A data analysis about my consumption of movies, operas, books and concerts.
The jupyter notebook is based on Python 3.7 and relies mainly on pandas, numpy and datetime for the data preparation. For plotting and visualizing I used mainly Seaborn and Altair.
In 2016, I started to write down every movie I saw, with who, where,the category and a my own rating. I also added movies and operas that I remembered from the past years, so my diary has now over 600 entries since 2002.
Learning Python, I needed a "passion project" so I started to visualize my consumption of movies and operas. This way, I have learned a lot about pandas and seaborn.
As I am also analyzing whith whom I watch which movie, I excluded this information and these plots from the "public" version. However I am working on a dictionary to give my friends some nice pseudonyms.
In the meantime, I just would like to show you some of my results, maybe you find them interesting and have ideas about their future development.
I am currently working on an implementation of IMDBPY to get more information about my movies from IMDB, work out a movie recomendation system and compare my own rating with IMDB's rating.
- Kulturprojekt-public.ipynb: My work up to now including all plots.
Every contribution or idea is welcome.
First I would like to thank alberanid for his IMDB library: https://github.com/alberanid/imdbpy/blob/master/docs/usage/quickstart.rst Also thanks to the developers of pandas, numpy, matplotlib, seaborn, altair.