Library import
Lesson part
Group Info
Study group:
- Igor Estrop s197686
- Filip Dąbkowski s197712
- Maksymilian Balicki s198117
If there a problem with displaying the data tables, we are really sorry we had no idea which button to flip. Everything is the same as for the example .Rmd but it does not want to work.
set.seed(31415)student_data <- data.frame(
student_id = 1:50,
name = paste0("Student", 1:50),
midterm1 = sample(60:100, 50, replace = TRUE),
midterm2 = sample(60:100, 50, replace = TRUE),
final = sample(60:100, 50, replace = TRUE)
)std_long = student_data %>% gather("test", "mark", midterm1, midterm2, final)Group Homework
Generate a poorly formatted csv document with data from students exams
std_messy <- data.frame(
student_id = 1:50, # Students ID should range from 1 to 50
name_age = c("John_21", "Alice_20", "Bob_22", "Emily_23", "Michael_22"), # Those generic names will be used for students names and ages
exam_scores = c("midterm1_80,midterm2_85,final_75", "midterm1_75,midterm2_78,final_80", "midterm1_82,midterm2_80,final_85", "midterm1_88,midterm2_90,final_92", "midterm1_85,midterm2_86,final_88") # exam and score are mushed up together
)1. Separate the data into apropariete columns
Use separate to split columns by characters that are in between data that is needed
std_separated = std_messy %>%
separate(col = "name_age", into=c("name", "age"), sep="_") %>% # separate column $name and $age by character "_"
separate(col = "exam_scores", into = c("mid1_", "midterm1", "mid2_", "midterm2", "final_", "final"), sep="[_|,]") %>% # separate the second column into appropriate cols by any character matching Regexp
pivot_longer(cols = c(midterm1, midterm2, final), names_to = "exam", values_to = "mark") %>% # change the data format into Long, use column names as values for row
select(c(-mid1_, -mid2_, -final_)) # remove unnecessary columns2. Extend the data with more values
Use complete to fill in missing values, make sure there exist every posiible combination of Student&Age also making sure students attend exams but did not get graded
students_full = std_separated %>%
complete(name, age, exam, fill = list()) # for permutation on data use columns $name $age to get more values and to make sure students have exam fields filled in also use $exam in permutation3. Convert the data back into Wide format
Use pivot_wider to change values from col A to be used as column names with values from col B
student_wide_again = students_full %>%
pivot_wider(names_from=exam, values_from=mark) # convert the DF to have every exam as separate column4. Join columns name and age
Use unite to combine column $name $age to create a pseudo unique identifier for student
std_final = student_wide_again %>%
unite(student, name, age, sep="_") # join values of two columns into the third columns, values are joined with specified separatoar in between