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In this tutorial, we will learn to handle date & time in R. We will start off by learning howto get current date & time before moving on to understand how R handles date/time internallyand the different classes such as Date
& POSIXct/lt
. We will spend some timeexploring time zones, daylight savings and ISO 8001 standard for representing date/time.We will look at all the weird formats in which date/time come in real world and learn toparse them using conversion specifications. After this, we will also learn how to handle date/timecolumns while reading external data into R. We will learn to extract and update different date/timecomponents such as year, month, day, hour, minute etc., create sequence of dates in different waysand explore intervals, durations and period. We will end the tutorial by learning how to round/rollbackdates. Throughout the tutorial, we will also work through a case study to better understand theconcepts we learn. Happy learning!
Table of Contents
Resources
Below are the links to all the resources related to this tutorial:
Introduction
Date
Let us begin by looking at the current date and time. Sys.Date()
and today()
will return the current date.
Sys.Date()## [1] "2020-04-17"lubridate::today()## [1] "2020-04-17"
Time
Sys.time()
and now()
return the date, time and the timezone. In now()
, we can specify the timezone using the tzone
argument.
Sys.time()## [1] "2020-04-17 17:37:21 IST"lubridate::now()## [1] "2020-04-17 17:37:21 IST"lubridate::now(tzone = "UTC")## [1] "2020-04-17 12:07:21 UTC"
AM or PM?
am()
and pm()
allow us to check whether date/time occur in the AM
or PM
? They return a logical value i.e.TRUE
or FALSE
lubridate::am(now())## [1] FALSElubridate::pm(now())## [1] TRUE
Leap Year
We can also check if the current year is a leap year using leap_year()
.
Sys.Date()## [1] "2020-04-17"lubridate::leap_year(Sys.Date())## [1] TRUE
Summary
Function | Description |
---|---|
Sys.Date() | Current Date |
lubridate::today() | Current Date |
Sys.time() | Current Time |
lubridate::now() | Current Time |
lubridate::am() | Whether time occurs in am? |
lubridate::pm() | Whether time occurs in pm? |
lubridate::leap_year() | Check if the year is a leap year? |
Your Turn
- get current date
- get current time
- check whether the time occurs in am or pm?
- check whether the following years were leap years
- 2018
- 2016
Case Study
Throughout the tutorial, we will work on a case study related to transactions of an imaginary trading company. The data set includes information about invoice and payment dates.
Data
transact <- readr::read_csv('https://raw.githubusercontent.com/rsquaredacademy/datasets/master/transact.csv')## # A tibble: 2,466 x 3## Invoice Due Payment ## <date> <date> <date> ## 1 2013-01-02 2013-02-01 2013-01-15## 2 2013-01-26 2013-02-25 2013-03-03## 3 2013-07-03 2013-08-02 2013-07-08## 4 2013-02-10 2013-03-12 2013-03-17## 5 2012-10-25 2012-11-24 2012-11-28## 6 2012-01-27 2012-02-26 2012-02-22## 7 2013-08-13 2013-09-12 2013-09-09## 8 2012-12-16 2013-01-15 2013-01-12## 9 2012-05-14 2012-06-13 2012-07-01## 10 2013-07-01 2013-07-31 2013-07-26## # ... with 2,456 more rows
We will explore more about reading data sets with date/time columns after learning how toparse date/time. We have shared the code for reading the data sets used in the practicequestions both in the Learning Management System as well as in our GitHub repo.
Data Dictionary
The data set has 3 columns. All the dates are in the format (yyyy-mm-dd).
Column | Description |
---|---|
Invoice | Invoice Date |
Due | Due Date |
Payment | Payment Date |
In the case study, we will try to answer a few questions we have about the transact
data.
- extract date, month and year from Due
- compute the number of days to settle invoice
- compute days over due
- check if due year is a leap year
- check when due day in february is 29, whether it is a leap year
- how many invoices were settled within due date
- how many invoices are due in each quarter
Date & Time Classes
In this section, we will look at two things. First, how to create date/timedata in R, and second, how to convert other data types to date/time. Let usbegin by creating the release date of R 3.6.2.
release_date <- 2019-12-12release_date## [1] 1995
Okay! Why do we see 1995
when we call the date? What is happening here? Let usquickly check the data type of release_date
.
class(release_date)## [1] "numeric"
The data type is numeric
i.e.R has subtracted 12
twice from 2019
toreturn 1995
. Clearly, the above method is not the right way to storedate/time. Let us see if we can get some hints from the built-in R functions weused in the previous section. If you observe the output, all of them returneddate/time wrapped in quotes. Hmmm… let us wrap our date in quotes and see whathappens.
release_date <- "2019-12-12"release_date## [1] "2019-12-12"
Alright, now R does not do any arithmetic and returns the date as we specified.Great! Is this the right format to store date/time then? No.Why? What is the problemif date/time is saved as character/string? The problem is the nature or type ofoperations done on date/time are different when compared to string/character,number or logical values.
- how do we add/subtract dates?
- how do we extract components such as year, month, day etc.
To answer the above questions, we will first check the data type of Sys.Date()
and now()
.
class(Sys.Date())## [1] "Date"class(lubridate::now())## [1] "POSIXct" "POSIXt"class(release_date)## [1] "character"
As you can see from the above output, there are 3 different classes for storingdate/time in R
Date
POSIXct
POSIXlt
Let us explore each of the above classes one by one.
Date
Introduction
The Date
class represents calendar dates. Let us go back to Sys.Date()
. Ifyou check the class of Sys.Date()
, it is Date
. Internally, this date is anumber i.e.an integer. The unclass()
function will show how dates are storedinternally.
Sys.Date()## [1] "2020-04-17"unclass(Sys.Date())## [1] 18369
What does this integer represent? Why has R stored the date as an integer?In R, dates are represented as the number of days since 1970-01-01
. All the dates in R areinternally stored in this way. Before we explore this concept further, let uslearn to create Date
objects in R. We will continue to use the release dateof R 3.6.2, 2019-12-12
.
Until now, we have stored the above date as character/string but now we will useas.Date()
to save it as a Date
object. as.Date()
is the easiest andsimplest way to create dates in R.
release_date <- as.Date("2019-12-12")release_date## [1] "2019-12-12"
The as_date()
function from the lubridate package is similar to as.Date()
.
release_date <- lubridate::as_date("2019-12-12")release_date## [1] "2019-12-12"
If you look at the difference between release_date
and 1970-01-01
, it willbe the same as unclass(release_date)
.
release_date - as.Date("1970-01-01")## Time difference of 18242 daysunclass(release_date)## [1] 18242
Let us come back to 1970-01-01
i.e.the origin for dates in R.
lubridate::origin## [1] "1970-01-01 UTC"
From the previous examples, we know that dates are internally stored as numberof days since 1970-01-01
. How about dates older than the origin? How are theystored? Let us look at that briefly.
unclass(as.Date("1963-08-28"))## [1] -2318
Dates older than the origin are stored as negative integers. For those who arenot aware, Martin Luther King, Jr.delivered his famous I Have a Dreamspeech on 1963-08-28
. Let us move on and learn how to convert numbers intodates.
