73 lines
2.9 KiB
Markdown
73 lines
2.9 KiB
Markdown
### source:
|
|
- https://www.kaggle.com/datasets/gregorut/videogamesales.
|
|
|
|
### require:
|
|
- cleaned data provide on the unit Moodle page
|
|
- lecture 4 slide 52
|
|
- for documentation
|
|
- standard academic report.
|
|
|
|
### delivery:
|
|
- FOP_Assignment1_<student id>.zip
|
|
- Your code
|
|
- README
|
|
- User Documentation
|
|
- and Report
|
|
- A signed and dated Declaration of Originality.
|
|
|
|
- two parts as
|
|
- (a) coding part and
|
|
- four main tasks
|
|
1. Reading games sale data stored in the `GamesSales.csv` file.
|
|
1. Displaying a menu asking the user what filters user want to apply to the data.
|
|
- `Add filters`: User select a smaller portion (based on filters) of data to print or graph.
|
|
- `Print names`: Prints the names and descriptions (attributes) of the filtered games (based on the filter).
|
|
- `Graph data`: Graphs the filtered data (based on the filters).
|
|
- `Reset filters`: Removes all the applied filters.
|
|
- `Exit`: Exits the program.
|
|
1. Displaying the data matched by the set filters as a graph or by printing to the terminal.
|
|
- It is up to you as to 4 what type of graph you want to use to plot the data
|
|
- (bar, line, histogram, etc)
|
|
1. Reset filter by removing all the filters that has been applied.
|
|
|
|
- (b) documentation and report
|
|
- documentation
|
|
- minimum of 2 pages long
|
|
- should follow the structure of a standard academic report.
|
|
- An overview of each of your program's features.
|
|
- A guide on how to use your program.
|
|
- A discussion of your code,
|
|
- explaining the features you implemented,
|
|
- how you implemented them and
|
|
- why you implemented them the way you did.
|
|
- report
|
|
- will be a mini-paper that is 2-3 pages long
|
|
- - References: see unit outlines for styling guide.
|
|
- Such as, what games have the most entries?
|
|
- What is the distribution of games (by rating) on sales data?
|
|
- Which game has the most highest rating values and/or
|
|
- any other interesting insights you discovered?
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
### CSV fields
|
|
- Name: In market name of the game.
|
|
- Platform: The gaming platform for the game is designed (e.g., x360 PS5)
|
|
- Year: Year of release.
|
|
- Genre: Category based on recent games classification. (e.g., Sports)
|
|
- Publisher: Agency responsible for publication of the game.
|
|
- NA_Sales: Sales in North America (in millions).
|
|
- EU_Sales:. Sales in Europe (in millions).
|
|
- JP_Sales: Sales in Japan (in millions).
|
|
- Other_Sales: Sales in the rest of the world (in millions)
|
|
- Global_Score: Total worldwide sales.
|
|
- Critic_Score: Critic score given to each game.
|
|
- Critic_Count: Number critic contributed for the rating.
|
|
- User_Score: User rating for each game.
|
|
- User_Count: Number of users contributed to the rating.
|
|
- Developer: The name of developer.
|
|
- Raring: Overall market rating. |