trade-register.csv
, taking into account the specified lines to skip and file encoding. After loading the data, we will analyze it to understand the relationships between suppliers and recipient countries. This will help us in plotting the map that visualizes these relationships.Supplier
and Recipient
columns. Then, we'll use the geopy
library to fetch the latitude and longitude for each country.geopy
library. This process may take some time due to the number of countries and potential rate limits of the geocoding service.Supplier
and Recipient
columns and use the get_coordinates
function to fetch the geographical coordinates for each country.get_coordinates
function ready, let's proceed to fetch the latitude and longitude for each unique country involved in the trade register. This process may take some time due to the number of countries and potential rate limits of the geocoding service.None
values. This could be due to various reasons such as limitations in the geocoding service or mismatches between country names in the dataset and those recognized by pycountry
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