Convert Numeric
The as.Date()
function can be used to convert any of the following to a Date
object
- character/string
- number
- factor (categorical/qualitative)
We have explored how to convert strings to date. How about converting numbers todate? Sure, we can create date from numbers by specifying the origin and numberof days since it.
as.Date(18242, origin = "1970-01-01")## [1] "2019-12-12"
The origin can be changed to another date (while changing the number as well.)
as.Date(7285, origin = "2000-01-01")## [1] "2019-12-12"
ISO 8601
If you have carefully observed, the format in which we have been specifying thedates as well as of those returned by functions such as Sys.Date()
orSys.time()
is the same i.e.YYYY-MM-DD
. It includes
- the year including the century
- the month
- the date
The month and date separated by -
. This default format used in R is the ISO8601 standard for date/time. ISO 8601 is the internationally accepted way torepresent dates and times and uses the 24 hour clock system. Let us create therelease date using another function ISOdate()
.
ISOdate(year = 2019, month = 12, day = 12, hour = 8, min = 5, sec = 3, tz = "UTC")## [1] "2019-12-12 08:05:03 UTC"
We will look at all the different weird ways in which date/time are specified inthe real world in the Date & Time Formats section. For the time being, let uscontinue exploring date/time classes in R. The next class we are going to lookat is POSIXct/POSIXlt
.
POSIX
You might be wondering what is this POSIX thing? POSIX stands for PortableOperating System Interface. It is a family of standards specified formaintaining compatibility between different operating systems. Before welearn to create POSIX objects, let us look at now()
from lubridate.
class(lubridate::now())## [1] "POSIXct" "POSIXt"
now()
returns current date/time as a POSIXct object. Let us look at itsinternal representation using unclass()
unclass(lubridate::now())## [1] 1587125246## attr(,"tzone")## [1] ""
The output you see is the number of seconds since January 1, 1970.
POSIXct
POSIXct
represents the number of seconds since the beginning of 1970 (UTC) andct
stands for calendar time. To store date/time as POSIXct
objects, useas.POSIXct()
. Let us now store the release date of R 3.6.2 as POSIXct
as shownbelow
release_date <- as.POSIXct("2019-12-12 08:05:03")class(release_date)## [1] "POSIXct" "POSIXt"unclass(release_date) ## [1] 1576118103## attr(,"tzone")## [1] ""
POSIXlt
POSIXlt
represents the following information in a list
- seconds
- minutes
- hour
- day of the month
- month
- year
- day of week
- day of year
- daylight saving time flag
- time zone
- offset in seconds from GMT
The lt
in POSIXlt
stands for local time. Use as.POSIXlt()
to storedate/time as POSIXlt
objects. Let us store the release date as a POSIXlt
object as shown below
release_date <- as.POSIXlt("2019-12-12 08:05:03")release_date## [1] "2019-12-12 08:05:03 IST"
As we said earlier, POSIXlt
stores date/time components in a list and thesecan be extracted. Let us look at the date/time components returned by POSIXlt
using unclass()
.
release_date <- as.POSIXlt("2019-12-12 08:05:03")unclass(release_date)## $sec## [1] 3## ## $min## [1] 5## ## $hour## [1] 8## ## $mday## [1] 12## ## $mon## [1] 11## ## $year## [1] 119## ## $wday## [1] 4## ## $yday## [1] 345## ## $isdst## [1] 0## ## $zone## [1] "IST"## ## $gmtoff## [1] NA
Use unlist()
if you want the components returned as a vector
.
release_date <- as.POSIXlt("2019-12-12 08:05:03")unlist(release_date)## sec min hour mday mon year wday yday isdst zone gmtoff ## "3" "5" "8" "12" "11" "119" "4" "345" "0" "IST" NA
To extract specific components, use $
.
release_date <- as.POSIXlt("2019-12-12 08:05:03")release_date$hour## [1] 8release_date$mon## [1] 11release_date$zone## [1] "IST"
Now, let us look at the components returned by POSIXlt
. Some of them areintuitive
Component | Description |
---|---|
sec | Second |
min | Minute |
hour | Hour of the day |
mon | Month of the year (0-11 |
zone | Timezone |
wday | Day of week |
mday | Day of month |
year | Years since 1900 |
yday | Day of year |
isdst | Daylight saving flag |
gmtoff | Offset is seconds from GMT |
Great! We will end this section with a few tips/suggestions on when to useDate
or POSIXct/POSIXlt
.
- use
Date
when there is no time component - use
POSIX
when dealing with time and timezones - use
POSIXlt
when you want to access/extract the different components
Your Turn
R 1.0.0 was released on 2000-02-29 08:55:23 UTC
. Save it as
Date
using characterDate
using origin and numberPOSIXct
POSIXlt
and extract- month day
- day of year
- month
- zone
- ISODate
Date Arithmetic
Time to do some arithmetic with the dates. Let us calculate the length of acourse you have enrolled for (Become a Rock Star Data Scientist in 10 Days) by subtracting the course start date from the course end date.
course_start <- as_date('2017-04-12')course_end <- as_date('2017-04-21')course_duration <- course_end - course_startcourse_duration## Time difference of 9 days
Shift Date
Time to shift the course dates. We can shift a date by days, weeks or months. Let us shift the course start date by:
- 2 days
- 3 weeks
- 1 year
course_start + days(2)## [1] "2017-04-14"course_start + weeks(3)## [1] "2017-05-03"course_start + years(1)## [1] "2018-04-12"
Case Study
Compute days to settle invoice
Let us estimate the number of days to settle the invoice by subtracting thedate of invoice from the date of payment.
