📖 Background
In the mystical land of Arcadia, where pixels and bits weave the fabric of reality, the ancient and revered Valut of Classics has begun to fade into obscurity. This vault, a legendary archive that houses the most iconic video games from 1980 to 2020, is threatened to be lost forever. Without intervention, the stories and legacies of these timeless classics may be forgotten.
You are a brave Data Sorcerer summoned by the Keepers of the vault. Your mission is not just a task, but an exhilarating adventure. You will delve into the vault, uncover the secrets of these legendary titles, and breathe new life into their stories. Along the way, you will face a series of challenges designed to test your skills in data analysis, visualization, and storytelling. Get ready for an epic journey! You must:
- Map the classics
- Race through time
This image was generated with an AI tool.
💾 The data
Columns | Description |
---|---|
Rank | Ranking of overall sales |
Name | Name of the game |
Platform | Platform of the games release (Wii, DS, PS3, etc.) |
Year | Release year |
Genre | Category of the game |
Publisher | who developed it (i.e. Nintento,Microsoft Games Studio, etc.) |
NA_Sales | Sales in North America (in millions) |
EU_Sales | Sales in Japan (in millions) |
JP_Sales | Sales in Japan (in millions) |
Other_Sales | Sales in the rest of the world (in millions |
Global_Sales | Total worldwide sales |
import pandas as pd
games = pd.read_csv('./data/vgsales.csv')
games.head()
💪 Challenge
Challenge 1: The Genre and Platform Expedition
- Investigate and visualize the distribution of video game genres and teams behind them from 1980 to 2020.
Challenge 2: The Racing Bar Chart Extravaganza
- Craft the ultimate bar chart race visual that crowns the top-selling video games of all time.
🧑⚖️ Judging criteria
This is a community-based competition. The top 5 most upvoted entries will win.
The winners will receive DataCamp merchandise.
✅ Checklist before publishing
- Rename your workspace to make it descriptive of your work. N.B. you should leave the notebook name as
notebook.ipynb
. - Remove redundant cells like the judging criteria, so the workbook is focused on your work.
- Check that all the cells run without error.
⌛️ Time is ticking. Good luck!
Challenge 1: The Genre and Platform Expedition
Load and Explore the Data:
import pandas as pd
games = pd.read_csv('./data/vgsales.csv')
games.head()
games['Genre'].value_counts()
games.shape
games.info()
Preprocess the Data