final-movie-analysis

A little package for analyzing universal studios movies from 2014-2024

Description

This package demonstrates:

How to scrape movie information from the web for a dirty dataset and clean it (data_creation)
View the dataset (print_dataset_head)
How to analyze a movie dataset (do_analysis_specific)
How to check missingness in the dataset (get_NAs)
How do it all in one step (totality)
How to analyze feature importance (do_ml_analysis_plots, do_ml_analysis_numbers, ml_analysis_findings)
How to analyze feature significance (season_significance, rating_significance, genre_significance, production_method_significance)
How to analyze factor relation (factors_analysis, earnings_correlation, season_earnings, genre_earnings, production_method_earnings, ratings_earnings)
How to analyze a feature over time (graph_revenue, graph_revenue_by_year, graph_revenue_and_profit, analyze_revenue)
How to check one feature specifically (describe_revenue)
How to interpret analysis (factors_findings, revenue_findings)

pip install final-movie-analysis

import sys, os
sys.path.append(os.path.abspath("src"))
from final_movie_analysis.functions import totality
#Create and analyze the data
totality()

MIT

Name		Name	Last commit message	Last commit date
Latest commit History 90 Commits
.vscode		.vscode
__pycache__		__pycache__
docs		docs
src/final_movie_analysis		src/final_movie_analysis
tests		tests
.gitignore		.gitignore
.python-version		.python-version
LICENSE		LICENSE
README.md		README.md
_quarto.yml		_quarto.yml
analyze.ipynb		analyze.ipynb
dirty_data.csv		dirty_data.csv
documentation.qmd		documentation.qmd
domestic_revenues.png		domestic_revenues.png
index.qmd		index.qmd
international_revenues.png		international_revenues.png
ml_movie_data.csv		ml_movie_data.csv
ml_testing.ipynb		ml_testing.ipynb
movie_data.csv		movie_data.csv
pyproject.toml		pyproject.toml
revenue_and_profit.png		revenue_and_profit.png
revenue_by_genre.png		revenue_by_genre.png
revenue_by_production_method.png		revenue_by_production_method.png
revenue_by_rating.png		revenue_by_rating.png
revenue_by_season.png		revenue_by_season.png
revenue_by_year.png		revenue_by_year.png
shap_after.png		shap_after.png
shap_before.png		shap_before.png
shap_once.png		shap_once.png
streamlit_app.py		streamlit_app.py
streamlit_graphs.py		streamlit_graphs.py
styles.css		styles.css
technical_report.qmd		technical_report.qmd
tutorial.qmd		tutorial.qmd
uv.lock		uv.lock
web_scrape.ipynb		web_scrape.ipynb