Analisis de Open Data del Poder Judicial

a9b115a4db
fix: dvc remote
7 months ago
d0100af50e
actualizacion dvc
7 months ago
856047939f
creacion proyecto
9 months ago
856047939f
creacion proyecto
9 months ago
4d74798007
upd: una cuicada en los nombres de los feather
7 months ago
856047939f
creacion proyecto
9 months ago
36c4a8ab2b
wip: clickfy code carga_limpieza
7 months ago
src
cc670b90e3
wip: Creacion de dvc.yaml nuevamente
7 months ago
856047939f
creacion proyecto
9 months ago
e5e103a814
update DVC
9 months ago
8da8ebfd65
wip: clickify
7 months ago
856047939f
creacion proyecto
9 months ago
856047939f
creacion proyecto
9 months ago
8da8ebfd65
wip: clickify
7 months ago
d0100af50e
actualizacion dvc
7 months ago
d0100af50e
actualizacion dvc
7 months ago
856047939f
creacion proyecto
9 months ago
8da8ebfd65
wip: clickify
7 months ago
856047939f
creacion proyecto
9 months ago
856047939f
creacion proyecto
9 months ago
Data Pipeline
Legend
DVC Managed File
Git Managed File
Metric
Stage File
External File

README.md

Analisis OpenData Pjud

Este proyecto busca analizar los datos abiertos del Poder Judicial de Chile.

Project Organization

├── 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
│
├── models             <- Trained and serialized models, model predictions, or model summaries
│
├── notebooks          <- Jupyter notebooks. Naming convention is a number (for ordering),
│                         the creator's initials, and a short `-` delimited description, e.g.
│                         `1.0-jqp-initial-data-exploration`.
│
├── 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
├── src                <- Source code for use in this project.
│   ├── __init__.py    <- Makes src a Python module
│   │
│   ├── data           <- Scripts to download or generate data
│   │   └── make_dataset.py
│   │
│   ├── features       <- Scripts to turn raw data into features for modeling
│   │   └── build_features.py
│   │
│   ├── models         <- Scripts to train models and then use trained models to make
│   │   │                 predictions
│   │   ├── predict_model.py
│   │   └── train_model.py
│   │
│   └── visualization  <- Scripts to create exploratory and results oriented visualizations
│       └── visualize.py
│
└── tox.ini            <- tox file with settings for running tox; see tox.readthedocs.io

Project based on the cookiecutter data science project template. #cookiecutterdatascience

Instalación

pip install -e .