NumPy: Compute the histogram of nums against the bins

Last update on March 25 2025 12:19:50 (UTC/GMT +8 hours)

14. Compute Histogram of Data Against Bins

Write a NumPy program to compute the histogram of nums against the bins.

Sample Solution:

Python Code:

# Importing necessary libraries
import numpy as np
import matplotlib.pyplot as plt

# Creating an array of numbers
nums = np.array([0.5, 0.7, 1.0, 1.2, 1.3, 2.1])

# Defining the bins
bins = np.array([0, 1, 2, 3])

# Displaying the original arrays
print("nums: ", nums)
print("bins: ", bins)

# Calculating the histogram using numpy's histogram function
print("Result:", np.histogram(nums, bins))

# Creating a histogram plot using matplotlib
plt.hist(nums, bins=bins)

# Displaying the histogram
plt.show() 

Sample Output:

nums:  [0.5 0.7 1.  1.2 1.3 2.1]
bins:  [0 1 2 3]
Result: (array([2, 3, 1], dtype=int64), array([0, 1, 2, 3]))

Explanation:

In the above exercise –

nums = np.array([0.5, 0.7, 1.0, 1.2, 1.3, 2.1]): This code creates a NumPy array containing the numbers to be plotted on the histogram.

bins = np.array([0, 1, 2, 3]): This code creates a NumPy array containing the bin edges for the histogram.

print("Result:", np.histogram(nums, bins)): This line calculates and prints the histogram of the given numbers using the specified bins. np.histogram returns two arrays: the histogram values and the bin edges.

plt.hist(nums, bins=bins): This line plots the histogram using Matplotlib's hist() function. The bins parameter specifies the bin edges to use.

plt.show(): This line displays the histogram plot.

For more Practice: Solve these Related Problems:

• Write a function that computes the histogram of a 1D array of floats using np.histogram with custom bin edges.
• Create a program that plots the histogram using matplotlib and verifies that the bin counts match np.histogram output.
• Implement a solution that normalizes the histogram counts to produce a probability density function.
• Develop a method that dynamically determines optimal bin sizes based on the data range and returns both counts and bin edges.

Python-Numpy Code Editor:

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