/fandango_score_comparison

The data download from fivethirtyeight. The dataset contains information on most movies from 2014 and 2015 and was used to help the team at FiveThirtyEight explore Fandango's suspiciously high ratings.

Primary LanguagePython

This project is still updating,some conclusion are not written yet.
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In this project,I'll be working with the file fandango_score_comparison.csv.Here are some of the columns in the dataset:

FILM - film name.
RottenTomatoes - Rotten Tomatoes critics average score.
RottenTomatoes_User - Rotten Tomatoes user average score.
RT_norm - Rotten Tomatoes critics average score (normalized to a 0 to 5 point scale).
RT_user_norm - Rotten Tomatoes user average score (normalized to a 0 to 5 point scale).
Metacritic - Metacritic critics average score.
Metacritic_user_nom - Metacritic user average score (normalized to a 0 to 5 point scale).
Metacritic_norm - Metacritic critics average score (normalized to a 0 to 5 point scale).
Fandango_Ratingvalue - Fandango user average score (0 to 5 stars).
IMDB_norm - IMDB user average score (normalized to a 0 to 5 point scale).

In this project, I will make a comparison by calculating statistical values,such as mean,variance,standard deviation，
covariance，correlation and so on.