This repository was developed for the code and data behind the story: Una constelación de escritoras latinoamericanas (nacidas en el siglo XX).
The analysis uses web scrapping of Wikipedia entries for Latin American women writers and network graph visualization in order to create a web application.
├── app.py # Streamlit app file
├── assets # Resources for the project
│ ├── datacritica
│ ├── imgs
│ ├── imgs_processed
│ ├── mosaics
│ ├── targets
│ └── targets_processed
├── data # Categorized data
│ ├── processed # Cleaned data
│ │ ├── escritoras_wiki.csv
│ │ └── escritores_destacados.csv
│ └── raw # Original data
│ └── escritoras.csv
├── Dockerfile # Commands to build a docker image
├── docs # Explanatory materials
│ ├── data-dictionary.md # Information about the data
│ └── references # Papers, manuals, articles, etc.
├── escritoras_latinas # Python package
│ ├── data # Functions to manipulate data
│ │ ├── analyze.py # Module to analyze data
│ │ ├── export.py # Module to save exports
│ │ ├── load.py # Module to load data and paths
│ │ └── process.py # Module to process data
│ └── utils # Functions to make common patterns
│ └── paths.py # Module to generate relative paths
├── LICENSE # Project license
├── notebooks # Jupyter notebooks
│ ├── 0.0-scrapping-text.ipynb
│ ├── 0.1-scrapping-text.ipynb
│ ├── 0.2-scrapping-images.ipynb
│ ├── 1.0-annotate-data.ipynb
│ ├── 1.1-process-images.ipynb
│ ├── 2.0-visualize-network.ipynb
│ ├── 2.1-visualize-network.ipynb
│ └── 2.2-visualize-donut-chart.ipynb
├── outputs # Exports generated by notebooks
│ ├── figures # Generated graphics, maps, etc.
│ │ └── index.html
| ├── networks # Generated graph network
│ │ └── index.html
│ └── tables # Generated pivot tables
│ ├── LICENSE
│ ├── photomosaics
│ │ ├── photomosaics.py
│ │ ├── run.py
│ │ └── scrape.py
│ ├── README.md
│ └── requirements.txt
├── Pipfile # Project dependencies
├── Pipfile.lock # Specific versions of packages on Pipfile
├── README.md # Top-level README for this project
├── README-ES.md # README in Spanish
├── requirements.txt # Project dependencies
├── setup.py # Import project as a python module
└── style.css # Styles for streamlit app
This project is released under MIT License.
This repository was generated with cookiecutter using a data-journalism template for python.