id | submission_type | answer
--- | --- | ---
tutorial-id | none | data-import
name | question | Yashi Gupta
email | question | ohyeahshe@gmail.com
reading-data-from-a-file-1 | question | Documentation for package ‘readr’ version 2.1.5
reading-data-from-a-file-2 | exercise | library(readr) students <- read_csv(file = "data/students.csv")
reading-data-from-a-file-3 | exercise | library(readr) students <- read_csv(file = "data/students.csv")
reading-data-from-a-file-4 | exercise | print(students)
reading-data-from-a-file-5 | exercise | library(readr) students <- read_csv(file = "data/students.csv", na = c("N/A", ""))
reading-data-from-a-file-6 | exercise | library(dplyr) students <- students %>% rename(student_id = `Student ID`)
reading-data-from-a-file-7 | exercise | library(janitor)
reading-data-from-a-file-8 | exercise | library(readr) library(dplyr) library(janitor) students <- read_csv( file = "data/students.csv", na = c("N/A", "") ) %>% clean_names()
reading-data-from-a-file-9 | exercise | library(readr) library(dplyr) library(janitor) students <- read_csv( file = "data/students.csv", na = c("N/A", "") ) %>% clean_names() %>% mutate(meal_plan = factor(meal_plan))
reading-data-from-a-file-10 | exercise | students <- read_csv( file = "data/students.csv", na = c("N/A", "") ) %>% clean_names() %>% mutate( meal_plan = factor(meal_plan), age = if_else(age == "five", "5", age) )
reading-data-from-a-file-11 | exercise | library(readr) library(dplyr) library(janitor) students <- read_csv( file = "data/students.csv", na = c("N/A", "") ) %>% clean_names() %>% mutate( meal_plan = factor(meal_plan), age = if_else(age == "five", "5", age), age = parse_number(age) )
reading-data-from-a-file-12 | exercise | library(readr) test_1 <- read_csv(file = "data/test_1.csv")
reading-data-from-a-file-13 | exercise | library(readr) test_1 <- read_csv(file = "data/test_1.csv", show_col_types = FALSE)
reading-data-from-a-file-14 | exercise | library(readr) test_2 <- read_csv(file = "data/test_2.csv", skip = 2, show_col_types = FALSE)
reading-data-from-a-file-15 | exercise | library(readr) test_3 <- read_csv(file = "data/test_3.csv", col_names = FALSE, show_col_types = FALSE)
reading-data-from-a-file-16 | exercise | library(readr) test_3 <- read_csv( file = "data/test_3.csv", col_names = c("a", "b", "c"), show_col_types = FALSE )
reading-data-from-a-file-17 | exercise | library(readr) test_3 <- read_csv( file = "data/test_3.csv", col_names = c("a", "b", "c"), col_types = cols( a = col_double(), b = col_double(), c = col_double() ), show_col_types = FALSE )
reading-data-from-a-file-18 | exercise | library(readr) test_5 <- read_csv( file = "data/test_5.csv", na = "." )
reading-data-from-a-file-19 | exercise | library(readr) test_6 <- read_csv( file = "data/test_6.csv", comment = "#" )
reading-data-from-a-file-20 | exercise | library(readr) test_7 <- read_csv( file = "data/test_7.csv", col_types = cols( grade = col_integer(), student = col_character() ) )
reading-data-from-a-file-21 | exercise | library(readr) test_bad_names <- read_csv( file = "data/test_bad_names.csv", name_repair = "universal" )
reading-data-from-a-file-22 | exercise | library(readr) library(janitor) library(dplyr) test_bad_names <- read_csv("data/test_bad_names.csv") %>% clean_names()
reading-data-from-a-file-23 | exercise | library(readr) test_bad_names <- read_csv( file = "data/test_bad_names.csv", name_repair = janitor::make_clean_names )
reading-data-from-a-file-24 | exercise | delim_1 <- read_delim( file = "data/delim_1.txt", delim = "|", comment = "##", show_col_types = FALSE )
