Getting and setting dates and times with

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# Getting and setting dates and times with

## RStudio Instructor Exam

### Dr. Laurie Baker

### `r Sys.Date()`

---

# You

* Are familiar with R, Rmarkdown notebooks, and dplyr.

* Are new to working with dates and times in R

* Want to learn easy ways to extract information from dates and times.

<img src="images/lubridate.png" width="350" style="display: block; margin: auto;" />
Artwork by @allison_horst

---
# Learning objectives

* Learn to create date, time, and date-time objects with **helpers** (e.g. ymd, dmy_hms).

* Learn to extract components (e.g. year, month, wday) from date-time objects with **accessors**.

* Learn how to change time zones with `with_tz`

---
# Getting started

* For this adventure you'll need the `tidyverse` meta-package, `lubridate` (part of the tidyverse). We will also need the package `readxl`

```r
#install.packages("tidyverse")
#install.packages("lubridate")
#install.packages("readxl")

library(tidyverse)
library(lubridate)
library(readxl)
```

* And we'll be working with the dataframe `training_schedule.xlsx` which you might find familiar...

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# What makes dates and times so challenging?

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# Physical phenomena

Elf Pavlik / CC0 https://commons.wikimedia.org/wiki/File:Blue_Marble_rotating.gif

???

* Rotation of the Earth
  * Earth's orbit around the sun
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# Geopolitical phenomena

* Months, time zones, leap years, and DST
  * The Tzolk'in Mayan calendar had 260 days!
  
![\Guardian News Headline](images/eu_guardian.png)

---

# Dates and times in R

Type can be
1. A date (`<date>`)
2. A time (`<time>`)
3. A date-time (`<dttm>`) a date plus time.

Can be built from

* Strings: 09/10/2010
* Existing date/time objects
* Date-time components (year = 1990, month = 12, day = 4)

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# Parsing dates and times using helpers

Artwork by @allison_horst

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# Parsing dates and times using helpers

* Identify the order in which the year (`y`), month (`m`), and day (`d`) appears in your dates.

* Let's look at October 2, 2020.

```r
ymd("20201002")
```

```
## [1] "2020-10-02"
```

```r
___("10-02-2020")
```

---
# Parsing dates and times using helpers

* For date-times, we can add an underscore and one of more `h` `m` and `s` to our parsing function.

* What helper would we use for October 3, 2020 if it comes in this format?

```r
____("03/10/20 15:32:05")
```

Times are supplied in `UTC`, the coordinated universal time, unless we specify a time zone (tz).

---
# A tale of 5 time zones...

Let's take a look at our training schedule

```
## # A tibble: 6 x 5
##   date                start_time end_time topic                   type        
##   <dttm>                   <dbl>    <dbl> <chr>                   <chr>       
## 1 2020-09-18 00:00:00         14       16 Introduction to R       workshop    
## 2 2020-10-02 00:00:00         14       17 Data Wrangling in R     training    
## 3 2020-10-09 00:00:00         14       16 Data Wrangling in R     workshop    
## 4 2020-10-16 00:00:00         14       17 Data Visualisation in R training    
## 5 2020-10-23 00:00:00         14       16 Data Visualisation in R workshop    
## 6 2020-10-30 00:00:00         14       16 Show and Tell           presentation
```

```r
path <- here::here("../data","training_schedule.xlsx")
schedule <- read_xlsx(path)

schedule <- schedule %>%
              mutate(date = as_datetime(date))

head(schedule)
```

---

# Getting components

We can pull out individual parts of a date with the **accessor** functions:

- year, month, day
- mday, yday, wday
- hour, minute, second

```r
schedule %>%
  mutate(year = year(date)) %>%
  head()
```

```
## # A tibble: 6 x 6
##   date                start_time end_time topic                 type        year
##   <dttm>                   <dbl>    <dbl> <chr>                 <chr>      <dbl>
## 1 2020-09-18 00:00:00         14       16 Introduction to R     workshop    2020
## 2 2020-10-02 00:00:00         14       17 Data Wrangling in R   training    2020
## 3 2020-10-09 00:00:00         14       16 Data Wrangling in R   workshop    2020
## 4 2020-10-16 00:00:00         14       17 Data Visualisation i~ training    2020
## 5 2020-10-23 00:00:00         14       16 Data Visualisation i~ workshop    2020
## 6 2020-10-30 00:00:00         14       16 Show and Tell         presentat~  2020
```
---

# Getting components

Fill in the blank to determine what day of the week our courses fall on

```r
schedule %>%
  mutate(weekday = ____(date)) 
```

We can change the arguments label = TRUE, abbr = FALSE.

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# Creating a date time from date-time components

We can create a date-time by combining our date and start-time

```r
schedule <- schedule %>%
              mutate(
                start_date_time = make_datetime(
                  year = year(date), 
                  month = month(date), 
                  day = day(date), 
                  hour = start_time, 
                  tz = "Europe/London")
                )
```

---
# Changing timezones with `with_tz`

But what is the time in Jamaica?

```r
schedule <- schedule %>%
              mutate(start_date_time_jam = with_tz(
                start_date_time, 
                tz = "America/Jamaica"))
```

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![\Concept Map](images/concept_map.png)

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# Thanks!

Slides created via the R package [**xaringan**](https://github.com/yihui/xaringan).

The chakra comes from [remark.js](https://remarkjs.com), [**knitr**](http://yihui.name/knitr), and [R Markdown](https://rmarkdown.rstudio.com).

The gorgeous artwork comes from [@allison_horst](https://github.com/allisonhorst/stats-illustrations)

---
# Having some fun

* Try changing the country to Belize

Hint: Run `OlsonNames(tzdir = NULL)` to find the correct time zone

```r
OlsonNames(tzdir = NULL)

schedule <- schedule %>%
              mutate(start_date_time___ = with_tz(
                start_date_time, 
                tz = "_____"))
```

Fill in the blanks to find out what time the delegates from Belize get to sleep in?

```r
schedule %>%
  filter(______(start_date_time____) > 7) %>%
  select(start_date_time_bz)
```