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R lessons (21/41)

R — Data Import

CSV files

# Base R
data <- read.csv("data.csv")
data <- read.csv("data.csv", stringsAsFactors = FALSE)

# readr
library(readr)
data <- read_csv("data.csv")
data <- read_tsv("data.tsv")
data <- read_delim("data.txt", delim = "|")

Excel files

library(readxl)

# Read Excel
data <- read_excel("data.xlsx")
data <- read_excel("data.xlsx", sheet = "Sheet1")
data <- read_excel("data.xlsx", range = "A1:D10")

# List sheets
excel_sheets("data.xlsx")

JSON files

library(jsonlite)

# Read JSON
data <- fromJSON("data.json")

# Write JSON
toJSON(data, pretty = TRUE, auto_unbox = TRUE)
write(toJSON(data, auto_unbox = TRUE), "output.json")

Database

library(DBI)
library(RSQLite)

# Connect
con <- dbConnect(SQLite(), "database.db")

# Read table
data <- dbReadTable(con, "users")

# Query
data <- dbGetQuery(con, "SELECT * FROM users WHERE age > 25")

# Disconnect
dbDisconnect(con)

Mini Practice

Write R code that:

  1. Reads a CSV file with readr
  2. Reads an Excel file with readxl
  3. Reads JSON with jsonlite
  4. Queries a SQLite database

Up Next

In the next lesson, you'll learn about Data Export — writing data to files.

Related Topics

Frequently Asked Questions about Data Import

What is Data Import in R?

Data Import is a fundamental concept in R. This lesson explains it step by step with clear examples, making it easy for beginners to understand.

How do I learn Data Import?

Start by reading the explanation above, then try the code examples. Practice by modifying the examples and experimenting with different values. Hands-on practice is the best way to learn Data Import.

Why is Data Import important in R?

Data Import is essential for R development. Understanding this concept will help you write better code and solve real-world problems more effectively.