Part 13 – Matplotlib Tutorial: Line Charts, Markers & Styles in Python
Learn data visualisation in Python with Matplotlib — plot and style line charts, markers, colours, labels, and grids in this hands-on lesson.
After selecting and analysing your data with pandas, the next skill every data analyst needs is turning numbers into clear, readable charts. This lesson is your hands-on introduction to Matplotlib, Python's most widely used plotting library — and it's the next step in the Python & Data Science Masterclass.
You won't just learn the theory — we plot together, step by step, and style every part of the chart.
In this 18-minute lesson, you'll learn to:
Create your first line chart with .plot() and .show()
Control line style (ls) and line colour (c)
Add and customise markers — types, size (ms), edge colour (mec), face colour (mfc)
Label your chart properly with xlabel, ylabel, and a title
Style text using font dictionaries for clean, professional plots
Add a background grid with .grid() for readability
By the end, you'll be able to build clear, presentation-ready line charts from your own data.
⏱️ CHAPTERS
00:00 – Introduction to Matplotlib and data visualization
01:44 – Basics of plotting with Matplotlib
02:20 – Installation and importing the library
03:22 – Creating line plots with Pyplot and NumPy
06:39 – Defining X and Y axis data points
07:08 – Highlighting data points using markers
10:52 – Customizing marker styles, colors, and lines
15:20 – Adding graph titles and axis labels
17:21 – Enabling grid lines for readability
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