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Merge pull request pandas-dev#10455 from cpcloud/odo-eco
Add odo to ecosystem docs
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doc/source/ecosystem.rst

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@@ -132,19 +132,19 @@ Pandas DataFrames with timeseries indexes.
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`pydatastream <https://github.com/vfilimonov/pydatastream>`_
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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PyDatastream is a Python interface to the
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PyDatastream is a Python interface to the
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`Thomson Dataworks Enterprise (DWE/Datastream) <http://dataworks.thomson.com/Dataworks/Enterprise/1.0/>`__
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SOAP API to return indexed Pandas DataFrames or Panels with financial data.
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SOAP API to return indexed Pandas DataFrames or Panels with financial data.
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This package requires valid credentials for this API (non free).
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`pandaSDMX <http://pandasdmx.readthedocs.org>`_
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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pandaSDMX is an extensible library to retrieve and acquire statistical data
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and metadata disseminated in
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`SDMX <http://www.sdmx.org>`_ 2.1. This standard is currently supported by
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pandaSDMX is an extensible library to retrieve and acquire statistical data
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and metadata disseminated in
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`SDMX <http://www.sdmx.org>`_ 2.1. This standard is currently supported by
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the European statistics office (Eurostat)
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and the European Central Bank (ECB). Datasets may be returned as pandas Series
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or multi-indexed DataFrames.
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and the European Central Bank (ECB). Datasets may be returned as pandas Series
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or multi-indexed DataFrames.
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`fredapi <https://github.com/mortada/fredapi>`_
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
@@ -183,8 +183,16 @@ Out-of-core
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-------------
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`Blaze <http://blaze.pydata.org/>`__
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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Blaze provides a standard API for doing computations with various
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in-memory and on-disk backends: NumPy, Pandas, SQLAlchemy, MongoDB, PyTables,
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PySpark.
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`Odo <http://odo.pydata.org>`__
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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Odo provides a uniform API for moving data between different formats. It uses
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pandas own ``read_csv`` for CSV IO and leverages many existing packages such as
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PyTables, h5py, and pymongo to move data between non pandas formats. Its graph
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based approach is also extensible by end users for custom formats that may be
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too specific for the core of odo.

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