Seaborn is a statistical data visualization library based on Matplotlib. We will use Seaborn to find interesting relationships in our data and turn them into informative graphs. As you will see shortly, this involves less code than if we were to use Matplotlib directly.
So far, I printed the Pandas data frame in Jupyter to see what data is in it. That works for small data frames but is rather useless for large ones. Let us find better ways to explore our data in Pandas.
The data we get is not always in a useful format. With a bit of Pandas magic we can clean-up a lot and automate the process along the way.
The methods to plot a data frame in Pandas (here & here) create us useful graphics. But as with Matplotlib, sometimes they do not fully meet our requirements. Let us find out how we can fix that in Pandas.
Plotting with Pandas works without much effort. Today we look at the two dedicated methods hist() and boxplot() directly on the data frame.
We are back on our journey to data visualisation. Matplotlib offered us a lot of features, but especially the combination of multiple plots into one graphic is painful. With Pandas we get an abstraction of Matplotlib that works on the whole data frame. Let us explore the plotting capabilities we get in Pandas.
Last week we explored the basic features for creating graphs with NetworkX. Today we put that knowledge to practice and untangle dependencies between projects.
Today we make a small deviation from the plots of Matplotlib and work with networks and graphs (as in computer science). Having a structure that allows us to define objects and their relation to each other is not only interesting for theoretical problems. In this post we look at the basics and next week we put that knowledge into practical use.
Matplotlib allows us to draw our annotations on top of a plot. Today we look what happens if we draw a plot on top of another plot.
Matplotlib can create a wide range of plots for us. But sometimes we need to point out an important aspect that only we know about. Let us figure out how we can do that.