Python Matplotlib Basics
In this page:
What is Matplotlib?
Matplotlib is Python's foundational 2D plotting library, and its pyplot module offers a MATLAB-inspired interface for building charts step by step. This tutorial's examples use the non-interactive Agg backend, which renders directly to image files rather than opening a graphical window, so the code runs safely without a display attached.
Example: What is Matplotlib?
import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt
plt.plot([1, 2, 3], [4, 5, 6])
plt.savefig("chart.png")
print("Chart saved")Customizing Labels and Titles
plt.title(), plt.xlabel(), and plt.ylabel() add descriptive text around a plot, and plt.legend() adds a key identifying each line or series when a chart shows more than one. A chart without these is often unreadable to anyone besides the person who made it, since the axes and series carry no context on their own.
Example: Customizing Labels and Titles
import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt
plt.plot([1, 2, 3], label="Sales")
plt.title("Monthly Sales")
plt.xlabel("Month")
plt.ylabel("Amount")
plt.legend()
plt.savefig("chart.png")Line Customization
The color, linewidth, and linestyle arguments to plt.plot() control a line's visual appearance -- letting you distinguish multiple series on the same chart by more than just their shape, which matters especially once a plot has three or more overlapping lines.
Example: Line Customization
import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt
plt.plot([1, 2, 3], color="red", linewidth=2, linestyle="--")
plt.savefig("chart.png")
print("Styled line saved")Creating Gridlines
plt.grid(True) overlays light reference lines across the plotting area, making it much easier for a viewer to read off approximate values at a glance rather than having to visually interpolate between bare axis tick marks.
Example: Creating Gridlines
import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt
plt.plot([1, 2, 3])
plt.grid(True)
plt.savefig("chart.png")Saving Figures
plt.savefig('filename.png') writes the current figure to disk as an image file, supporting formats like PNG, PDF, and SVG based on the file extension you give it. This is how generated charts get embedded into reports, dashboards, or web pages instead of only appearing in an interactive window.
Example: Saving Figures
import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt
plt.plot([1, 2, 3])
plt.savefig("chart.png")
print("Saved as PNG")Chapter Quiz — Complete all 14 topics to unlock
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Complete these topics first:
- Python NumPy Introduction
- Python NumPy Arrays
- Python Pandas Introduction
- Python Pandas DataFrame
- Python Matplotlib Basics
- Python Data Visualization
- Python Statistics Module
- Python CSV & Data Analysis
- Python requests Module
- Python JSON & APIs
- Python Web Scraping Basics
- Python Flask Introduction
- Python Django Introduction
- Python MongoDB