Create Random Data & 8 Essential Plots in Python with NumPy & Matplotlib
This guide shows how to set up a Windows 10 Python 3.6 environment, generate random numbers using NumPy’s various methods, and visualize the data with Matplotlib through eight chart types—including scatter, line, bar, histogram, pie, and box plots—complete with code snippets and images.
1. Environment
System: Windows 10 Python version: 3.6.1 Libraries: matplotlib, numpy
2. Methods to Generate Random Numbers with NumPy
Demonstrates several ways to produce random data using numpy.random.
3. Scatter Plot
Example of a scatter plot created with Matplotlib.
4. Line Plot
Uses the plot function to draw a line chart.
5. Bar Chart
Shows a horizontal bar chart (orientation set to horizontal).
6. Histogram
Illustrates a histogram of random data.
7. Pie Chart
Displays a pie chart representing categorical distribution.
8. Box Plot
Creates a box plot to visualize data distribution and outliers.
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