Advance Plotting Options Using Matplotlib
Explore advanced plotting options in Matplotlib to customize your data visualizations. Learn how to set custom ticks, logarithmic scales, scientific notation, axis adjustments, grid lines, and create multi-plot layouts. This lesson helps you apply complex visualization techniques to effectively present data using Python.
We'll cover the following...
This section covers commonly used concepts in data science workflows. Matplotlib also provides additional features that are less commonly used but remain useful. Refer to the official documentation for additional details. We’ll have a look at a few of these advanced plotting concepts.
Note: Memorizing the code is not required. After identifying the required plot type, refer to this lesson to reuse and adapt the code.
Customized ticks and their labels
Ticks are the values that indicate specific points along the coordinate axes. When we plot a graph, default ticks are created. However, we can set custom ticks using set_xticks and ...