transact %>% mutate( days_to_pay = Payment - Invoice )## # A tibble: 2,466 x 4## Invoice Due Payment days_to_pay## <date> <date> <date> <drtn> ## 1 2013-01-02 2013-02-01 2013-01-15 13 days ## 2 2013-01-26 2013-02-25 2013-03-03 36 days ## 3 2013-07-03 2013-08-02 2013-07-08 5 days ## 4 2013-02-10 2013-03-12 2013-03-17 35 days ## 5 2012-10-25 2012-11-24 2012-11-28 34 days ## 6 2012-01-27 2012-02-26 2012-02-22 26 days ## 7 2013-08-13 2013-09-12 2013-09-09 27 days ## 8 2012-12-16 2013-01-15 2013-01-12 27 days ## 9 2012-05-14 2012-06-13 2012-07-01 48 days ## 10 2013-07-01 2013-07-31 2013-07-26 25 days ## # ... with 2,456 more rows
Compute days over due
How many of the invoices were settled post the due date? We can find this by:
- subtracting the due date from the payment date
- counting the number of rows where delay > 0
transact %>% mutate( delay = Payment - Due ) %>% filter(delay > 0) %>% count(delay)## # A tibble: 36 x 2## delay n## <drtn> <int>## 1 1 days 61## 2 2 days 65## 3 3 days 51## 4 4 days 62## 5 5 days 69## 6 6 days 56## 7 7 days 55## 8 8 days 49## 9 9 days 38## 10 10 days 33## # ... with 26 more rows
Your Turn
- compute the length of a vacation which begins on
2020-04-19
and ends on2020-04-25
- recompute the length of the vacation after shifting the vacation start and end date by
10
days and2
weeks - compute the days to settle invoice and days overdue from the
receivables.csv
data set - compute the length of employment (only for those employees who have been terminated) from the
hr-data.csv
data set (use date of hire and termination)
Time Zones & Daylight Savings
Introduction
In the previous section, POSIXlt
stored date/time components as a list. Amongthe different components it returned were
gmtoff
zone
gmtoff
is offset in seconds from GMT i.e.difference in hours and minutes fromUTC. Wait.. What do UTC and GMT stand for?
- Coordinated Universal Time (UTC)
- Greenwich Meridian Time (GMT)
Since we are talking about UTC, GMT etc., let us spend a little time onunderstanding the basics of time zones and daylight savings.
Time Zones
Timezones exist because different parts of the Earth receive sun light atdifferent times. If there was a single timezone, noon or morning would meandifferent things in different parts of the world. The timezones are based onEarth’s rotation. The Earth moves ~15 degrees every 60 minutes i.e.360 degreesin 24 hours. The planet is divided into 24 timezones, each 15 degrees oflongitude width.
Now, you have heard of Greenwich Meridian Time (GMT) right? We just saw GMT offset in POSIXlt
and you would have come across it in other time formats aswell. For example, India timezone is given as GMT +5:30. Let us explore GMT in alittle more detail. Greenwich is a suburb of London and the time at Greenwichis Greenwich Mean Time. As you move West from Greenwich, every 15degree section is one hour earlier than GMT and every 15 degree section to theEast is an hour later.
Alright! What is UTC then? Coordinated Universal Time (UTC) ,on the other hand, is the time standard commonly used across the world. Eventhough they share the same current time, GMT is a timezone whileUTC is a time standard.
So how do we check the timezone in R? When you run Sys.timezone()
, you shouldbe able to see the timezone you are in.
Sys.timezone()## [1] "Asia/Calcutta"
If you do not see the timezone, use Sys.getenv()
to get the value of theTZ environment variable.
Sys.getenv("TZ")## [1] ""
If nothing is returned, it means we have to set the timezone. Use Sys.setenv()
to set the timezone as shown below. The author resides in India and hence thetimezone is set to Asia/Calcutta
. You need to set the timezone in which youreside or work.
Sys.setenv(TZ = "Asia/Calcutta")
Another way to get the timezone is through tz()
from the lubridate package.
lubridate::tz(Sys.time())## [1] "Asia/Calcutta"
If you want to view the time in a different timezone, use with_tz()
. Let uslook at the current time in UTC instead of Indian Standard Time.
lubridate::with_tz(Sys.time(), "UTC")## [1] "2020-04-17 12:07:28 UTC"
Daylight Savings
Daylight savings also known as
- daylight saving time
- daylight savings time
- daylight time
- summer time
is the practice of advancing clocks during summer months so that darkness fallslater each day according to the clock. In other words
- advance clock by one hour in spring (spring forward)
- retard clocks by one hour in autumn (fall back)
In R, the dst()
function is an indicator for daylight savings. It returnsTRUE
if daylight saving is in force, FALSE
if not and NA
if unknown.
Sys.Date()## [1] "2020-04-17"dst(Sys.Date()) ## [1] FALSE
Your Turn
- check the timezone you live in
- check if daylight savings in on
- check the current time in UTC or a different time zone
Date & Time Formats
After the timezones and daylight savings detour, let us get back on path andexplore another important aspect, date & time formats. Although it is a goodpractice to adher to ISO 8601 format, not all date/time data will comply withit. In real world, date/time data may come in all types of weird formats. Belowis a sample
Format |
---|
December 12, 2019 |
12th Dec, 2019 |
Dec 12th, 19 |
12-Dec-19 |
2019 December |
12.12.19 |
When the data is not in the default ISO 8601 format, we need to explicitlyspecify the format in R. We do this using conversion specifications. Aconversion specification is introduced by %, usually followed by a singleletter or O or E and then a single letter.
Conversion Specifications
Specification | Description | Example |
---|---|---|
%d | Day of the month (decimal number) | 12 |
%m | Month (decimal number) | 12 |
%b | Month (abbreviated) | Dec |
%B | Month (full name) | December |
%y | Year (2 digit) | 19 |
%Y | Year (4 digit) | 2019 |
%H | Hour | 8 |
%M | Minute | 5 |
%S | Second | 3 |
Time to work through a few examples. Let us say you are dealing with dates inthe format 19/12/12
. In this format, the year comes first followed by monthand the date; each separated by a slash (/
). The year consists of only 2digits i.e.it does not include the century. Let us now map each component ofthe date to the conversion specification table shown at the beginning.
Date | Specification |
---|---|
19 | %y |
12 | %m |
12 | %d |
Using the format argument, we will specify the conversion specification as a character vectori.e.enclosed in quotes.
as.Date("19/12/12", format = "%y/%m/%d")## [1] "2019-12-12"
Another way in which the release data can be written is 2019-Dec-12
. We stillhave the year followed by the month and the date but there are a few changeshere:
- the components are separated by a
-
instead of/
- year has 4 digits i.e.includes the century
- the month is specified using abbreviation instead of digits
Let us map the components to the format table:
Date | Specification |
---|---|
2019 | %Y |
Dec | %b |
12 | %d |
Let us specify the format for the date using the above mapping.
as.Date("2019-Dec-12", format = "%Y-%b-%d")## [1] "2019-12-12"
In both the above examples, we have not dealt with time components. Let usinclude the release time of R 3.6.2 in the next one i.e.19/12/12 08:05:03
.
