Metadata-Version: 1.1
Name: pandaSDMX
Version: 0.2.1
Summary: A Python- and pandas-powered client for Statistical Data and Metadata eXchange
Home-page: https://github.com/dr-leo/pandasdmx
Author: Dr. Leo
Author-email: fhaxbox66@gmail.com
License: UNKNOWN
Description: =============
        pandaSDMX
        =============
        
        
        
        
        pandaSDMX is an Apache 2.0-licensed `Python <http://www.python.org>`_ 
        package aimed at becoming the 
        most intuitive and versatile tool to retrieve and acquire statistical data and metadata
        disseminated in `SDMX <http://www.sdmx.org>`_ format. 
        It should work with all
        SDMX data providers supporting SDMX 2.1. Currently,
        this is tested for the European statistics office (Eurostat),
        and the European Central Bank (ECB) each providing hundreds of
        thousands of indicators. 
        
        While pandaSDMX is extensible to 
        cater any output format, it currently supports only `pandas <http://pandas.pydata.org>`_, the gold-standard 
        of data analysis in Python. But from pandas you can export your data to Excel and friends. 
        
        Main features
        ---------------------
        
        * intuitive API inspired by `requests <https://pypi.python.org/pypi/requests/>`_  
        * support for many SDMX features including
        
          - generic datasets
          - data structure definitions, codelists and concept schemes
          - dataflow definitions
          - categorisations and category schemes
        
        * pythonic representation of the SDMX information model  
        * find dataflows by name or description in multiple languages if available
        * read and write files including zip archives for offline use
        * writer transforming SDMX generic datasets into multi-indexed pandas DataFrames or Series of observations and attributes 
        * extensible through custom readers and writers for alternative input and output formats of data and metadata
        
        Example
        ---------
        
        
        
            >>> from pandasdmx import Request
            >>> # Get annual unemployment data from Eurostat
            >>> une_resp = Request('ESTAT').get(resource_type = 'data', resource_id = 'une_rt_a')
            >>> # From the received dataset, select the time series on Greece, Ireland and Spain, and write them to a pandas DataFrame
            >>> une_df = une_resp.write(s for s in une_resp.msg.data.series if s.key.GEO in ['EL', 'ES', 'IE'])
            >>> # Explore the DataFrame
            >>> une_df.columns.names
            >>> une_df.columns.levels[0:2]
            >>> une_df.loc[:'2006', ('TOTAL', 'T')]
        
        
        pandaSDMX Links
        -------------------------------
        
        * `Download the latest stable version from the Python package index <https://pypi.python.org/pypi/pandaSDMX>`_
        * `Documentation <http://pandasdmx.readthedocs.org>`_
        * `Mailing list <https://groups.google.com/forum/?hl=en#!forum/sdmx-python>`_  
        * `github <https://github.com/dr-leo/pandaSDMX>`_
         
          
          
        Recent changes 
        ========================
        
        Version 0.2.1 (2015-04-22)
        ----------------------------------
        
        * API: add support for zip archives received from an SDMX server. 
          This is common for large datasets from Eurostat
        * incidentally get a remote resource if the footer of a received message
          specifies an URL. This pattern is common for large datasets from Eurostat.
        * allow passing a file-like object to api.Request.get() 
        * enhance documentation
        * make pandas writer parse more time period formats and increase its performance  
          
        Version 0.2.0 (2015-04-13)
        ------------------------------------
        
        
        This version is a quantum leap. The whole project has been redesigned and rewritten from
        scratch to provide robust support for many SDMX features. The new architecture is centered around
        a pythonic representation of the SDMX information model. It is extensible through readers and writers
        for alternative input and output formats. 
        Export to pandas has been dramatically improved. Sphinx documentation
        has been added.
        
        v0.1 (2014-09)
        ----------------
        
        Initial release
        
         
        
        
        
Platform: UNKNOWN
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Financial and Insurance Industry
Classifier: Development Status :: 4 - Beta
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Provides: pandasdmx
