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F1 Data Challenge: Purpose
F1 Data Challenge: Purpose
The data visualization is meant to be eye-catching and attract the attention of those who are normally not Formula 1 fans. Formula 1 already has a highly skilled and highly experienced team of data science and analyst wizards; this is not that.
This is bite-sized information consumed quickly and easily by the data and Formula 1 novice.
Challenge Overview: F1 Prediction
Challenge Overview: F1 Prediction
Perform an Exploratory Data Analysis (EDA) on the 2024 Formula 1 season, focusing on pit stop strategies, tire usage, and race performance. Participants will use detailed lap-by-lap data to explore patterns and relationships influencing race outcomes, providing valuable insights into the strategic decisions made by teams and drivers throughout the season.
https://competitions.desights.ai/challenge/31/0
Wrangling Process
Wrangling Process
Phase 1
Phase 1
Consult industry experts for terminology
Split the necessary columns of data
Format column datatypes (i.e., duration, number, etc.)
Use VLOOKUP to connect driver FullName to Driver (abbreviations), results_2024.csv to lap_2024.csv
Convert time into a uniform format
Convert Time into a Uniform Format:
Using Google Sheets, convert the time values in columns 'B' through 'H' into total seconds or total minutes. I used formulas:
For seconds: =MINUTE(B2)*60 + SECOND(B2)
For minutes: =MINUTE(B2) + SECOND(B2)/60
Driver Position per Lap by Event
Driver Position per Lap by Event
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