ANN: pandaSDMX 0.5 released

[Dr. Leo]

Hi,

I am very pleased to announce the release of pandaSDMX v0.5. It comes
with several new features, API improvements and bug fixes. The big thing
is a new reader module for the latest JSON file format for SDMX data
messages. It depends on json-rw. The new reader and an extended API
allows to access OECD data. However, column selection at request time is
not as easy as with SDMXML, because the SDMXJSON standard does not yet
support structural metadata such as code lists. Hence, validation of
keys (filters by column key) is not supported yet. However, you can well
use 'startPeriod' and other parameter when downloading data from OECD.

So what's new in v0.5?

• new reader module for SDMX JSON data messages
• add OECD as data provider (data messages only)
• pandasdmx.model.Category
is now an iterator over categorised objects. This greatly simplifies
category usage. Besides, categories with the same ID while belonging to
multiple
category schemes are no longer conflated.
Listenende

1.1.2. API changes
Liste mit 2 Einträgen
• Request constructor: make agency ID case-insensitive
• As Category is now an iterator over categorised objects,
Categorisations is no longer considered part of the public API.
Listenende

1.1.3. Bug fixes
Liste mit 2 Einträgen
• sdmxml reader: fix AttributeError in write_source method, thanks to Topas
• correctly distinguish between categories with same ID while belonging
to different category schemes

You can pip-install it or view the much improved docs at
http://pandasdmx.readthedocs.io/.

What it is:

pandaSDMX is an Apache 2.0-licensed
Python
package aimed at becoming the most intuitive and versatile tool to
retrieve and acquire statistical data and metadata disseminated in
SDMX
format. It supports out of the box the SDMX services of the European
statistics office (Eurostat), the European Central Bank (ECB), the
French National
Institute for statistics (INSEE), and the OECD (JSON only). pandaSDMX
can export data and metadata as
pandas
DataFrames, the gold-standard of data analysis in Python. From pandas
you can export data and metadata to Excel, R and friends. As from
version 0.4, pandaSDMX
can export data to many other file formats and database backends via
Odo.

Enjoy!

Leo