reading-data-from-a-file-25 | exercise | delim_2 <- read_delim( file = "data/delim_2.txt", delim = "|", comment = "##", col_types = cols( date = col_date(), population = col_integer(), town = col_character() ) )
controlling-column-types-1 | exercise | read_csv(" a, b, c 1, 2, 3")
controlling-column-types-2 | exercise | read_csv(" logical,numeric,date,string TRUE,1,2021-01-15,abc false,4.5,2021-02-15,def T,Inf,2021-02-16,ghi ")
controlling-column-types-3 | exercise | simple_csv <- " x 10 . 20 30" read_csv(simple_csv)
controlling-column-types-4 | exercise | library(readr) simple_data <- read_csv( file = "data/simple_csv.csv", col_types = list(x = col_double()) )
controlling-column-types-5 | exercise | library(readr) df <- read_csv( file = "data/simple_csv.csv", col_types = list(x = col_double()) ) problems(df)
controlling-column-types-6 | exercise | library(readr) df <- read_csv( file = "data/simple_csv.csv", na = "." )
controlling-column-types-7 | exercise | another_csv <- " x,y,z 1,2,3"
controlling-column-types-8 | exercise | library(readr) df <- read_csv( file = "data/another_csv.csv", col_types = cols_only(x = col_character()) )
controlling-column-types-9 | exercise | read_csv("data/ex_2.csv")
controlling-column-types-10 | exercise | library(readr) df <- read_csv( file = "data/ex_2.csv", col_types = cols(.default = col_character()) )
controlling-column-types-11 | exercise | library(readr) library(dplyr) df <- read_csv( file = "data/ex_2.csv", col_types = cols(.default = col_character()) ) %>% mutate(a = parse_integer(a))
controlling-column-types-12 | exercise | library(readr) library(dplyr) df <- read_csv( file = "data/ex_2.csv", col_types = cols(.default = col_character()) ) %>% mutate( a = parse_integer(a), b = parse_date(b, format = "%Y%M%D") )
controlling-column-types-13 | exercise | library(readr) df <- read_csv("data/ex_3.csv") problems(df)
controlling-column-types-14 | exercise | library(readr) library(dplyr) df <- read_csv("data/ex_3.csv") %>% mutate(x = parse_date(x, format = "%d %B %Y"))
controlling-column-types-15 | exercise | library(readr) library(dplyr) df <- read_csv("data/ex_3.csv") %>% mutate( x = parse_date(x, format = "%d %B %Y"), z = parse_number(z) )
reading-data-from-multiple-fil-1 | exercise | list.files("data")
reading-data-from-multiple-fil-2 | exercise | list.files("data", pattern = "similar")
reading-data-from-multiple-fil-3 | exercise | list.files("data", pattern = "similar", full.names = TRUE)
reading-data-from-multiple-fil-4 | exercise | list.files("data", pattern = "similar", full.names = TRUE) |> read_csv()
reading-data-from-multiple-fil-5 | exercise | list.files("data", pattern = "similar", full.names = TRUE) |> read_csv(NA=".")
reading-data-from-multiple-fil-6 | exercise | list.files("data", pattern = "similar", full.names = TRUE) |> read_csv(na=".",show_col_types=FALSE)
reading-data-from-multiple-fil-7 | exercise | list.files(path ="data", pattern = "sales")
reading-data-from-multiple-fil-8 | exercise | list.files(path = "data", pattern = 'sales', full.names = TRUE) |> read_csv()
reading-data-from-multiple-fil-9 | exercise | list.files(path = "data", pattern = 'sales', full.names = TRUE) |> read_csv(id = "file")
writing-to-a-file-1 | exercise | students2 <- students |> clean_names() |> mutate( meal_plan = factor(meal_plan), age = if_else(age == "five", "5", age), age = parse_number(age) ) students2
writing-to-a-file-2 | exercise | students2
data-entry-1 | exercise | library(tibble) df <- tibble( x = c(1, 2, 5), y = c("h", "m", "g"), z = c(0.08, 0.83, 0.60) )
data-entry-2 | exercise | library(tibble) df <- tribble( ~x, ~y, ~z, 1, "h", 0.08, 2, "m", 0.83, 5, "g", 0.60 )
minutes | question | 100