Matplotlib for Python Developers

This video explains how the simplest kind of data is co relational and how x versus y. plot() and scatter() can be used to visualize this kind of data.

In this video, we will see how we can represent ordinal data, or the distribution of scalar datausing bar charts and histograms.

In this video, we will see how we can represent 3D scalar fields (that is, data with x,y, and z components) with images and contours.

This video explains that not all numbers are created equal: some have uncertainties associated with them!

This video explains what if a region or area is what we want to show and Also, what if a scatter plot is too dense.

In this video, we will see how we can show multiple plots together.

In this video, we will see how we can annotate the colors or styles in our plots.

Now that you are done with the videos of section 2, let’s assess your learning. Here, are a few questions; answer them and validate your learning! The correct answers are provided in a separate sheet

In this video, we will see what components are in a matplotlib plot and how do they work together.

In this video, we will learn which container objects are used for a plot,how can we construct and use them.

In this video, we will see which coordinate systems are used in a matplotlib plot and how does a data point get translated to a position in the plot image.

In this video, we will see how matplotlib constructs the x and y axis andhow does it decide where the ticks go.

In this video, we will learn how matplotlib formats the labels for the ticks on the x and y axis.

In this video, we will see how matplotlib actually displays a plot on the screen or write to a file.

Now that you are done with the videos of section 3, let’s assess your learning. Here, are a few questions; answer them and validate your learning! The correct answers are provided in a separate sheet

In this video, we will see how we can use Jupyter and the notebook to present and work with matplotlib effectively.

In this video, we will see how we can work with Pandas to make data manipulation easier.

In this video, we will see how we can use the rich features of Pandas Dataframes to select and manipulate data.

In this video, we will see how we can use Pandas together with matplotlib to make plots efficiently.

Now that you are done with the videos of section 4, let’s assess your learning. Here, are a few questions; answer them and validate your learning! The correct answers are provided in a separate sheet