Exercise 06: Date and Time

Author
Affiliation

Jihong Zhang*, Ph.D

Educational Statistics and Research Methods (ESRM) Program*

University of Arkansas

Published

August 18, 2025

Question 1: Basic Date-Time Functions

  1. Load the lubridate package and print the current date and time using R functions.
  2. Convert the following character strings into Date objects:
    • "2024-07-01"
    • "15/08/2023" (Use the correct format for parsing.)
  3. Convert the following character strings into POSIXct date-time objects:
    • "2023-12-25 18:30:00"
    • "07-13-2024 14:45" (Use the correct format for parsing.)
❖ Answer ❖ 
library(lubridate)
ymd("2024-07-01")
dmy("15/08/2023")

ymd_hms("2024-01-15 14:30:45")
mdy_hm("07-13-2024 14:45") # correct

Question 2: Importing and Parsing Dates

  1. Create a CSV file (or use an inline string) with the following data:
csv_data.csv
date, datetime
01-15-2024, 2024/01/15 14:20:00
02-28-2023, 2023-02-28 23:59:59
-   Read this CSV into R using `read_csv()`.
-   Ensure that the `date` column is parsed as a `Date` and the `datetime` column is parsed as a `POSIXct` object.
  1. Modify the import function to parse the date column correctly, assuming it follows the "MM-DD-YYYY" format.
❖ Answer ❖ 
csv_data <- "
  date, datetime
  01-15-2024, 2024/01/15 14:20:00
  02-28-2023, 2023-02-28 23:59:59
"
library(readr)
library(lubridate)

df <- read_csv(csv_data)
df

df2 <- read_csv(csv_data, col_types = cols(date = col_date("%m-%d-%Y")))
df2
❖ Answer ❖ 
df3 <- df2 |> mutate(datetime = ymd_hms(datetime))
df3

Question 3: Extracting Components from Dates

  1. Given the date vector:

    ❖ Answer ❖ 
    dates <- as.Date(c("2023-07-15", "2024-01-01", "2025-12-31"))
    • Extract the year, month, and day components.
    • Extract the day of the week in both numeric and abbreviated name formats.
    • Extract the day of the year.
❖ Answer ❖ 
dates <- as.Date(c("2023-07-15", "2024-01-01", "2025-12-31"))
year(dates)  
month(dates) 
day(dates)
wday(dates)
yday(dates)

Question 4: Rounding and Formatting Dates

  1. Given the date-time "2024-07-12 15:47:23", apply:
    • floor_date() to round it down to the nearest hour.
    • ceiling_date() to round it up to the nearest day.
    • round_date() to round it to the nearest 10-minute interval.
❖ Answer ❖ 
library(lubridate)

dt <- ymd_hms("2024-07-12 15:47:23")

# Round down to the nearest hour
floor_dt <- floor_date(dt, unit = "hour")

# Round up to the nearest day
ceiling_dt <- ceiling_date(dt, unit = "day")

# Round to the nearest 10-minute interval
round_dt <- round_date(dt, unit = "10 minutes")

# Print results
floor_dt    # "2024-07-12 15:00:00"
ceiling_dt  # "2024-07-13 00:00:00"
round_dt    # "2024-07-12 15:50:00"
  1. Convert "2025-02-15" into the following formats using format():
    • "YYYY/MM/DD"
    • "Month Day, Year" (e.g., "February 15, 2025")
    • "Day-Month-Year" (e.g., "15-February-2025")
❖ Answer ❖ 
date <- as.Date("2025-02-15")

# Format as "YYYY/MM/DD"
format_1 <- format(date, "%Y/%m/%d") 

# Format as "Month Day, Year"
format_2 <- format(date, "%B %d, %Y") 

# Format as "Day-Month-Year"
format_3 <- format(date, "%d-%B-%Y") 

# Print results
format_1  # "2025/02/15"
format_2  # "February 15, 2025"
format_3  # "15-February-2025"

Question 5: Working with Time Zones

  1. Retrieve the system’s current time zone and display all available time zones containing "America".
  2. Convert "2024-08-01 12:00:00" from "UTC" to:
    • "America/New_York"
    • "Europe/London"
    • "Asia/Tokyo"
  3. Calculate the time difference (in hours) between "US/Central" and "Asia/Hong_Kong" on January 1, 2025.
    • Hint: use difftime(units = "hours") to return time difference between two time
❖ Answer ❖ 
# Get the system's current time zone
current_tz <- Sys.timezone()

# List all available time zones containing "America"
america_tzs <- OlsonNames()[grep("America", OlsonNames())]

# Print results
current_tz     # Example: "America/Chicago" (varies by system)
america_tzs    # Displays all time zones containing "America"
❖ Answer ❖ 
library(lubridate)

# Define the UTC datetime
utc_time <- ymd_hms("2024-08-01 12:00:00", tz = "UTC")

# Convert to different time zones
ny_time <- with_tz(utc_time, "America/New_York")
london_time <- with_tz(utc_time, "Europe/London")
tokyo_time <- with_tz(utc_time, "Asia/Tokyo")

# Print results
ny_time      # "2024-08-01 08:00:00 EDT"
london_time  # "2024-08-01 13:00:00 BST"
tokyo_time   # "2024-08-01 21:00:00 JST"
❖ Answer ❖ 
# Define the datetime in "US/Central"
central_time <- ymd_hms("2025-01-01 00:00:00", tz = "US/Central")

# Convert to "Asia/Hong_Kong"
hk_time <- ymd_hms("2025-01-01 00:00:00", tz = "Asia/Hong_Kong")

# Compute time difference in hours
time_difference <- as.numeric(difftime(hk_time, central_time, units = "hours"))

# Print result
time_difference  # 14 (hours)
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