conduct your own data analysis to create a shareable file that documents your findings. You should start by taking a look at your dataset and brainstorming what questions you could answer using it. Then you should use pandas and NumPy to answer the questions you are most interested in, and create a report sharing the answers. You will not be required to use inferential statistics or machine learning to complete this project, but you should make it clear in your communications that your findings are tentative. This project is open-ended in that we are not looking for one right answer.
Overview and Notes
This data set contains information about 10,000 movies collected from The Movie Database (TMDb), including user ratings and revenue.
- Certain columns, like ‘cast’ and ‘genres’, contain multiple values separated by pipe (|) characters.
- There are some odd characters in the ‘cast’ column. Don’t worry about cleaning them. You can leave them as is.
- The final two columns ending with “_adj” show the budget and revenue of the associated movie in terms of 2010 dollars, accounting for inflation over time.
|
|
Example Questions
| Which genres are most popular from year to year? What kinds of properties are associated with movies that have high revenues? |
|
|
|