Page 257 - Robotics and AI class 10
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# Creating a numpy array
arr = np.array([50, 10, 40, 20, 30])
# Sorting the array in ascending order
sorted_arr = np.sort(arr)
print("Sorted Array (ascending):", sorted_arr)
# Sorting the array in descending order
sorted_arr_desc = np.sort(arr)[::-1]
print("Sorted Array (descending):", sorted_arr_desc)
Output:
Sorted Array (ascending): [10 20 30 40 50]
Sorted Array (descending): [50 40 30 20 10]
g. Create a Numpy array of marks and calculate the mean, median and mode.
import numpy as np
from scipy import stats
# Create a NumPy array of marks
marks = np.array([85, 92, 78, 65, 88, 75, 90, 70, 82, 95])
# Calculate the mean using NumPy's mean() function
mn = np.mean(marks)
print("Mean:", mn)
# Calculate the median using NumPy's median() function
mdn = np.median(marks)
print("Median:", mdn)
# Calculate the mode using SciPy's mode() function
mode = stats.mode(marks)
print("Mode:", mode.mode[0])
Output:
Mean: 82.0
Median: 83.5
Mode: 65
5. Display an image using matplotlib and print its numpy array form. Also check the data type and shape of
the numpy array. Use the library `skimage' for getting sample images.
Ans. import numpy as np
import matplotlib.pyplot as plt
from skimage import data
# Load a sample image using skimage
image = data.astronaut()
Assignment 255

