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This is a small project that does a small analysis on data provided by netflix.
To run this project, first install the requirements on requirement.txt by using the pip install -r requirements.txt command.
IMPORTANT: I strongly recommend the use of virtual environments before installing so that to keep organized the dependencies.
The first step is to acquire the netflix information by accessing the following link. Provide the specified information and wait until the Netflix team sends you back your desired information.
Now, you can save the zip file in the following path as follows: data/raw/netflix-report.zip.
Once this is done, we can finally extract the information and generate the report. To do this you can easily run
the pipeline_flow.py file: python pipeline_flow.py
If you want to see the step-by-step execution, refer to that file as well.
This small proyect will allow you to make the following netflix analysis:
Heatmap that is a calendar-like plot to see which months over the course of the profile generation have been the ones the more time was spent.
├── LICENSE
├── Makefile <- Makefile with commands like `make data` or `make train`
├── README.md <- The top-level README for developers using this project.
├── data
│ ├── external <- Data from third party sources.
│ ├── interim <- Intermediate data that has been transformed.
│ ├── processed <- The final, canonical data sets for modeling.
│ └── raw <- The original, immutable data dump.
│
├── docs <- A default Sphinx project; see sphinx-doc.org for details
│
├── notebooks <- Jupyter notebooks.
│
├── references <- Data dictionaries, manuals, and all other explanatory materials.
│
├── reports <- Generated analysis as HTML, PDF, LaTeX, etc.
│ └── figures <- Generated graphics and figures to be used in reporting
│
├── requirements.txt <- The requirements file for reproducing the analysis environment, e.g.
│ generated with `pip freeze > requirements.txt`
│
├── setup.py <- makes project pip installable (pip install -e .) so src can be imported
├── pipeline_flow.py <- Runs most important files to execute the report successfully.
├── src <- Source code for use in this project.
│ ├── __init__.py <- Makes src a Python module
│ │
│ ├── data <- Scripts to download or generate data
│ │ ├── initial_data_unzip_extraction.py
│ │ ├── fetch_information.py
│ │ └── movies_and_series.py
│ │
│ └── visualization <- Scripts to create exploratory and results oriented visualizations
│ │ ├── create_visualizations.py
│ │ └── utils.py
│
└── tox.ini <- tox file with settings for running tox; see tox.readthedocs.io
Project based on the cookiecutter data science project template. #cookiecutterdatascience