﻿ Histogram with NumPy and Matplotlib

# Creating Histogram with NumPy and Matplotlib in Python

## Python Pandas Numpy: Exercise-16 with Solution

Create a histogram of a numerical column using NumPy and Matplotlib.

Sample Solution:

Python Code:

``````import numpy as np
import matplotlib.pyplot as plt

# Create a sample numerical column
data = np.random.randn(1000)  # Generating random data for demonstration

# Create a histogram
hist, edges = np.histogram(data, bins=10)

# Plot the histogram using Matplotlib
plt.hist(data, bins=edges, edgecolor='black', alpha=0.7)
plt.title('Histogram of a Numerical Column')
plt.xlabel('Values')
plt.ylabel('Frequency')
plt.show()
```
```

Output:

```
```

Explanation:

In the exerciser above,

• First we create a sample numerical column (data) with random data using numpy.random.randn(1000).
• The numpy.histogram function is used to calculate the histogram. It returns two arrays: hist (the values of the histogram bins) and edges (the edges of the bins).
• We use Matplotlib (plt.hist()) to plot the histogram, specifying the data, bins, edge color, and other parameters.
• Finally, we add labels and a title to the plot and display it using plt.show().

Flowchart:

Python Code Editor:

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