Resources
This carefully curated collection of resources will help you find packages and learning resources to help you on your R journey.
A Scientist's Guide to R: Step 2.5 - dates & times
A Scientist's Guide to R: Step 2.5 - dates & times is a blog post that provides a guide on how to work with dates and times in R using the lubridate package. It covers topics such as date/time basics, reading dates, time zones, month names, extracting datetime components, custom date formats, date calculations, and planning a behavioural neuroscience experiment. The post aims to help readers handle dates and times effectively in R.
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How (and Why) I came to Use R for Data Analysis and Evaluation
Alberto Espinoza recounts his journey with R for data analysis and evaluation, marking his 10-year experience since first encountering R during his graduate assistantship. Initially clueless about R, he was tasked with assisting and leading statistics labs using R. Despite early challenges and a steep learning curve, he recognized R's power over software like SPSS or Excel. His continued use of R spanned graduate projects, market research, data preparation for Tableau, and Survey Monkey analysis. Espinoza outlines R's advantages: reproducibility, efficiency, clarity, and an extensive package ecosystem, underlining R's significance in his professional growth.
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lubridate
Lubridate makes working with date-time data easier in R. It provides intuitive commands for parsing and manipulating date-times, handles time zones and other quirks, and expands the types of mathematical operations that can be performed with date-time objects. This resource provides an overview of lubridate, installation instructions, a cheatsheet of its features, and information about its code of conduct.
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R for Data Science, Chapter 16: Dates and Times
This chapter in the R for Data Science book provides an introduction to working with dates and times in R. It covers topics such as creating date/times, parsing strings into date/time objects, and working with date/time components. The chapter also introduces the 'lubridate' package, which makes it easier to work with dates and times in R.
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R lubridate: How To Efficiently Work With Dates and Times in R - R programming
Learn how to efficiently work with dates and times in R using the lubridate package. This tutorial provides 15 useful examples to help you master lubridate.
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resouRces
This content encompasses a comprehensive list of R-related educational materials, packages, tutorials, and datasets with projected dates ranging up to the year 2025. It includes various titles that focus on learning R programming, data analysis, data visualization, geospatial mapping, and statistical methods. Significant emphasis is placed on resources for learning R, such as introductions to R, books, courses, and video tutorials. Additionally, specific packages for data wrangling, statistical modeling, and visualization are mentioned, indicating the evolution and specialization of R's ecosystem to cater to diverse data science needs.
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