#####Introduction to Business Analytics with R#####

In this section I am converting a date string into a date object of a standard format and then displaying it.

date1Words<- 'May 8, 2020'
d <- format(as.Date(date1Words, format = "%B %d, %Y"), "%m/%d/%Y")
d <- as.Date(d, format = '%m/%d/%y')
print(d)

## [1] "2020-05-08"

Now I check the datatype of the date object.

class(d)

## [1] "Date"

I already installed the lubridate package so I will load it.

library(lubridate)

## Warning: package 'lubridate' was built under R version 4.3.3

## 
## Attaching package: 'lubridate'

## The following objects are masked from 'package:base':
## 
##     date, intersect, setdiff, union

Let’s extract a few date elements from the d date object using the lubridate functions.I will display them in this chunk as well.

d_year = year(d)
d_month = month(d)
d_week = week(d)
d_day = wday(d)
print(c(d_year, d_month, d_week, d_day))

## [1] 2020    5   19    6

Create a new datetime object d_25 based on object d plus 25 days.The instructions for this section are ambiguous in saying, “..where d_25 is the date 25 days from now,” but d is a specific date, not today() or “now”. So I am picking the meaning I think is intended.

d_25 = d + 25
print(d_25)

## [1] "2020-06-02"

Finally, let’s check that thee difference between d and d_25 is actually 25 days.

diff <- difftime(d_25, d, units = "days")
print(diff)

## Time difference of 25 days

diff == 25

## [1] TRUE