Date | Specification |
---|---|
19 | %y |
12 | %m |
12 | %d |
08 | %H |
05 | %M |
03 | %S |
Since we are dealing with time, we will use as.POSIXct()
instead ofas.Date()
.
as.POSIXct("19/12/12 08:05:03", tz = "UTC", format = "%y/%m/%d %H:%M:%S")## [1] "2019-12-12 08:05:03 UTC"
In the below table, we look at some of the most widely used conversionspecifications. You can learn more about these specifications by running?strptime
or help(strptime)
.
Specification | Description |
---|---|
%a | Abbreviated weekday |
%A | Full weekday |
%C | Century (00-99) |
%D | Same as %m/%d/%y |
%e | Day of month [1 - 31] |
%F | Same as %Y-%m-%d |
%h | Same as %b |
%I | Hours as decimal [01 - 12] |
%j | Day of year [001 - 366] |
%R | Same as %H:%M |
%t | Tab |
%T | Same as %H:%M:%S |
%u | Weekday 1 - 7 |
%U | Week of year [00 - 53] |
%V | Week of year [01 - 53] |
%w | Weekday 0 - 6 |
%W | Week of year [00 - 53] |
We have included a lot of practice questions for you to explore the differentdate/time formats. The solutions are available in the Learning Management Systemas well as in our GitHub repo. Try them and let us know if you have any doubts.
Guess Format
guess_formats()
from lubridate is a very useful function. It will guess thedate/time format if you specify the order in which year, month, date, hour,minute and second appear.
release_date_formats <- c("December 12th 2019", "Dec 12th 19", "dec 12 2019")guess_formats(release_date_formats, orders = "mdy", print_matches = TRUE)## Omdy mdy ## [1,] "December 12th 2019" "%Om %dth %Y" "%B %dth %Y"## [2,] "Dec 12th 19" "%Om %dth %y" "%b %dth %y"## [3,] "dec 12 2019" "%Om %d %Y" "%b %d %Y"## Omdy Omdy Omdy mdy mdy ## "%Om %dth %Y" "%Om %dth %y" "%Om %d %Y" "%B %dth %Y" "%b %dth %y" ## mdy ## "%b %d %Y"
Your Turn
Below, we have specified July 5th, 2019
in different ways. Create the date using as.Date()
while specifying the correct format for each of them.
05.07.19
5-July 2019
July 5th, 2019
July 05, 2019
2019-July- 05
05/07/2019
07/05/2019
7/5/2019
07/5/19
2019-07-05
Parse Date & Time
While creating date-time objects, we specified different formats using theconversion specification but most often you will not create date/time andinstead deal with data that comes your way from a database or API orcolleague/collaborator. In such cases, we need to be able to parse date/timefrom the data provided to us. In this section, we will focus on parsingdate/time from character data. Both base R and the lubridate package offerfunctions to parse date and time and we will explore a few of them in thissection. We will initially use functions from base R and later on explore thosefrom lubridate which will give us an opportunity to compare and contrast. Itwill also allow us to choose the functions based on the data we are dealingwith.
strptime()
will convert character data to POSIXlt
. You will use this whenconverting from character data to date/time. On the other hand, if you want toconvert date/time to character data, use any of the following:
strftime()
format()
as.character()
The above functions will convert POSIXct/POSIXlt
to character. Let us startwith a simple example. The data we have been supplied has date/time ascharacter data and in the format YYYYMMDD
i.e.nothing separates the year,month and date from each other. We will use strptime()
to convert this to anobject of class POSIXlt
.
rel_date <- strptime("20191212", format = "%Y%m%d")class(rel_date)## [1] "POSIXlt" "POSIXt"
If you have a basic knowledge of conversion specifications, you can usestrptime()
to convert character data to POSIXlt
. Let us quickly explore thefunctions to convert date/time to character data before moving on to thefunctions from lubridate.
rel_date_strf <- strftime(rel_date)class(rel_date_strf)## [1] "character"rel_date_format <- format(rel_date)class(rel_date_format)## [1] "character"rel_date_char <- as.character(rel_date)class(rel_date_char)## [1] "character"
As you can see, all the 3 functions converted date/time to character. Time tomove on and explore the lubridate package. We will start with an example inwhich the release date is formatted in 3 different ways but they have one thingin common i.e.the order in which the components appear. In all the 3 formats,the year is followed by the month and then the date.
To parse the release date, we will use parse_date_time()
from lubridate whichparses the input into POSIXct
objects.
release_date <- c("19-12-12", "20191212", "19-12 12")parse_date_time(release_date, "ymd")## [1] "2019-12-12 UTC" "2019-12-12 UTC" "2019-12-12 UTC"parse_date_time(release_date, "y m d")## [1] "2019-12-12 UTC" "2019-12-12 UTC" "2019-12-12 UTC"parse_date_time(release_date, "%y%m%d")## [1] "2019-12-12 UTC" "2019-12-12 UTC" "2019-12-12 UTC"
Try to use strptime()
in the above example and see what happens. Now, let uslook at another data set.
release_date <- c("19-07-05", "2019-07-05", "05-07-2019")
What happens in the below case? The same date appears in multiple formats. Howdo we parse them? parse_date_time()
allows us to specify mutiple date-timeformats. Let us first map the dates to their formats.
Date | Specification |
---|---|
19-07-05 | ymd |
2019-07-05 | ymd |
05-07-2019 | dmy |
The above specifications can be supplied as a character vector.
parse_date_time(release_date, c("ymd", "ymd", "dmy"))## [1] "2019-07-05 UTC" "2019-07-05 UTC" "2019-07-05 UTC"
Great! We have used both strptime()
and parse_date_time()
now. Can you tellwhat differentiates parse_date_time()
when compared to strptime()
? Wesummarize it in the points below:
- no need to include
%
prefix or separator - specify several date/time formats
There are other helper functions that can be used to
- parse dates with only year, month, day components
- parse dates with year, month, day, hour, minute, seconds components
- parse dates with only hour, minute, second components
and are explored in the below examples.
# year/month/dateymd("2019-12-12")## [1] "2019-12-12"# year/month/dateymd("19/12/12")## [1] "2019-12-12"# date/month/yeardmy(121219)## [1] "2019-12-12"# year/month/date/hour/minute/secondymd_hms(191212080503)## [1] "2019-12-12 08:05:03 UTC"# hour/minute/secondhms("8, 5, 3")## [1] "8H 5M 3S"# hour/minute/secondhms("08:05:03")## [1] "8H 5M 3S"# minute/secondms("5,3")## [1] "5M 3S"# hour/minutehm("8, 5")## [1] "8H 5M 0S"
Note, in a couple of cases where the components are not separated by /
, -
orspace, we have not enclosed the values in quotes.
