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reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["data","economy","python","uruguay"],"created_at":"2026-01-17T04:47:12.850Z","updated_at":"2026-01-17T04:47:12.947Z","avatar_url":"https://github.com/rxavier.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003cimg src=\"https://i.imgur.com/o6cxmaP.jpg\" width=400 style=\"margin-bottom:60px;\"\u003e\n\n  \u003ca href=\"https://www.python.org/downloads/release/python-310/\"\u003e\u003cimg src=\"https://img.shields.io/pypi/pyversions/econuy\"\u003e\u003c/a\u003e\n  \u003ca href=\"https://img.shields.io/pypi/l/econuy\"\u003e\u003cimg src=\"https://img.shields.io/pypi/l/econuy\"\u003e\u003c/a\u003e\n  \u003ca href=\"https://pypi.org/project/econuy/\"\u003e\u003cimg src=\"https://img.shields.io/pypi/v/econuy\"\u003e\u003c/a\u003e\n  \u003ca href=\"https://econuy.readthedocs.io/en/latest/?badge=latest\"\u003e\u003cimg src=\"https://readthedocs.org/projects/econuy/badge/?version=latest\"\u003e\u003c/a\u003e\n\n# Overview\n\nThis project simplifies gathering and processing of Uruguayan economic statistics. Data is retrieved from (mostly) government sources, processed into a familiar tabular format, tagged with useful metadata and can be transformed in several ways (converting to dollars, calculating rolling averages, resampling to other frequencies, etc.).\n\nIf [this screenshot](https://i.imgur.com/Ku5OR0y.jpg) gives you anxiety, this package should be of interest.\n\nA webapp with a limited but interactive version of econuy is available at [econ.uy](https://econ.uy). Check out the [repo](https://github.com/rxavier/econuy-web) as well.\n\nThe most basic econuy workflow goes like this:\n\n```python\nfrom econuy import load_dataset, load_datasets_parallel\n\ndata1 = load_dataset(\"cpi\")\n```\n\n# Installation\n\n* PyPI:\n\n```bash\npip install econuy\n```\n\n* Git:\n\n```bash\ngit clone https://github.com/rxavier/econuy.git\ncd econuy\npython setup.py install\n```\n\n# Usage\n\n**[Full API documentation available at RTD](https://econuy.readthedocs.io/en/latest/api.html)**\n\n### Cache directory\n\neconuy saves and reads data to a directory which by default is at the system `home / .cache / econuy`. This can be modified for all data loading by setting `ECONUY_DATA_DIR` or directly in `load_dataset(data_dir=...)`.\n\n### Dataset load branching\n\n1. Check that the dataset exists in the `REGISTRY`.\n2. Cache check:\n  - If `skip_cache=True`, **download dataset**\n  - If `skip_cache=False` (default):\n    - Check whether the dataset exists in the cache.\n      - If it exists:\n        - Recency check:\n          - If it was created in the last day, **return existing dataset**.\n          - If it was created prior to the last day and `skip_update=False`, **download dataset**.\n          - If it was created prior to the last day and `skip_update=True`, **return existing dataset**.\n      - If it does not exist, **download dataset**\n3. If the dataset was downloaded, try to update the cache:\n- Validation:\n  - If `force_overwrite=True`, **overwrite dataset**.\n  - If `force_overwrite=False` (default):\n    - If the new dataset is similar to the cached dataset, **overwrite dataset**.\n    - If the new dataset is not similar to the cached dataset, **do not overwrite dataset**.\n\n### Loading and transforming data\n\n```python\nfrom econuy import load_dataset, load_datasets_parallel\n\n\n# load a single dataset\ndata1 = load_dataset(\"cpi\")\n\n# load a single dataset and chain transformations\ndata2 = (\n    load_dataset(\"fiscal_balance_nonfinancial_public_sector\")\n    .select(names=\"Ingresos: SPNF\")\n    .resample(\"QE-DEC\", \"sum\")\n    .decompose(method=\"x13\", component=\"t-c\")\n    .filter(start_date=\"2014-01-01\")\n    )\n```\nThis returns a `Dataset` object, which contains a `Metadata` object.\n\nYou can also load multiple datasets fast:\n```python\n# load multiple datasets using threads or processes\ndata3 = load_datasets_parallel([\"nxr_monthly\", \"ppi\"])\n```\n\n### Finding datasets\n\n```python\nfrom econuy.utils.operations import REGISTRY\n\n\nREGISTRY.list_available()\nREGISTRY.list_by_area(\"activity\")\n```\n### Dataset metadata\n\nDatasets include the following metadata per indicator:\n\n1. Indicator name\n2. Area\n3. Frequency\n4. Currency\n5. Inflation adjustment\n6. Unit\n7. Seasonal adjustment\n8. Type (stock or flow)\n9. Cumulative periods\n\n### Transformation methods\n\n`Dataset` objects have multiple methods to transform their underlying data and update their metadata.\n\n* `resample()` - resample data to a different frequency, taking into account whether data is of stock or flow type.\n* `chg_diff()` - calculate percent changes or differences for same period last year, last period or at annual rate.\n* `decompose()` - seasonally decompose series into trend or seasonally adjusted components.\n* `convert()` - convert to US dollars, constant prices or percent of GDP.\n* `rebase()` - set a period or window as 100, scale rest accordingly\n* `rolling()` - calculate rolling windows, either average or sum.\n\n## External binaries and libraries\n\n### unrar libraries\n\nThe [patool](https://github.com/wummel/patool) package is used in order to access data provided in `.rar` format. This package requires that you have the `unrar` binaries in your system, which in most cases you should already have. You can can get them from [here](https://www.rarlab.com/rar_add.htm) if you don't.\n\n----\n\n# Caveats\n\nThis project is heavily based on getting data from online sources that could change without notice, causing methods that download data to fail. While I try to stay on my toes and fix these quickly, it helps if you create an issue when you find one of these (or even submit a fix!).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frxavier%2Feconuy","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Frxavier%2Feconuy","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frxavier%2Feconuy/lists"}