Python Data Visualization Transcripts
Lecture: API overview
0:00 Now let me go over the basics of pandas, plotting. An important thing to remember is that it is based on matplot lib.
0:08 So all of the information that we learned in the previous chapter will be really helpful
0:12 for understanding how to create and customize your plots with pandas. In addition, you can specify other backend,
0:21 such as plotly or Altair to provide some of those plotting capabilities in pandas. Within pandas, there are two primary API's for plotting.
0:31 There are also some specialized API's which I will cover later. The first primary method is a plot method that you can call on a series or
0:40 data frames and it looks like this. If we want to plot a histogram, we can do a dot plot on the comb08, column and pass the parameter kind equals hist.
0:52 Or we can do a plot.hist and it will create a histogram And both of those calls will create a histogram that looks the same.
1:02 The other option is that there is a specialized API for histogram, and box plots that you call on the data frames.
1:10 And it has a separate interface in this example, I create a histogram but actually passed the column and then it creates a
1:18 histogram that looks very similar. There is some additional formatting that's done but the basics are the same.
1:25 This specialized API does provide some enhanced capabilities that I will walk through in a moment.