**pyam**: analysis and visualization of assessment models ========================================================= .. |br| raw:: html
Release v\ |version|. .. image:: https://img.shields.io/pypi/v/pyam-iamc.svg :target: https://pypi.python.org/pypi/pyam-iamc/ .. image:: https://anaconda.org/conda-forge/pyam/badges/version.svg :target: https://anaconda.org/conda-forge/pyam .. image:: https://anaconda.org/conda-forge/pyam/badges/license.svg :target: https://anaconda.org/conda-forge/pyam .. image:: https://zenodo.org/badge/113359260.svg :target: https://zenodo.org/badge/latestdoi/113359260 .. image:: https://anaconda.org/conda-forge/pyam/badges/latest_release_date.svg :target: https://anaconda.org/conda-forge/pyam .. image:: https://circleci.com/gh/IAMconsortium/pyam.svg?style=shield&circle-token=:circle-token :target: https://circleci.com/gh/IAMconsortium/pyam .. image:: https://travis-ci.org/IAMconsortium/pyam.svg?branch=master :target: https://travis-ci.org/IAMconsortium/pyam .. image:: https://ci.appveyor.com/api/projects/status/qd4taojd2vkqoab4/branch/master?svg=true&passingText=passing&failingText=failing&pendingText=pending :target: https://ci.appveyor.com/project/gidden/pyam/branch/master The **pyam** Python package provides a range of diagnostic tools and functions for analyzing and visualizing data from your favorite assessment model(s). The source code for **pyam** is available on `Github`_. .. _`Github`: https://github.com/IAMconsortium/pyam .. _`groups.google.com/d/forum/pyam` : https://groups.google.com/d/forum/pyam Overview -------- Some of the **pyam** features include: - Easily filter and manipulate data in the `IAMC`_ timeseries format - An interface similar in feel and style to `pandas.DataFrame`_ - Advanced visualization and plotting functions. - Diagnostic checks for non-reported variables or timeseries values to analyze and validate scenario data. - Categorization of scenarios according to timeseries data or metadata for further analysis. .. _`IAMC`: https://data.ene.iiasa.ac.at/database .. _`pandas.DataFrame`: https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.html After installing, check out our tutorials or our plotting gallery to get started. Documentation ------------- .. toctree:: :maxdepth: 1 install data tutorials examples/index api .. include:: ../../CONTRIBUTING.rst License ------- :code:`pyam` is available under the open source `Apache License`_. .. _Apache License: http://www.apache.org/licenses/LICENSE-2.0.html