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Python Numpy Practice Problems
Write a NumPy program to find the index of the maximum value.
[76, 36, 56, 90]
3
argmax.import numpy as npprint(np.argmax([76, 36, 56, 90]))3
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Write a NumPy program to find the union of two arrays.
[56, 18, 28, 36], [76, 36, 56]
[18 28 36 56 76]
np.union1d.import numpy as npprint(np.union1d([56, 18, 28, 36], [76, 36, 56]))[18 28 36 56 76]
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Write a NumPy program to find the unique values of array1 that are not in array2.
[56, 18, 28, 36], [76, 36, 56]
[18 28]
np.setdiff1d.import numpy as npprint(np.setdiff1d([56, 18, 28, 36], [76, 36, 56]))[18 28]
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Write a NumPy program to get the unique elements of an array.
[25, 33, 10, 45, 33, 10]
[10 25 33 45] [25 33 10 45]
np.unique returns them sorted; use the index to keep first-seen order.import numpy as npa = np.array([25, 33, 10, 45, 33, 10])print(np.unique(a))_, first = np.unique(a, return_index=True)print(a[np.sort(first)])[10 25 33 45] [25 33 10 45]
return_index gives each value’s first position; sorting those keeps the original order.
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Write a NumPy program to find the common elements of two arrays.
[56, 18, 28, 36], [76, 36, 56]
[36 56]
np.intersect1d (sorted result).import numpy as npprint(np.intersect1d([56, 18, 28, 36], [76, 36, 56]))[36 56]
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Write a NumPy program to find the real and imaginary parts of complex numbers.
[6+2j, 10+5j]
Real: [ 6. 10.] Imaginary: [2. 5.]
.real and .imag.import numpy as npa = np.array([6 + 2j, 10 + 5j])print("Real:", a.real, "Imaginary:", a.imag)Real: [ 6. 10.] Imaginary: [2. 5.]
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Write a NumPy program to add row 2 to row 1.
[[6, 5], [10, 9], [7, 8]]
[[16 14] [10 9] [ 7 8]]
a[0] += a[1].import numpy as npa = np.array([[6, 5], [10, 9], [7, 8]])a[0] += a[1]print(a)[[16 14] [10 9] [ 7 8]]
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Write a NumPy program to multiply row 1 of an array by 2.
[[6, 5], [10, 9], [7, 8]]
[[12 10] [10 9] [ 7 8]]
*=.import numpy as npa = np.array([[6, 5], [10, 9], [7, 8]])a[0] *= 2print(a)[[12 10] [10 9] [ 7 8]]
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Write a NumPy program to swap the rows of an array (first and last).
[[6, 5], [10, 9], [7, 8]]
[[ 7 8] [10 9] [ 6 5]]
import numpy as npa = np.array([[6, 5], [10, 9], [7, 8]])a[[0, 2]] = a[[2, 0]]print(a)[[ 7 8] [10 9] [ 6 5]]
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Write a NumPy program to replace numbers greater than or equal to 8 with 0.
[[6, 5], [10, 9], [7, 8]]
[[6 5] [0 0] [7 0]]
np.where(condition, new, old).import numpy as npa = np.array([[6, 5], [10, 9], [7, 8]])print(np.where(a >= 8, 0, a))[[6 5] [0 0] [7 0]]
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