as npprint(np.array([[3, 0], [6, 4]]))

[[3 0]
 [6 4]]

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Add a vector to each row

Write a NumPy program to add a vector to each row of a matrix.

[2, 5] and [[5, 3], [7, 4]]

[[7 8]
 [9 9]]

Approach

1. Broadcasting adds the vector to every row.

Solution

import numpy as npprint(np.array([[5, 3], [7, 4]]) + np.array([2, 5]))

[[7 8]
 [9 9]]

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Dot product of two vectors

Write a NumPy program to calculate the dot product of two vectors.

[5, 3] and [7, 4]

47 47

Approach

1. np.dot(a, b) or a @ b.

Solution

import numpy as npa, b = np.array([5, 3]), np.array([7, 4])print(np.dot(a, b), a @ b)

47 47

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