Your Turn
Below, we have specified July 5th, 2019
in different ways. Parse the dates using strptime()
or parse_date_time()
or any other helper function.
July-05-19
JUL-05-19
05.07.19
5-July 2019
July 5th, 2019
July 05, 2019
2019-July- 05
05/07/2019
07/05/2019
7/5/2019
07/5/19
2019-07-05
Date & Time Components
In the second section, we discussed the downside of saving date/time ascharacter/string in R. One of the points we discussed was that we can’t extractcomponents such as year, month, day etc. In this section, we will learn toextract date/time components such as
- year
- month
- date
- week
- day
- quarter
- semester
- hour
- minute
- second
- timezone
The below table outlines the functions we will explore in the first part of thissection.
Function | Description |
---|---|
year() | Get year |
month() | Get month (number) |
month(label = TRUE) | Get month (abbreviated name) |
month(abbr = FALSE) | Get month (full name) |
months() | Get month |
week() | Get week |
Year
release_date <- ymd_hms("2019-12-12 08:05:03")year(release_date) ## [1] 2019
Month
month()
will return the month as a number i.e.12
for December.
month(release_date)## [1] 12
Instead, if you want the name of the month , use the label
argument and set itto TRUE
. Now it returns Dec
instead of 12
.
month(release_date, label = TRUE)## [1] Dec## 12 Levels: Jan < Feb < Mar < Apr < May < Jun < Jul < Aug < Sep < ... < Dec
But this is the abbreviated name and not the full name. How do we get the fullname of the month? Set the abbr
argument to FALSE
.
month(release_date, label = TRUE, abbr = FALSE)## [1] December## 12 Levels: January < February < March < April < May < June < ... < December
Ah! now we can see the full name of the month. months()
from base R willreturn the full name of the month by default. If you want the abbreviated name,use the abbreviate
argument and set it to TRUE
.
months(release_date)## [1] "December"
Week
week()
returns the number of complete 7 day periods between the date and 1stJanuary plus one.
week(release_date)## [1] 50
Day
Use day()
to extract the date component. There are other variations such as
Function | Description |
---|---|
day | Get day |
mday() | Day of the month |
wday() | Day of the week |
qday() | Day of quarter |
yday() | Day of year |
weekdays() | Day of week |
days_in_month() | Days in the month |
day(release_date)## [1] 12mday(release_date) ## [1] 12qday(release_date) ## [1] 73yday(release_date) ## [1] 346
wday
can return
- a number
- abbreviation of the weekday
- full name of the weekday
wday(release_date) ## [1] 5wday(release_date, label = TRUE)## [1] Thu## Levels: Sun < Mon < Tue < Wed < Thu < Fri < Satwday(release_date, label = TRUE, abbr = FALSE) ## [1] Thursday## 7 Levels: Sunday < Monday < Tuesday < Wednesday < Thursday < ... < Saturday
weekdays()
from base R also returns the day of the week (the name and notthe number). If you want the abbreviated name, use the abbreviate
argument.
weekdays(release_date)## [1] "Thursday"weekdays(release_date, abbreviate = TRUE)## [1] "Thu"
Days in Month
If you want to know the number of days in the month, use days_in_month()
.In our example, the month is December and it has 31 days.
days_in_month(release_date)## Dec ## 31
Hour, Minute & Seconds
Function | Description |
---|---|
hour() | Get hour |
minute() | Get minute |
second() | Get second |
seconds() | Number of seconds since 1970-01-01 |
So far we have been looking at date components. Now, let us look at timecomponents.
hour(release_date)## [1] 8minute(release_date)## [1] 5second(release_date)## [1] 3
seconds()
returns the number of seconds since 1970-01-01
.
seconds(release_date)## [1] "1576137903S"
Quarter & Semester
quarter()
will return the quarter from the date. December is in the 4thquarter and hence it returns 4.
quarter(release_date)## [1] 4
If you want the year along with the quarter, set the with_year
argument toTRUE
.
quarter(release_date, with_year = TRUE)## [1] 2019.4
In India, the fiscal starts in April and December falls in the 3rd quarter. Howcan we accommodate this change? The fiscal_start
argument allows us to set themonth in which the fiscal begins. We will set it to 4 for April. Now it returns3 instead of 4.
quarter(release_date, fiscal_start = 4) ## [1] 3
quarters()
from base R also returns the quarter.
quarters(release_date)## [1] "Q4"
Function | Description |
---|---|
quarter() | Get quarter |
quarter(with_year = TRUE) | Quarter with year |
quarter(fiscal_start = 4) | Fiscal starts in April |
quarters() | Get quarter |
semester() | Get semester |
Case Study
Extract Date, Month & Year from Due Date
Let us now extract the date, month and year from the Due
column.
transact %>% mutate( due_day = day(Due), due_month = month(Due), due_year = year(Due) )## # A tibble: 2,466 x 6## Invoice Due Payment due_day due_month due_year## <date> <date> <date> <int> <dbl> <dbl>## 1 2013-01-02 2013-02-01 2013-01-15 1 2 2013## 2 2013-01-26 2013-02-25 2013-03-03 25 2 2013## 3 2013-07-03 2013-08-02 2013-07-08 2 8 2013## 4 2013-02-10 2013-03-12 2013-03-17 12 3 2013## 5 2012-10-25 2012-11-24 2012-11-28 24 11 2012## 6 2012-01-27 2012-02-26 2012-02-22 26 2 2012## 7 2013-08-13 2013-09-12 2013-09-09 12 9 2013## 8 2012-12-16 2013-01-15 2013-01-12 15 1 2013## 9 2012-05-14 2012-06-13 2012-07-01 13 6 2012## 10 2013-07-01 2013-07-31 2013-07-26 31 7 2013## # ... with 2,456 more rows
Data Sanitization
Let us do some data sanitization. If the due day happens to be February 29,let us ensure that the due year is a leap year. Below are the steps to checkif the due year is a leap year:
- we will extract the following from the due date:
- day
- month
- year
- we will then create a new column
is_leap
which will have be set toTRUE
ifthe year is a leap year else it will be set toFALSE
- filter all the payments due on 29th Feb
- select the following columns:
Due
is_leap
transact %>% mutate( due_day = day(Due), due_month = month(Due), due_year = year(Due), is_leap = leap_year(due_year) ) %>% filter(due_month == 2 & due_day == 29) %>% select(Due, is_leap) ## # A tibble: 4 x 2## Due is_leap## <date> <lgl> ## 1 2012-02-29 TRUE ## 2 2012-02-29 TRUE ## 3 2012-02-29 TRUE ## 4 2012-02-29 TRUE
Invoices Distribution by Quarter
Let us count the invoices due for each quarter.
