In this video, we will learn how to create a special type of map called choropleth map with Folium. I'm sure that most of you have seen maps similar to this one and this one. These are what we call choropleth maps. So what is a choropleth map? A choropleth map is a thematic map in which areas are shaded or patterned in proportion to the measurement of the statistical variable being displayed on the map, such as population density or per capita income. The higher the measurement the darker the color. So, the map to the left is a choropleth map of the world showing infant mortality rate per 1000 births. The darker the color the higher the infant mortality rate. According to the map, African countries have very high infant mortality rates with some of them reporting a rate that is higher than 160 per 1000 births. Similarly, the map to the right is a choropleth map of the US showing population per square mile by state. Again, the darker the color the higher the population. According to the map, states in the eastern part of the US tend to be more populous than states in the western part, with California being an exception. In order to create a choropleth map of a region of interest, Folium requires a Geo JSON file that includes geospatial data of the region. For a choropleth map of the world, we would need a Geo JSON file that lists each country along with any geospatial data to define its borders and boundaries. Here is an example of what the Geo JSON file would include about each country. The example here pertains to the country Brunei. As you can see, the file includes the country's name, it's ID, geometry shape, and the coordinates that define the country's borders and boundaries. So let's see how we can create a choropleth map of the world like this one showing immigration to Canada. Before we go over the code to do that, let's do a quick recap of our dataset. Recall that each row represents a country and contains metadata about the country such as where it is located geographically and whether it is developing or developed. Each row also contains numerical figures of annual immigration from that country to Canada from 1980 to 2013. Now let's process the data, and let's add an extra column which represents the cumulative sum of annual immigration from each country from 1980 to 2013. So for Afghanistan for example, it is 58,639, total, and for Albania it is 15,699, and so on. And let's name our dataframe df_Canada. So now that we know how our data is stored in the dataframe, df_Canada, let's see how we can generate a choropleth map of the world showing immigration to Canada. We should be experts now in creating world maps with Folium. So let's go ahead and create a world map, but this time let's use the mapbox bright tiles set. The result is a nice world map displaying the name of every country. Now to convert this map into a choropleth map, we first define a variable that points to our Geo JSON file. Then we apply the choropleth function to our world map and we tell it to use the columns "Country" and "Total" in our df_Canada dataframe, and to use the country names to look up the geospatial information about each country in the Geo JSON file. And there you have it: A choropleth map of Canada showing the intensity of immigration from different countries worldwide. In the lab session, we explore choropleth maps in more details, so please make sure to complete this module's lab session. And with this, we conclude our video on choropleth maps.