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Thursday, July 6 • 5:35pm - 5:40pm
Preparing Datetime Data with Padr

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Keywords: Data Preparation, Datetime Data, Tidyverse,
Webpages: https://CRAN.R-project.org/package=padr, https://github.com/edwinth/padr
padr solves two problems that you can be confronted with when preparing datetime data for analysis. First, data is often recorded on too fine a granualarity. For instance, the timestamp registers the moment up to the second, while you want to do the analysis on an hourly level. The thicken function will add a column to a data frame. In conjunction with dplyr, it will allow for quick aggregation to the higher level. Second, when no events take place there are typically no data records generated. This is sensible from a storage perspective, but often unhelpful for analysing the data. In this context the pad function is used. Besides demonstrating these two functions, I will elaborate on the concept of the interval, on which both functions heavily rely.

Speakers
avatar for Edwin Thoen

Edwin Thoen

Data Scientist, Rabobank
I work at the Advanced Data Analytics department of a large bank that supports all departments of the bank with projects that makes the organisation more data-driven. I am especially interested in rare-event prediction, Bayesian analysis, deep learning and a deeper understanding... Read More →



Thursday July 6, 2017 5:35pm - 5:40pm
3.01 Wild Gallery

Attendees (78)