Excercise for Deep Pulusani, merging 3 datasets into one and making some visualizations.
3 csv files. Download outcome csv here: http://www.sharecsv.com/s/e593dd089bc5aaf6583b5187f96cb48e/outcome_interview.csv Download event csv here: http://www.sharecsv.com/s/f9b678bf4a60bafe3f0a4132313e194d/event_interview.csv Download fighter csv here: http://www.sharecsv.com/s/4f1b611a0d9f96d7700adba8b387df21/fighter_interview.csv
The outcome csv contains the matchup data for various mixed martial arts fights - including the two fighters involved, the winner, and the event where it took place - all encoded in IDs. The event csv contains event data for various mixed martial arts events - most importantly the event name. The id corresponds to the event_id in the outcome csv. The fighter csv contains fighter data for various mixed martial arts fighters - their names and their nationalities. The id corresponds to both fighter1_id and fighter2_id in the outcome csv.
The Exercise: Using the csv’s you have, I need a pandas dataframe and corresponding exported csv of all the matchups (reminder: matchups are listed in the outcome csv) with ONLY the following columns: | fighter1_name | fighter2_name | fighter1_nationality | fighter2_nationality | event_name |
*hint you will need to combine data from all three csvs, rename column names, and also get rid of many columns
And last, please make a visualization of your choice showing the distribution of fighters from various nationalities.