From 4bce854c8ec6d154b2d605c2d1b06f8bb8cd8780 Mon Sep 17 00:00:00 2001 From: Evgeny Pogrebnyak Date: Wed, 1 Sep 2021 22:35:41 +0300 Subject: [PATCH] make matplotlib a development package fixes #23 --- CHANGELOG.md | 0 README.md | 19 ++-- poetry.lock | 220 +++++++++++++++++++++++------------------------ pyproject.toml | 4 +- weo/dataframe.py | 1 - 5 files changed, 121 insertions(+), 123 deletions(-) create mode 100644 CHANGELOG.md diff --git a/CHANGELOG.md b/CHANGELOG.md new file mode 100644 index 0000000..e69de29 diff --git a/README.md b/README.md index bf59852..8d546c6 100644 --- a/README.md +++ b/README.md @@ -5,6 +5,7 @@ [![Downloads](https://pepy.tech/badge/weo/week)](https://pepy.tech/project/weo/week) This is a Python client to download [IMF World Economic Outlook Report][weo] dataset as [pandas](https://pandas.pydata.org/) dataframes by release dates. You can explore: + - single country macroeconomic data and forecast, - macro variables across countries for a given year, - country-year panel for single macro variable. @@ -40,22 +41,23 @@ You can access WEO releases starting October 2007 with this client. WEO is norma Release is referenced by number (`1` or `2`) or by month (`'Apr'` or `'Oct'`, and `'Sep'` in 2011). -Your can list all years and releases available for download with `weo.all_releases()`. Combine it to create local dataset of WEO vintages from 2007 to present: +Your can list all years and releases available for download with `weo.all_releases()`. +Combine it to create local dataset of WEO vintages from 2007 to present: ```python -from weo import all_releases +import weo -for (year, release) in all_releases(): +for (year, release) in weo.all_releases(): weo.download(year, release, directory='weo_data') ``` -Note that folder 'weo_data' must exist for this script to run. +Note that folder `weo_data` must exist for this script to run, +it will not be created automatically. ## Step 2. Inspect data -Use `WEO` class to view and extract data. `WEO` is a wrapper around a pandas dataframe that ensures proper data import and easier access and slicing of data. - +Use `WEO` class to view and extract data. `WEO` is a wrapper around a pandas dataframe that ensures proper data import and easier access and slicing of data across time-country-variable dimensions. Try code below: @@ -86,6 +88,7 @@ w.iso_code3("Netherlands") # 'NLD' ``` The dataset is year-country-variable-value cube, you can fix any dimension to get a table. + ```python w.get("General government gross debt", "Percent of GDP") @@ -128,11 +131,13 @@ ts1 = fetch_series_by_api_link("https://api.db.nomics.world/v22/" "?observations=1") ``` -2\. Similar dataset, not updated since 2018, but with earlier years: https://github.com/datasets/imf-weo +2\. Similar dataset, not updated since 2018, but with earlier years than `weo-reader`: +https://github.com/datasets/imf-weo ## Development notes - You can download the WEO file in command line with `curl` command: + ``` curl -o weo.csv https://www.imf.org/-/media/Files/Publications/WEO/WEO-Database/2020/02/WEOOct2020all.xls ``` diff --git a/poetry.lock b/poetry.lock index 6b0d966..7bc6e35 100644 --- a/poetry.lock +++ b/poetry.lock @@ -191,7 +191,7 @@ python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*" name = "cycler" version = "0.10.0" description = "Composable style cycles" -category = "main" +category = "dev" optional = false python-versions = "*" @@ -268,22 +268,6 @@ category = "dev" optional = false python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" -[[package]] -name = "importlib-metadata" -version = "3.3.0" -description = "Read metadata from Python packages" -category = "dev" -optional = false -python-versions = ">=3.6" - -[package.dependencies] 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