id submission_type answer
tutorial-id none data-import
name question Hassan Ali
email question hassan.alisoni007@gmail.com
reading-data-from-a-file-1 question Documentation for package ‘readr’ version 2.1.5
reading-data-from-a-file-2 exercise setwd("E:/DataScience/") library(readr) read_csv("E:/DataScience/data.csv")
reading-data-from-a-file-3 exercise setwd("E:/DataScience/") library(readr) students <- read_csv("data.csv")
reading-data-from-a-file-4 exercise print(students)
reading-data-from-a-file-5 exercise setwd("E:/DataScience/") library(readr) students <- read_csv("data.csv", na = c("N/A", ""))
reading-data-from-a-file-6 exercise setwd("E:/DataScience/") library(readr) students <- read_csv("data.csv", na = c("N/A", "")) |> rename(student_id = "Student ID")
reading-data-from-a-file-7 exercise setwd("E:/DataScience/") library(janitor)
reading-data-from-a-file-8 exercise setwd("E:/DataScience/") library(janitor) students <- read_csv("data.csv", na = c("N/A", "")) |> clean_names()
reading-data-from-a-file-9 exercise setwd("E:/DataScience/") library(readr) library(dplyr) library(janitor) students <- read_csv("data.csv", na = c("N/A", "")) |> clean_names() |> mutate(meal_plan = factor(meal_plan))
reading-data-from-a-file-10 exercise setwd("E:/DataScience/") library(readr) library(dplyr) library(janitor) students <- read_csv("data.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 setwd("E:/DataScience/") library(readr) library(dplyr) library(janitor) students <- read_csv("data.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 setwd("E:/DataScience/") test_1 <- read_csv("test_1.csv")
reading-data-from-a-file-13 exercise setwd("E:/DataScience/") test_1 <- read_csv("test_1.csv", show_col_types = FALSE)
reading-data-from-a-file-14 exercise setwd("E:/DataScience/") test_2 <- read_csv("test_2.csv")
reading-data-from-a-file-15 exercise setwd("E:/DataScience/") test_3 <- read_csv("test_3.csv", col_names = FALSE)
reading-data-from-a-file-16 exercise setwd("E:/DataScience/") test_3 <- read_csv("test_3.csv", col_names = c("a", "b", "c"))
reading-data-from-a-file-17 exercise setwd("E:/DataScience/") test_3 <- read_csv( "test_3.csv", col_names = c("a", "b", "c"), col_types = cols( a = col_double(), b = col_double(), c = col_double() ) )
reading-data-from-a-file-18 exercise setwd("E:/DataScience/") test_5 <- read_csv("test_5.csv", na = ".")
reading-data-from-a-file-19 exercise setwd("E:/DataScience/") test_6 <- read_csv("test_6.csv", comment = "#")
reading-data-from-a-file-20 exercise setwd("E:/DataScience/") test_7 <- read_csv( "test_7.csv", col_types = cols( grade = col_integer(), student = col_character() ) )
reading-data-from-a-file-21 exercise setwd("E:/DataScience/") test_bad_names <- read_csv( "test_bad_names.csv", name_repair = "universal" )
reading-data-from-a-file-22 exercise setwd("E:/DataScience/") test_bad_names <- read_csv("test_bad_names.csv") |> clean_names()
reading-data-from-a-file-23 exercise setwd("E:/DataScience/") library(readr) read_csv( "test_bad_names.csv", name_repair = janitor::make_clean_names )
reading-data-from-a-file-24 exercise setwd("E:/DataScience/") library(readr) read_delim("delim_1.txt", delim = "|")
reading-data-from-a-file-25 exercise setwd("E:/DataScience/") library(readr) read_delim( "delim_2.txt", delim = "|", 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 setwd("E:/DataScience/") library(readr) simple_csv <- " x 10 . 20 30" read_csv(simple_csv) read_csv(simple_csv, col_types = list(x = col_double()))
controlling-column-types-5 exercise setwd("E:/DataScience/") library(readr) simple_csv <- " x 10 . 20 30" df <- read_csv(simple_csv, col_types = list(x = col_double())) problems(df)
controlling-column-types-6 exercise setwd("E:/DataScience/") library(readr) simple_csv <- " x 10 . 20 30" df <- read_csv(simple_csv, na = ".")
