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R in 3 Months (Fall 2022)

{lubridate} for working with dates and times

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The {lubridate} package is part of the tidyverse and provides awesome tools for manipulating, creating and working with both dates and times. Charlie's recorded the short video lesson on the topic below, and there's a dedicated chapter in the R for Data Science book.

Here's a copy of the code that Charlie used in her video

library(tidyverse)
library(haven)
library(lubridate)

museum_data <- read_spss("Corning Museum of Glass - Glass of the Architects TT Data 2018-10-30.sav")

museum_data %>%
  select(starts_with("time")) %>% 
  mutate(time_A = duration(time_A))

museum_data %>%
  select(starts_with("time")) %>% 
  mutate(across(starts_with("time"),
                ~ duration(.))) %>% 
  select(1:4) %>% 
  mutate(time_total_a_thru_c = time_A + time_B + time_C,
         time_total_a_thru_c = as.numeric(time_total_a_thru_c, "hours"))
         

# Make shipping data -------------------------------------------------------------

set.seed(1)
shipping_data <- tibble(
  order_date = sample(seq(ymd('2012-04-07'),ymd('2020-03-22'), by = 'day'), 50)
) %>% 
  mutate(shipping_date = order_date + sample(days(5:10), 50, replace = TRUE)) %>% 
  mutate(receive_date = shipping_date + sample(days(10:50), 50, replace = TRUE)) %>% 
  mutate(id = row_number()) %>% 
  mutate(order_year = year(order_date),
         order_month = month(order_date),
         order_day = day(order_date)) %>% 
  select(id, order_year, order_month, order_day, shipping_date, receive_date)


# Wrangle shipping date ---------------------------------------------------

shipping_data %>% 
  mutate(order_date = make_date(order_year, order_month, order_day)) %>% 
  select(id, order_date, shipping_date, receive_date) %>% 
  mutate(total_order_time = receive_date - order_date,
         total_order_time = as.numeric(total_order_time, "days"))

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Course Content

142 Lessons

1
R in 3 Months Fall 2022 Week 10 Drop-in Session