transact %>% mutate( quarter_due = quarter(Due) ) %>% count(quarter_due)## # A tibble: 4 x 2## quarter_due n## <int> <int>## 1 1 521## 2 2 661## 3 3 618## 4 4 666
Your Turn
Get the R release dates using r_versions()
from the rversions package andtabulate the following
- year
- month with label
- weekday with label
- hour
- and quarter
Create, Update & Verify
In the second section, we learnt to create date-time objects using as.Date()
,as.POSIXct()
etc. In this section, we will explore a few other functions thatwill allow us to do the same
make_date()
make_datetime()
Create
To create date without time components, use make_date()
and specify thefollowing:
- year
- month
- date
We need to specify all the components in numbers i.e.we cannot use Dec
orDecember
for the month. It has to be 12
.
make_date(year = 2019, month = 12, day = 12)## [1] "2019-12-12"
When you need to include time components, use make_datetime()
.
make_datetime(year = 2019, month = 12, day = 12, hour = 08, min = 05, sec = 03, tz = "UTC")## [1] "2019-12-12 08:05:03 UTC"
Update
Let us look at another scenario. You have a date-time object and want to changeone of its components i.e.any of the following
- year
- month
- date
Instead of creating another date-time object, you can change any of thecomponents using update()
. In the below example, we will start with the dateof release of R version 3.6.1 and using update()
, we will change it to2019-12-12
.
prev_release <- ymd("2019-07-05")prev_release %>% update(year = 2019, month = 12, mday = 12)## [1] "2019-12-12"
Date Sequence
So far we have created a single date-time instance. How about creating asequence of dates? We can do that using seq.Date()
. We need to specify thefrom date as the bare minimum input. If the end date is not specified, it willcreate the sequence uptil the current date.
The interval of the sequence can be specified in any of the following units:
- day
- week
- month
- quarter
- year
We can add the following to the interval units
- integer
+
/-
(increment or decrement)
Using the integer, we can specify multiples of the units mentioned and using thesign, we can specify whether to increment or decrement.
The below table displays the main arguments used in seq.Date()
:
Function | Description |
---|---|
from | Starting date of the sequence |
by | End date of the sequence |
to | Date increment of the sequence |
length.out | Length of the sequence |
along.with | Use length of this value as length of sequence |
In the first example, we will create a sequence of dates from 2010-01-01
to2019-12-31
. The unit of increment should be a year i.e.the differencebetween the dates in the sequence should be 1 year, specified using the by
argument.
seq.Date(from = as.Date("2010-01-01"), to = as.Date("2019-12-31"), by = "year")## [1] "2010-01-01" "2011-01-01" "2012-01-01" "2013-01-01" "2014-01-01"## [6] "2015-01-01" "2016-01-01" "2017-01-01" "2018-01-01" "2019-01-01"
In the next example, we change the unit of increment to a quarter i.e.thedifference between the dates in the sequence should be a quarter or 3 months.
seq.Date(from = as.Date("2009-12-12"), to = as.Date("2019-12-12"), by = "quarter")## [1] "2009-12-12" "2010-03-12" "2010-06-12" "2010-09-12" "2010-12-12"## [6] "2011-03-12" "2011-06-12" "2011-09-12" "2011-12-12" "2012-03-12"## [11] "2012-06-12" "2012-09-12" "2012-12-12" "2013-03-12" "2013-06-12"## [16] "2013-09-12" "2013-12-12" "2014-03-12" "2014-06-12" "2014-09-12"## [21] "2014-12-12" "2015-03-12" "2015-06-12" "2015-09-12" "2015-12-12"## [26] "2016-03-12" "2016-06-12" "2016-09-12" "2016-12-12" "2017-03-12"## [31] "2017-06-12" "2017-09-12" "2017-12-12" "2018-03-12" "2018-06-12"## [36] "2018-09-12" "2018-12-12" "2019-03-12" "2019-06-12" "2019-09-12"## [41] "2019-12-12"
We will now create a sequence of dates but instead of specifying the unit ofincrement, we specify the number of dates in the sequence i.e.the length of thesequence. We do this using the length.out
argument which specifies the desiredlength of the sequence. We want the sequence to have 10 dates including thestart and end date, and hence we supply the value 10
for the length.out
argument.
seq.Date(from = as.Date("2010-01-01"), to = as.Date("2019-12-31"), length.out = 10)## [1] "2010-01-01" "2011-02-10" "2012-03-22" "2013-05-02" "2014-06-11"## [6] "2015-07-22" "2016-08-31" "2017-10-10" "2018-11-20" "2019-12-31"
In all of the previous examples, we have specified both the start and the enddate. Let us look at a few examples where we create a sequence of dates wherewe only specify the start date. In the below example, we want to create asequence of dates starting from 2010-01-01
. The unit of increment should be 1year i.e.the difference between the dates in the sequence should be 1 year andthe length of the sequence should be 10
i.e.the number of dates including thestart date should be 10
.
seq.Date(from = as.Date("2010-01-01"), by = "year", length.out = 10)## [1] "2010-01-01" "2011-01-01" "2012-01-01" "2013-01-01" "2014-01-01"## [6] "2015-01-01" "2016-01-01" "2017-01-01" "2018-01-01" "2019-01-01"
The unit of increment can include multiples and +/-
sign i.e.it can be anunit of increment or decrement. In the next example, we can increment the datesin the sequence by 2
i.e.the difference between the dates should be 2
instead of 1
. This is achieved by specifying the unit of increment (multiple)first followed by a space and then the unit. In our example, it is 2 year
. Asyou can see, the sequence now goes all the way till 2028
and the gap betweenthe dates is 2 years.
seq.Date(from = as.Date("2010-01-01"), by = "2 year", length.out = 10)## [1] "2010-01-01" "2012-01-01" "2014-01-01" "2016-01-01" "2018-01-01"## [6] "2020-01-01" "2022-01-01" "2024-01-01" "2026-01-01" "2028-01-01"
Let us say instead of increment we want to decrement the dates i.e.the sequenceof dates will go backwards as shown in the next example. We achieve this byusing the -
sign along with the unit of decrement. The sequence of dates innext example starts from 2010
and goes back upto 1992
and the differencebetween the dates in 2 years.
seq.Date(from = as.Date("2010-01-01"), by = "-2 year", length.out = 10)## [1] "2010-01-01" "2008-01-01" "2006-01-01" "2004-01-01" "2002-01-01"## [6] "2000-01-01" "1998-01-01" "1996-01-01" "1994-01-01" "1992-01-01"
In the last example, we will explore the along.with
argument. Here we havesupplied a vector which is a sequence of numbers from 1 to 10. The length ofthis vector is 10 and the same length is used as the length of the sequence i.e.the length of value supplied to along.with
is also the length of the sequence.
