Interactive Scatter Plots

As you know by now, scatter plots are one of the most essential types of plots for presenting global patterns within a dataset. Naturally, it is important to know how to introduce interactivity in these plots. We will first look at the zoom and reset actions on plots. Before that, though, let's have a look at the dataset.

We can view the HPI dataset using the following code:

import pandas as pd
#Download the data from Github repo 
hpi_url = "https://raw.githubusercontent.com/TrainingByPackt/Interactive-Data-Visualization-with-Python/master/datasets/hpi_data_countries.tsv"
# Once downloaded, read it into a DataFrame using pandas
hpi_df = pd.read_csv(hpi_url, sep='\t')
hpi_df.head()

The output is as follows:

Figure 4.1: HPI dataset

Note that there are 5 numerical/quantitative features in this dataset: Life Expectancy (years), Wellbeing (0-10), Inequality of outcomes, Ecological Footprint...