Learning How to Import Data

Load Packages

Haven enables R to read and write various data formats used by other statistical packages by wrapping the fantastic ReadStat C library written by Evan Miller.

https://www.rdocumentation.org/packages/haven/versions/2.5.1

if (!require(haven)){
  install.packages("haven", dependencies = TRUE)
  require(haven)
}

Loading required package: haven

The tidyverse makes it easy for us to tidy, clean, manipulate and rearrange our data.

https://www.rdocumentation.org/packages/tidyverse/versions/1.3.2

if (!require(tidyverse)){
  install.packages("tidyverse", dependencies = TRUE)
  library(tidyverse)
}

Loading required package: tidyverse

── Attaching packages ─────────────────────────────────────── tidyverse 1.3.2 ──
✔ ggplot2 3.4.0      ✔ purrr   1.0.1 
✔ tibble  3.1.8      ✔ dplyr   1.0.10
✔ tidyr   1.2.1      ✔ stringr 1.5.0 
✔ readr   2.1.3      ✔ forcats 0.5.2 
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()

Simplifies the creation of .xlsx files by providing a high level interface to writing, styling and editing worksheets. Through the use of Rcpp, read/write times are comparable to the xlsx and XLConnect packages with the added benefit of removing the dependency on Java.

https://www.rdocumentation.org/packages/openxlsx/versions/4.2.5.1

if (!require(openxlsx)){
  install.packages("openxlsx", dependencies = TRUE)
  library(openxlsx)
}

Loading required package: openxlsx

Import Data

dataset.xlsx <- read.xlsx("Harry Potter Data.xlsx")

dataset.csv <- read_csv("Harry Potter Data.csv")

Rows: 124 Columns: 90
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
chr (90): StartDate, EndDate, Status, IPAddress, Progress, Duration (in seco...

ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

dataset.spss <- read_sav("Harry Potter Data.sav")

dataset.spss.web <- read_sav("https://osf.io/download/kd4ej/")

Bonus Points

dataset.csv.web <- read_csv("https://osf.io/download/wtghz/")

Rows: 124 Columns: 90
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
chr (90): StartDate, EndDate, Status, IPAddress, Progress, Duration (in seco...

ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

dataset.xlsx <- read.xlsx("https://osf.io/download/7fz89/")