Do two arrays have the same shape?

Write a NumPy program to check whether two arrays have the same dimensions.

True False

Approach

1. Compare .shape.

Solution

import numpy as npa, b, c = np.zeros((2, 3)), np.ones((2, 3)), np.ones((3, 2))print(a.shape == b.shape, a.shape == c.shape)

True False

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Create and reshape

Write a NumPy program to create an array and reshape it.

[[ 0  1  2  3]
 [ 4  5  6  7]
 [ 8  9 10 11]]
(2, 6)

Approach

1. reshape(-1, n) lets NumPy work out one dimension.

Solution

import numpy as npa = np.arange(12)print(a.reshape(3, 4))print(a.reshape(-1, 6).shape)

[[ 0  1  2  3]
 [ 4  5  6  7]
 [ 8  9 10 11]]
(2, 6)

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Array to a DataFrame with headers

Write a NumPy program to convert an array into a pandas DataFrame with column headers.

   maths  science
0     90       85
1     72       64
2     88       91

Approach

1. pd.DataFrame(array, columns=[...]).

Solution

import numpy as npimport pandas as pd a = np.array([[90, 85], [72, 64], [88, 91]])df = pd.DataFrame(a, columns=["maths", "science"])print(df)

   maths  science
0     90       85
1     72       64
2     88       91

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Merge arrays of the same shape

Write a NumPy program to merge two arrays of identical shape.

[[1 2]
 [3 4]
 [5 6]
 [7 8]]
[[1 2 5 6]
 [3 4 7 8]]

Approach

1. np.vstack stacks rows; np.hstack joins side by side.

Solution

import numpy as npa = np.array([[1, 2], [3, 4]])b = np.array([[5, 6], [7, 8]])print(np.vstack((a, b)))print(np.hstack((a, b)))

[[1 2]
 [3 4]
 [5 6]
 [7 8]]
[[1 2 5 6]
 [3 4 7 8]]

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Row averages ignoring NaN

Write a NumPy program to calculate the average of each row, ignoring NaNs.

[[6, 5, nan], [nan, 9, 1], [7, 8, 2]]

[5.5  5.   5.67]

Approach

1. np.nanmean(axis=1).

Solution

import numpy as npa = np.array([[6, 5, np.nan], [np.nan, 9, 1], [7, 8, 2]])print(np.nanmean(a, axis=1).round(2))

[5.5  5.   5.67]

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Sum of all columns

Write a NumPy program to calculate the sum of each column.

[[6, 5, 7], [10, 9, 1], [7, 8, 2]]

[23 22 10]

Approach

1. sum(axis=0).

Solution

import numpy as npprint(np.array([[6, 5, 7], [10, 9, 1], [7, 8, 2]]).sum(axis=0))

[23 22 10]

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Copy an array

Write a NumPy program to copy data from one array to another.

[ 1 77  3] [99  2  3]

Approach

1. copy() creates independent data; a slice is only a view.

Solution

import numpy as npa = np.array([1, 2, 3])b = a.copy()view = a[:]b[0] = 99view[1] = 77print(a, b)

[ 1 77  3] [99  2  3]

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Top-left 2 × 2 block

Write a NumPy program to extract the first and second elements of the first and second rows.

[[6, 5, 7], [10, 9, 1], [7, 8, 2]]

[[ 6  5]
 [10  9]]

Approach

1. a[:2, :2].

Solution

import numpy as npa = np.array([[6, 5, 7], [10, 9, 1], [7, 8, 2]])print(a[:2, :2])

[[ 6  5]
 [10  9]]

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First two columns

Write a NumPy program to access the first two columns of an array.

[[6, 5, 7], [10, 9, 1], [7, 8, 2]]

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

Approach

1. a[:, :2].

Solution

import numpy as npa = np.array([[6, 5, 7], [10, 9, 1], [7, 8, 2]])print(a[:, :2])

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

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Save an array to CSV

Write a NumPy program to save an array to a CSV file.

a,b,c
1,2,3
4,5,6

Approach

1. np.savetxt with delimiter=",".

Solution

import numpy as npa = np.array([[1, 2, 3], [4, 5, 6]])np.savetxt("data.csv", a, delimiter=",", fmt="%d", header="a,b,c", comments="")print(open("data.csv").read())

a,b,c
1,2,3
4,5,6

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