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This Python matplotlib tutorial will help you understand what is matplotlib, types of plots, plotting graphics and subgraphs, adding a graph inside a graph, graph parameters, line graphs, canvas grid & axis range, 2D plots, radar charts, histogram, 3D surface image along with a practice example. Data visualization is the technique to present the data in a pictorial or graphical format. It enables stakeholders and decision makers to analyze data visually. Many new python data visualization libraries are introduced recently, such as matplotlib, Vispy, bokeh, Seaborn, pygal, folium, and networkx. The matplotlib has emerged as the main data visualization library. The data in a graphical format allows them to identify new trends and patterns easily. Matplotlib is a python two-dimensional plotting library for data visualization and creating interactive graphics or plots. Using pythons matplotlib, data visualization of large and complex data becomes easy. Now, let us get started and understand matplolib and how it can be used.
The below topics are explained in this Matplotlib tutorial:
1. What is matplotlib? (00:55)
2. Types of plots (01:25)
3. Plotting graphics and subgraphs
4. Adding a graph inside a graph
5. Graph parameters - title, label, legend
6. Line graphs - line types, color and transparency
7. Canvas grid and axis range
8. 2D plots - scatter, step, bar, fill_between
9. Radar chart, histogram, the contour image
10. 3D surface image
11. Practice example (pie chart)
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