controlling-column-types-7 exercise another_csv <- " x,y,z 1,2,3"
controlling-column-types-8 exercise another_csv <- " x,y,z 1,2,3" setwd("E:/DataScience/") library(readr) read_csv(another_csv, col_types = cols_only(x = col_character()))
controlling-column-types-9 exercise setwd("E:/DataScience/") df <- read_csv("ex_2.csv", col_types = cols(.default = col_character())) problems(df)
controlling-column-types-10 exercise setwd("E:/DataScience/") library(readr) df <- read_csv("ex_2.csv", col_types = cols(.default = col_character()))
controlling-column-types-11 exercise setwd("E:/DataScience/") library(readr) library(dplyr) df <- read_csv("ex_2.csv", col_types = cols(.default = col_character())) |> mutate(a = parse_integer(a))
controlling-column-types-12 exercise setwd("E:/DataScience/") library(readr) library(dplyr) df <- read_csv("ex_2.csv", col_types = cols(.default = col_character())) |> mutate( a = parse_integer(a), b = parse_date(b, format = "%Y-%m-%d") # Corrected date format )
controlling-column-types-13 exercise setwd("E:/DataScience/") library(readr) df <- read_csv("ex_3.csv") problems(df)
controlling-column-types-14 exercise setwd("E:/DataScience/") library(readr) library(dplyr) read_csv("ex_3.csv") |> mutate(x = parse_date(x, "%d %B %Y"))
controlling-column-types-15 exercise setwd("E:/DataScience/") library(readr) library(dplyr) read_csv("ex_3.csv") |> mutate( x = parse_date(x, "%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 setwd("E:/DataScience/") library(readr) library(purrr) list.files("data", pattern = "similar", full.names = TRUE) |> map_dfr(~ read_csv(.x, na = ".", col_types = cols(.default = col_double())))
reading-data-from-multiple-fil-5 exercise setwd("E:/DataScience/") library(readr) library(purrr) list.files("data", pattern = "similar", full.names = TRUE) |> map_dfr(~ read_csv(.x, na = "."))
reading-data-from-multiple-fil-6 exercise setwd("E:/DataScience/") library(readr) library(purrr) list.files("data", pattern = "similar", full.names = TRUE) |> map_dfr(~ read_csv(.x, na = ".", show_col_types = FALSE))
reading-data-from-multiple-fil-7 exercise list.files("data", pattern = "sales")
reading-data-from-multiple-fil-8 exercise list.files("data", pattern = "sales", full.names = TRUE) |> map_dfr(read_csv)
reading-data-from-multiple-fil-9 exercise list.files("data", pattern = "sales", full.names = TRUE) |> map_dfr(~ read_csv(.x, 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
writing-to-a-file-3 exercise # Write the students2 data to a CSV file in the data directory write_csv(x = students2, file = "students2.csv")
writing-to-a-file-4 exercise students2_reloaded <- read_csv("data/students2.csv")
writing-to-a-file-5 exercise iris_p <- iris |> ggplot(aes(x = Sepal.Length, y = Sepal.Width)) + geom_jitter() + labs(title = "Sepal Dimensions of Various Species of Iris", x = "Sepal Length", y = "Sepal Width")
writing-to-a-file-6 exercise list.files("data")
writing-to-a-file-7 exercise read_rds("data/test_1.rds")
writing-to-a-file-8 exercise write_rds(mtcars, "data/test_2.rds")
writing-to-a-file-9 exercise list.files("data")
writing-to-a-file-10 exercise read_rds("data/test_2.rds")
writing-to-a-file-11 question What is the difference between Apache Arrow and Parquet?
data-entry-1 exercise tibble( x = c(1, 2, 5), y = c("h", "m", "g"), z = c(0.08, 0.83, 0.60) )
data-entry-2 exercise tribble( ~x, ~y, ~z, 1, "h", 0.08, 2, "m", 0.83, 5, "g", 0.60 )
minutes question 170