Package: evdsts
evdstsThe Purposeevdstsis a Python implementation for retrieving and transforming macroeconomic time series data fromThe Central Bank of Republic of TürkiyeElectronic Data Delivery System(EDDS)API.evdstsis designed for making both data retrieving and also time series analysis easy thanks to its
time series analysis ready outputs and other useful transformations.The Overviewevdstsis mainly designed for preparing the time series analysis ready datasets from the data
retrieved fromEDDS.evdstsboth makes the data retrieving easy and also allows you to start
working on data instantly with its advanced features that gives you complete control over the
retrieved data.evdstsis consisted of two important classes:The Connector: Responsible for processes such as; connecting to EDDS, data retrieving, data
renaming, etc.The Transformator: Works co-integrated with theConnectorand responsible for making some
useful transformations which can provide you a preliminary undestanding about the series you're
dealing with.Some key features ofevdstsare listed below:evdstscan perform instant transformations on retrieved data thanks to itsTransformatorclass.
The Transformator is designed to co-work withConnectorand perform a set of frequently used
transformations on retrieved data such as; z-score calculation, dummy series creation, outliers
detection, differentiation and others.You can search series by keywords inevdstswithout any need for visiting EDDS website to find
series definitions you would like to retrieve from the service. Searches are done locally and gives
you instant results.evdstsensures that all returned data can be used for mathematical operations instantly. That
guarantees no anystringtype is returned for a data type which actually represents adatetime,floatorinttype.All retrieved data are converted to real time series automatically (optional, can be disabled)Requesting data from the API doesn't require remembering the complex series names definitions of
the original EDDS database to retrieve them.evdstsallows you to assign meaningful names to
the series such as;cppi,ir,gdpandusdtry, and these assigned names can be used when
retrieving data from the EDDS later on. User assigned names are called reference names, and they
are permanent once they are assigned to series unless they're changed or deleted. Additionally,
current reference names in a project can be transferred to new projects easily.All parameters belong to transformation and aggregation functions and frequencies are renamed in
a meaningful manner likedaily,quarterly,percent,diff,max, etc. and these definitions
are used as parameters for retrieving data from the API service. Therefore, there is no need to know
original API's complex parameter definitions for transformation or aggregation functions or time
series frequencies anymore.evdstsdetects many kinds of errors and warns you before a connection request is made.
This allows you to know why the data would not be able to be retrieved with provided parameters, or,
about emerged ambiguities which are arisen from the provided parameter sets.evdstsallows you to make useful data transformations such as higher order differentiations
or log-returns that are originally not supported by the API, but is used for time series analysis
frequently.All types of retrieved data can be returned inDataFrame,JSONordicttypes optionally.All retrieved data can be written on disk inJSON,CSVandXLSformats in order to store and
use them later, or in other softwares such as R, EViews, SAS or RATS.All functions and class methods are fully annotated and you can get peak hints for everything you
need to use while working with Spyder IDE, Pycharm, VS Code or Jupyter.All types in source code are annotated (and commented) to make working easy on source code for
developers.DocumentationPlease seeTHE USER MANUALfor detailed explanations about how to get an API key from the EDDS and useevdstsExamplesPlease download theJupyter Notebook Applicationthat covers the main use cases ofevdsts,
or alternatively open it onGoogle Colabby clicking theOpen in Colablink above.Dependenciesevdstsis aPython 3only project and depends on below packages:cpython >= 3.6.15 (or equivalent PyPy distribution)pandas >= 0.25.3requests >= 2.12.5Additional Requirementsopenpyxlis required if you would like to write data on disk
in MS Excel format. openpyxl is not required if you don't think working with MS Excel files.InstallationStable version ofevdstsis available on GitHub, PyPI and conda-forge and can be installed
following one of the below ways:PyPIpip install evdstsGitHubpip install git+https://github.com/syncoding/evdsts.gitCondaconda install evdsts -c conda-forgeSource CodeGitHubChangelogChangelogLicenseMITContact