Skip to main content

Prepare data for LexImpact

Project description

LexImpact Prepare Data

Ce projet regroupe les scripts permettant de préparer les données des différents projets Leximpact.

Schéma complet de préparation et d'utilisation des données

LexImpact Pipeline

Le pipeline prepare-data est donc le suivant :

Input: erfs_flat_2018.h5

01_db_reduce.ipynb

Objectif: Réduit le nombre de variables dans la base

Output: 01_erfs_reduced_2018.h5

02_db_enlarge.ipynb

Objectif: Ajoute des gens fictifs dans la base pour pouvoir calibrer

Output: 02_erfs_enlarged_2018.h5

03_db_add_rfr.ipynb

Input : CalibPote-2018-revkire.json

Objectifs:

  • Calculer le RFR dans OpenFisca
  • Calibrer le RFR ERFS_2018 sur POTE_2018

Output: 03_erfs_rfr_2018.h5

04_db_add_var

0403_db_add_var_copules.ipynb

0401_db_add_var_copules-algo_monte-carlo.ipynb

0402_db_add_var_copules-validate.ipynb

Input : ExportCopule-2018-variable.json

Objectif: Ajoute les variables issues de POTE 2018 dans la base ERFS 2018

Output: 04_erfs_var_copules_2018.h5

05_db_calib_var_copules.ipynb

Input : CalibPote-2019-variable.json

Objectifs:

  • Vieillit la base ERFS_2018 vers 2019 (nos données les plus récentes) : inflation économique et inflation des foyers
  • Calibre chacune des variables issues de POTE sur POTE 2019

Output: 05_erfs_calibrated_ff_2018_to_2019.h5

06_db_aging_final.ipynb

Objectifs:

  • Vieillit la base ERFS_2019 vers 2021 (année voulue pour les calculs) : inflation économique et inflation des foyers
  • Bruitage statistique de la base pour anonymisation

Output: 06_erfs_ff_2018_aged_2021.h5

How to contribute

Please see the contributing page.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

leximpact_prepare_data-0.0.5.tar.gz (50.4 kB view details)

Uploaded Source

Built Distribution

leximpact_prepare_data-0.0.5-py3-none-any.whl (54.3 kB view details)

Uploaded Python 3

File details

Details for the file leximpact_prepare_data-0.0.5.tar.gz.

File metadata

  • Download URL: leximpact_prepare_data-0.0.5.tar.gz
  • Upload date:
  • Size: 50.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/33.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.63.0 importlib-metadata/4.11.2 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.8.12

File hashes

Hashes for leximpact_prepare_data-0.0.5.tar.gz
Algorithm Hash digest
SHA256 49ffe7eddce2918a0881136da2003e720f1598369d502d3b1a43d3d6105c09ba
MD5 56341e2b0dcc543bdc53139696ac129f
BLAKE2b-256 ee6ace4a66b4e6f9f5b80f40eba7aa6ca3d45f688cc7ab07627e38e561f11f92

See more details on using hashes here.

File details

Details for the file leximpact_prepare_data-0.0.5-py3-none-any.whl.

File metadata

  • Download URL: leximpact_prepare_data-0.0.5-py3-none-any.whl
  • Upload date:
  • Size: 54.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/33.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.63.0 importlib-metadata/4.11.2 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.8.12

File hashes

Hashes for leximpact_prepare_data-0.0.5-py3-none-any.whl
Algorithm Hash digest
SHA256 7f0d9feb6973fddf55858a8846c14cdecfd13d825d986632164e244190bbbd6a
MD5 ea5c094f858fd7cd1776d385a74b7db7
BLAKE2b-256 f673499e2178f38d52c65c3f60a4e130e8f6f83106987ade486bbe99bf7e66f2

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page