18 Importing

18.1 Setup

library(tidyverse)
#> ── Attaching core tidyverse packages ──── tidyverse 2.0.0 ──
#> ✔ dplyr     1.1.3     ✔ readr     2.1.4
#> ✔ forcats   1.0.0     ✔ stringr   1.5.0
#> ✔ ggplot2   3.4.4     ✔ tibble    3.2.1
#> ✔ lubridate 1.9.3     ✔ tidyr     1.3.0
#> ✔ purrr     1.0.2     
#> ── Conflicts ────────────────────── tidyverse_conflicts() ──
#> ✖ dplyr::filter() masks stats::filter()
#> ✖ dplyr::lag()    masks stats::lag()
#> ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
library(readxl)
library(WDI)
library(owidR)
library(wid)

18.2 EDA by R Studio: Step 3 - Importing Data

Assign a name you can recall easily when you import data. You may need to reload the data with options.

3.1. Use a package:

  • WDI, wir, eurostat, etc/
  • `wdi_shortname <- WDI(indicator = “indicator’s name”, … )
  • Store the data and use it: write_csv(wdi_shortname, "./data/wdi_shortname.csv")
  • wdi_shortname <- read_csv("./data/wdi_shortname.csv")

3.2. Use readr to read from data, your data folder

  • df1_shortname <- read_csv("./data/file_name.csv")

3.3. Use readr to read using the url of the data

  • df2_shortname <- read_csv("url_of_the_data")
  • Store the data and use it: write_csv(df2_shortname, "./data/df2_shortname.csv")
  • df2_shortname <- read_csv("./data/df2_shortname.csv")

3.5. Use readxl to read Excel data. Add library(readxl) in the setup and run.

  • df4 <- read_excel("./data/file_name.xlsx", sheet = 1)

References: Cheat Sheet - readr, readr, readxl