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Python practice problems help beginners to become experts in a python programming language with a small amount of practice effort.
Write a NumPy program to calculate the standard deviation of an array.
[2, 4, 4, 4, 5, 5, 7, 9]
2.0 2.138
np.std (population); ddof=1 for a sample.import numpy as npa = np.array([2, 4, 4, 4, 5, 5, 7, 9])print(np.std(a), round(float(np.std(a, ddof=1)), 3))2.0 2.138
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Write a NumPy program to calculate the sine of angles.
0, 30, 90 degrees
[0. 0.5 1. ]
np.sin.import numpy as npprint(np.sin(np.radians([0, 30, 90])).round(3))[0. 0.5 1. ]
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Write a NumPy program to check whether two arrays have the same dimensions.
True False
.shape.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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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)
reshape(-1, n) lets NumPy work out one dimension.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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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
pd.DataFrame(array, columns=[...]).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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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]]
np.vstack stacks rows; np.hstack joins side by side.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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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]
np.nanmean(axis=1).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]
The third row’s average is 17 / 3 = 5.67; the original sample answer (8.5) was not correct.
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Write a NumPy program to calculate the sum of each column.
[[6, 5, 7], [10, 9, 1], [7, 8, 2]]
[23 22 10]
sum(axis=0).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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Write a NumPy program to copy data from one array to another.
[ 1 77 3] [99 2 3]
copy() creates independent data; a slice is only a view.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]
Changing the copy leaves a alone, but changing the view changes a.
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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]]
a[:2, :2].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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