Classwork 9

ETL Process in R

Question 1

Consider the following three related data frames from the Classwork 8 - Social Media Analytics:

• df_survey — individual student responses about social media usage
  
• df_platform — reference information about each social media platform
  
• df_card — additional details or attributes linked to each platform

You will use these data frames in Question 1.

df_platform <- 
  read_csv("https://bcdanl.github.io/data/platform_reference.csv")

df_card <- 
  read_csv("https://bcdanl.github.io/data/card_suit_rules.csv")

df_survey <- 
  read_csv("https://bcdanl.github.io/data/danl-101-survey-social-media-fall-2025.csv")

Part A

Write an R code to create a data frame named df_joined that combines the three datasets — df_survey, df_platform, and df_card — using the left_join() function.

Part B

Find out which platforms DANL 101 students use.

count(): Counting Occurrences of Each Category in a Categorical Variable

DATA.FRAME |> count(CATERIGOCAL_VARIABLE)

• The data transformation function count() calculates the frequency of each unique value in a categorical variable.

library(nycflights13)
flights |> count(origin)

• flights |> count(origin) returns the data.frame with the two variables, origin and n:
  • n: the number of occurrences of each unique value in the origin variable in the flights data.frame

Part C

Count how many students use each platform, and determine which platform is the most popular based on the number of users.

• Check out the new data transformation function: count():

Part D

Calculate descriptive statistics (e.g., mean, standard deviation, and quartiles) of daily_time_min for each platform by using the skimr::skim() function.

Question 2

Consider the two related data.frames, df_1 and df_2:

• df_1

id	name	age
1	Alice	19
2	Bob	21
4	Olivia	20

• df_2

id	major
1	Economics
2	Business Administration
3	Data Analytics

Which of the following R code correctly join the two related data.frames, df_1 and df_2, to produce the resulting data.frame shown below?

id	major	name	age
1	Economics	Alice	19
2	Business Administration	Bob	21
3	Data Analytics	NA	NA

1. df_1 |> left_join(df_2)
2. df_2 |> left_join(df_1)
3. Both a and b

Discussion

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