Top Rated English Movies of This Decade

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Presentation transcript:

Top Rated English Movies of This Decade Hakeem Walters DSCI101

Categories X Title Rating Total Votes Genre

Ratings of Movies Which genre out of the many that there are, draws in the most attention? Top Picks: Drama Adventure Action Comedy Biography

Data Source List of the Top Movies- Sai Pranava on Kaggle CSV 36KB Provided by IMDB CSV 36KB

Dataset Original Amount of fields: 54 End Amount: 6 X: Number Field Title: Rating: Total Votes: Genre 1 & 2:

Dataset Cont. End Result: Drama:63 Adventure: 39 Action: 33 Comedy: 22 Biography: 21

Genres Action: 33 Adventure: 39 Drama:63 Western:2 Biography:21 Comedy:22 History:1 Romance:5 Fantasy:3

Cont. Mystery:3 Sci-fi: 2 Animation:13 Thriller:4 Sport:1 War:1 Family:1

Meta-Slide X: Where the movie was positioned in its original list setting which was alphabetically Title: Name and year of release for the movie Rating: Initial rating given by the site where the creator of the dataset got it from which was IMDB Total Votes: How many people voted for this movie Genre 1&2: Categories of which the movie falls under

Field Alterations For the X field I changed it up so that the dataset wasn’t sorted alphabetically anymore, and was instead sorted based on the rating field

Field Alterations: Genre For the genres I composed a list of the genres shown in the 2 fields and used countif to show how many of each of them were in the two fields.

Meta-Slide With all the data I collected I was able to discern that out of all the presented movies on this list and the data remaining that Drama was the one most shown, most likely due to the fact that drama is one thing that is shown more often than not in most movies in general. I found this by surfing through all available data multiple times even going over deleted data to come to a complete conclusion and by using countif as previously demonstrated

Problems There were numerous problems with this data: Most of the fields didn’t make any sense or have a clear reason for being there Missing data Inaccuracy Nonsensical analysis In short this dataset had way too many holes and in three cases the data didn’t match what was in the field at all

Discoveries Unlike previously thought, drama has more of a pull than action or adventure does, since even they get more hype they’re still outshined by drama

Future Work Make sure to find all the data and branch out to include the previous decade as well Disclose any of the ones that have holes entirely

QUESTIONS?