seq.Date(from = as.Date("2010-01-01"), by = "-2 year", along.with = 1:10)## [1] "2010-01-01" "2008-01-01" "2006-01-01" "2004-01-01" "2002-01-01"## [6] "2000-01-01" "1998-01-01" "1996-01-01" "1994-01-01" "1992-01-01"
Verify Type
How do you check if the data is a date-time object? You can do that using anyof the following from the lubridate package.
is.Date()
is.POSIXct()
is.POSIXlt()
is.Date(release_date)## [1] FALSEis.POSIXct(release_date)## [1] TRUEis.POSIXlt(release_date)## [1] FALSE
Your Turn
R 2.0.0 was released on
2004-10-04 14:24:38
. Create this date using bothmake_date()
andmake_datetime()
R 3.0.0 was released on
2013-04-03 07:12:36
. Update the date created in theprevious step to the above usingupdate()
Intervals, Duration & Period
In this section, we will learn about
- intervals
- duration
- and period
Interval
An interval is a timespan defined by two date-times. Let us represent the lengthof the course using interval
.
course_start <- as_date('2017-04-12')course_end <- as_date('2017-04-21')interval(course_start, course_end)## [1] 2017-04-12 UTC--2017-04-21 UTC
If you observe carefully, the interval is represented by the course start andend dates. We will learn how to use intervals in the case study.
Overlapping Intervals
Let us say you are planning a vacation and want to check if the vacationdates overlap with the course dates. You can do this by:
- creating vacation and course intervals
- use
int_overlaps()
to check if two intervals overlap. It returnsTRUE
if the intervals overlap elseFALSE
.
Let us use the vacation start and end dates to create vacation_interval
and then check if it overlaps with course_interval
.
vacation_start <- as_date('2017-04-19')vacation_end <- as_date('2017-04-25')course_interval <- interval(course_start, course_end)vacation_interval <- interval(vacation_start, vacation_end)int_overlaps(course_interval, vacation_interval)## [1] TRUE
How many invoices were settled within due date?
Let us use intervals to count the number of invoices that were settled withinthe due date. To do this, we will:
- create an interval for the invoice and due date
- create a new column
due_next
by incrementing the due date by 1 day - another interval for
due_next
and the payment date - if the intervals overlap, the payment was made within the due date
transact %>% mutate( inv_due_interval = interval(Invoice, Due), due_next = Due + days(1), due_pay_interval = interval(due_next, Payment), overlaps = int_overlaps(inv_due_interval, due_pay_interval) ) %>% select(Invoice, Due, Payment, overlaps)## # A tibble: 2,466 x 4## Invoice Due Payment overlaps## <date> <date> <date> <lgl> ## 1 2013-01-02 2013-02-01 2013-01-15 TRUE ## 2 2013-01-26 2013-02-25 2013-03-03 FALSE ## 3 2013-07-03 2013-08-02 2013-07-08 TRUE ## 4 2013-02-10 2013-03-12 2013-03-17 FALSE ## 5 2012-10-25 2012-11-24 2012-11-28 FALSE ## 6 2012-01-27 2012-02-26 2012-02-22 TRUE ## 7 2013-08-13 2013-09-12 2013-09-09 TRUE ## 8 2012-12-16 2013-01-15 2013-01-12 TRUE ## 9 2012-05-14 2012-06-13 2012-07-01 FALSE ## 10 2013-07-01 2013-07-31 2013-07-26 TRUE ## # ... with 2,456 more rows
Below we show another method to count the number of invoices paid within thedue date. Instead of using days
to change the due date, we use int_shift
to shift it by 1 day.
transact %>% mutate( inv_due_interval = interval(Invoice, Due), due_pay_interval = interval(Due, Payment), due_pay_next = int_shift(due_pay_interval, by = days(1)), overlaps = int_overlaps(inv_due_interval, due_pay_next) ) %>% select(Invoice, Due, Payment, overlaps)## # A tibble: 2,466 x 4## Invoice Due Payment overlaps## <date> <date> <date> <lgl> ## 1 2013-01-02 2013-02-01 2013-01-15 TRUE ## 2 2013-01-26 2013-02-25 2013-03-03 FALSE ## 3 2013-07-03 2013-08-02 2013-07-08 TRUE ## 4 2013-02-10 2013-03-12 2013-03-17 FALSE ## 5 2012-10-25 2012-11-24 2012-11-28 FALSE ## 6 2012-01-27 2012-02-26 2012-02-22 TRUE ## 7 2013-08-13 2013-09-12 2013-09-09 TRUE ## 8 2012-12-16 2013-01-15 2013-01-12 TRUE ## 9 2012-05-14 2012-06-13 2012-07-01 FALSE ## 10 2013-07-01 2013-07-31 2013-07-26 TRUE ## # ... with 2,456 more rows
You might be thinking why we incremented the due date by a day before creatingthe interval between the due day and the payment day. If we do not increment,both the intervals will share a common date i.e.the due date and they willalways overlap as shown below:
transact %>% mutate( inv_due_interval = interval(Invoice, Due), due_pay_interval = interval(Due, Payment), overlaps = int_overlaps(inv_due_interval, due_pay_interval) ) %>% select(Invoice, Due, Payment, overlaps)## # A tibble: 2,466 x 4## Invoice Due Payment overlaps## <date> <date> <date> <lgl> ## 1 2013-01-02 2013-02-01 2013-01-15 TRUE ## 2 2013-01-26 2013-02-25 2013-03-03 TRUE ## 3 2013-07-03 2013-08-02 2013-07-08 TRUE ## 4 2013-02-10 2013-03-12 2013-03-17 TRUE ## 5 2012-10-25 2012-11-24 2012-11-28 TRUE ## 6 2012-01-27 2012-02-26 2012-02-22 TRUE ## 7 2013-08-13 2013-09-12 2013-09-09 TRUE ## 8 2012-12-16 2013-01-15 2013-01-12 TRUE ## 9 2012-05-14 2012-06-13 2012-07-01 TRUE ## 10 2013-07-01 2013-07-31 2013-07-26 TRUE ## # ... with 2,456 more rows
Shift Interval
Intervals can be shifted too. In the below example, we shift the courseinterval by:
- 1 day
- 3 weeks
- 1 year
course_interval <- interval(course_start, course_end)# shift course_interval by 1 day int_shift(course_interval, by = days(1))## [1] 2017-04-13 UTC--2017-04-22 UTC# shift course_interval by 3 weeksint_shift(course_interval, by = weeks(3))## [1] 2017-05-03 UTC--2017-05-12 UTC# shift course_interval by 1 yearint_shift(course_interval, by = years(1))## [1] 2018-04-12 UTC--2018-04-21 UTC
Within
Let us assume that we have to attend a conference in April 2017. Does itclash with the course? We can answer this using %within%
which willreturn TRUE
if a date falls within an interval.
conference <- as_date('2017-04-15')conference %within% course_interval## [1] TRUE
How many invoices were settled within due date?
