Module 3 Peer Review

Introduction to Business Analytics with R

Creating a Datetime Object in Base R

# Convert the character string into a date object using base R
# The format is specified as MM/DD/YYYY

d <- as.Date("05/08/2020", format = "%m/%d/%Y")

Checking the Data Type of the d Object

# Print the object to check if it is in date format
print(d)

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

Installing and Loading the lubridate Package

# Install lubridate if not already installed
# install.packages("lubridate")

# Load the lubridate package
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

Extracting Year, Month, Week, and Weekday

# Extract year, month, week number, and weekday number from d

d_year <- year(d)
d_month <- month(d)
d_week <- week(d)
d_day <- wday(d)

# Display the extracted values
print(d_year)

## [1] 2020

print(d_month)

## [1] 5

print(d_week)

## [1] 19

print(d_day)

## [1] 6

Creating a New Date Object 25 Days Later

# Create a new date object that is 25 days after d
d_25 <- d + 25

# Display the new date object
d_25

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

Calculating the Difference Between Dates

# Calculate the difference between d and d_25

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

# Display the difference
diff_days

## Time difference of 25 days