R Programming in Data Science: Dates and Times

Learn how to format, compare, calculate, manage, and troubleshoot dates and times using R-based tools.

Introduction

• Calculating times and dates with R
• Course organization

1. Why Are Dates and Times in R Confusing?

• Typical date calculations
• How dates and times are stored in R
• Choose the right date and time tool

2. Dates and Times in Base R

• The base R "Date" class
• Use formatters to recognize dates in character strings
• Dealing with time zones and daylight savings time
• Use operators to compare date objects
• Adding and subtracting dates and times
• Create sequences of dates, cut dates, and round dates
• Extract parts of a date
• Presenting formatted dates and times
• Use read.csv() to import CSV date information

3. Lubridate and the Tidyverse

• Advantages of the Lubridate package
• Parsing date and time with Lubridate
• Getting and setting time components with Lubridate
• Rounding dates and time with Lubridate
• Lubridate math with durations
• Lubridate math with periods
• Lubridate math with intervals
• Time zones with Lubridate

4. Dates and Times for Business and Finance

• The busdater package
• The BusinessDuration package
• The fmdates package

5. Working with Time-Series Data

• Time-series data
• The base R ts class
• The zoo package
• The xts package
• The tsibble and tibbletime packages
• Time-series rolling statistics
• Time-series graphics
• The timelineR package
• The timelineS package
• The CRAN task view for time-series analysis

6. Specialized Date and Time Packages

• The anytime package
• The hms package
• The mondate package
• The datetime package
• The datetimeutils package
• The padr package

Conclusion

• Next steps