IDEAS home Printed from https://ideas.repec.org/p/kof/wpskof/15-384.html
   My bibliography  Save this paper

timeseriesdb: Manage and Archive Time Series Data in Establishment Statistics with R and PostgreSQL

Author

Abstract

timeseriesdb is an R package which suggests a PostgreSQL database structure to store time series alongside extensive multi-lingual meta information and provides an R database interface including a web based GUI. The timeseriesdb package was designed to handle time series in establishment statistics. Information such as the GDP or data stemming from the aggregation of economic surveys is typically published on a monthly, quarterly or yearly basis. Hence the package is optimized to handle a large amount of dierent time series as opposed to managing a smaller number of high frequency time series such as real time data obtained from measuring devices. The particular focus of timeseriesdb is to help the user nd and extract a particular set of information within a larger set of information. The timeseriesdb package intends to provide the infrastructure for a time series catalog as opposed to handling time series operations on database level. The underlying structure relies on PostgreSQL's hstore data type which allows to store an array of key-value pairs in a single cell. The hstore data type is not only used to reduce the number of records by storing an entire time series in a single record but also to store a record specic amount of multi-lingual meta information items exibly.

Suggested Citation

  • Matthias Bannert, 2015. "timeseriesdb: Manage and Archive Time Series Data in Establishment Statistics with R and PostgreSQL," KOF Working papers 15-384, KOF Swiss Economic Institute, ETH Zurich.
  • Handle: RePEc:kof:wpskof:15-384
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.3929/ethz-a-010480183
    Download Restriction: no

    References listed on IDEAS

    as
    1. B. D. McCullough & H. D. Vinod, 2003. "Verifying the Solution from a Nonlinear Solver: A Case Study," American Economic Review, American Economic Association, vol. 93(3), pages 873-892, June.
    2. Manik L. Shrestha & Marco Marini, 2013. "Quarterly GDP Revisions in G-20 Countries; Evidence from the 2008 Financial Crisis," IMF Working Papers 13/60, International Monetary Fund.
    3. Roger Koenker & Achim Zeileis, 2009. "On reproducible econometric research," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(5), pages 833-847.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Time series; Data management; Relational database; Establishment statistics; Ocial statistics; hstore; NoSQL; Economic data; Reproducible research; R; PostgreSQL;

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:kof:wpskof:15-384. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (). General contact details of provider: http://edirc.repec.org/data/koethch.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.