18 Importing
18.1 Setup
library(tidyverse)
#> ── Attaching core tidyverse packages ──── tidyverse 2.0.0 ──
#> ✔ dplyr 1.1.2 ✔ readr 2.1.4
#> ✔ forcats 1.0.0 ✔ stringr 1.5.0
#> ✔ ggplot2 3.4.2 ✔ tibble 3.2.1
#> ✔ lubridate 1.9.2 ✔ tidyr 1.3.0
#> ✔ purrr 1.0.1
#> ── 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)