Dealing with

Date and Times

Dealing with dates and times in any database or statistics package is always tricky. Working with dates and times in R is no exception. Below are some resources that can help you better understand how R deals with dates and times and

Data Values- Quick- R

Dates are represented as the number of days since 1970-01-01, with negative values for earlier dates.

A Comprehensive Introduction to Handling Date & Time in R

Statistics Globe: Change Format of Dates in R (4 Examples) | How to Display Time Objects | as.Date, class & format (3:56)

DataCamp: R Tutorial: An introduction to dates in R (2:26)

DataDaft: Introduction to R: Dealing With Dates (12:35)

UC Business Analytics R Programming Guide: Dealing with Dates

Real world data are often associated with dates and time; however, dealing with dates accurately can appear to be a complicated task due to the variety in formats and accounting for time-zone differences and leap years. R has a range of functions that allow you to work with dates and times.

R for Data Science: Dates and times

This chapter will show you how to work with dates and times in R. At first glance, dates and times seem simple. You use them all the time in your regular life, and they don’t seem to cause much confusion. However, the more you learn about dates and times, the more complicated they seem to get.

Make Dealing with Dates a Little EasierFunctions to work with date-times and time-spans: fast and user friendly parsing of date-time data, extraction and updating of components of a date-time (years, months, days, hours, minutes, and seconds), algebraic manipulation on date-time and time-span objects. The lubridate package has a consistent and memorable syntax that makes working with dates easy and fun. Parts of the CCTZ source code, released under the Apache 2.0 License, are included in this package. See <https://github.com/google/cctz> for more details.

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