Let us use %within%
to count the number of invoices that were settled withinthe due date. We will do this by:
- creating an interval for the invoice and due date
- check if the payment date falls within the above interval
transact %>% mutate( inv_due_interval = interval(Invoice, Due), overlaps = Payment %within% inv_due_interval ) %>% select(Due, Payment, overlaps)## # A tibble: 2,466 x 3## Due Payment overlaps## <date> <date> <lgl> ## 1 2013-02-01 2013-01-15 TRUE ## 2 2013-02-25 2013-03-03 FALSE ## 3 2013-08-02 2013-07-08 TRUE ## 4 2013-03-12 2013-03-17 FALSE ## 5 2012-11-24 2012-11-28 FALSE ## 6 2012-02-26 2012-02-22 TRUE ## 7 2013-09-12 2013-09-09 TRUE ## 8 2013-01-15 2013-01-12 TRUE ## 9 2012-06-13 2012-07-01 FALSE ## 10 2013-07-31 2013-07-26 TRUE ## # ... with 2,456 more rows
Duration
Duration is timespan measured in seconds. To create a duration object, useduration()
. The timespan can be anything from seconds to years but it will berepresented as seconds. Let us begin by creating a duration object where the timespan is in seconds.
duration(50, "seconds")## [1] "50s"
Another way to specify the above timespan is shown below:
duration(second = 50)## [1] "50s"
As you can see, the output is same in both the cases. Let us increase the timespan to 60 seconds and see what happens.
duration(second = 60)## [1] "60s (~1 minutes)"
Although the timespan is primarily measured in seconds, it also shows ~1 minutes
in the brackets. As the length of the timespan increases i.e.the number becomes large, it is represented using larger units such as hours and days. In the below examples, as the number of seconds increases, you can observe larger units being used to represent the timespan.
# minutesduration(minute = 50)## [1] "3000s (~50 minutes)"duration(minute = 60)## [1] "3600s (~1 hours)"# hoursduration(hour = 23)## [1] "82800s (~23 hours)"duration(hour = 24)## [1] "86400s (~1 days)"
The following helper functions can be used to create duration objects as well.
# defaultdseconds()## [1] "1s"dminutes()## [1] "60s (~1 minutes)"# secondsduration(second = 59)## [1] "59s"dseconds(59)## [1] "59s"# minutesduration(minute = 50)## [1] "3000s (~50 minutes)"dminutes(50)## [1] "3000s (~50 minutes)"# hoursduration(hour = 36)## [1] "129600s (~1.5 days)"dhours(36)## [1] "129600s (~1.5 days)"# weeksduration(week = 56)## [1] "33868800s (~1.07 years)"dweeks(56)## [1] "33868800s (~1.07 years)"
Let us use the above helper functions to get the course length in different units.
# course length in seconds course_interval / dseconds()## [1] 777600# course length in minutescourse_interval / dminutes()## [1] 12960# course length in hourscourse_interval / dhours()## [1] 216# course length in weekscourse_interval / dweeks()## [1] 1.285714# course length in yearscourse_interval / dyears()## [1] 0.02465753
Period
A period
is a timespan defined in units such as years, months, and days. Inthe below examples, we use period()
to represent timespan using differentunits.
# secondperiod(5, "second")## [1] "5S"period(second = 5)## [1] "5S"# minute & secondperiod(c(3, 5), c("minute", "second"))## [1] "3M 5S"period(minute = 3, second = 5)## [1] "3M 5S"# hour, minte & secondperiod(c(1, 3, 5), c("hour", "minute", "second"))## [1] "1H 3M 5S"period(hour = 1, minute = 3, second = 5)## [1] "1H 3M 5S"# day, hour, minute & secondperiod(c(3, 1, 3, 5), c("day", "hour", "minute", "second"))## [1] "3d 1H 3M 5S"period(day = 3, hour = 1, minute = 3, second = 5)## [1] "3d 1H 3M 5S"
Let us get the course length in different units using as.period()
.
# course length in secondas.period(course_interval, unit = "seconds")## [1] "777600S"# course length in hours and minutesas.period(course_interval, unit = "minutes")## [1] "12960M 0S"# course length in hours, minutes and secondsas.period(course_interval, unit = "hours")## [1] "216H 0M 0S"
time_length()
computes the exact length of a timespan i.e.duration
, interval
or period
. Let us use time_length()
to compute the length of thecourse in different units.
# course length in secondstime_length(course_interval, unit = "seconds")## [1] 777600# course length in minutestime_length(course_interval, unit = "minutes")## [1] 12960# course length in hourstime_length(course_interval, unit = "hours")## [1] 216
Round & Rollback
In this section, we will learn to round date/time to the nearest unit and rollback dates.
Rounding Dates
We will explore functions for rounding dates
- to the nearest value using
round_dates()
- down using
floor_date()
- up using
ceiling_date()
The unit for rounding can be any of the following:
- second
- minute
- hour
- day
- week
- month
- bimonth
- quarter
- season
- halfyear
- and year
We will look at a few examples using round_date()
and you will then practiceusing the other two functions.
# minuteround_date(release_date, unit = "minute")## [1] "2019-12-12 08:05:00 UTC"round_date(release_date, unit = "mins")## [1] "2019-12-12 08:05:00 UTC"round_date(release_date, unit = "5 mins")## [1] "2019-12-12 08:05:00 UTC"# hourround_date(release_date, unit = "hour")## [1] "2019-12-12 08:00:00 UTC"# dayround_date(release_date, unit = "day")## [1] "2019-12-12 UTC"
Rollback
Use rollback()
if you want to change the date to the last day of the previousmonth or the first day of the month.
rollback(release_date)## [1] "2019-11-30 08:05:03 UTC"
To change the date to the first day of the month, use the roll_to_first
argument and set it to TRUE
.
rollback(release_date, roll_to_first = TRUE)## [1] "2019-12-01 08:05:03 UTC"
Your Turn
- round up R release dates to hours
- round down R release dates to minutes
- rollback R release dates to the beginning of the month
Readings & References
- https://lubridate.tidyverse.org/
- https://r4ds.had.co.nz/dates-and-times.html
- https://en.wikipedia.org/wiki/Daylight_saving_time
- https://en.wikipedia.org/wiki/Time_zone
- https://www.worldtimebuddy.com/
- https://en.wikipedia.org/wiki/POSIX
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