Introduction to Importing Data in R

Importing data is the first step in any data analysis project. R allows you to import data from various sources such as CSV, Excel, and databases.

Importing CSV Files

CSV files are one of the most common formats for storing data. You can import them using the read.csv() function.

data <- read.csv('data.csv')

Viewing Imported Data

Once you import data, you can inspect it using functions like head() and summary().

head(data)
summary(data)

Importing Excel Files

To import Excel files, you need to use the readxl package.

install.packages('readxl')
library(readxl)
data <- read_excel('data.xlsx')

Importing Data from Databases

R allows you to connect to databases using the DBI and RSQLite packages.

install.packages('DBI')
library(DBI)
con <- dbConnect(RSQLite::SQLite(), 'my_database.db')

Importing JSON Data

JSON files can be imported using the jsonlite package.

install.packages('jsonlite')
library(jsonlite)
data <- fromJSON('data.json')

Handling Missing Data

Missing values in imported data are represented as NA. You can check for missing values using is.na().

sum(is.na(data))

Saving Data to CSV

You can save data frames to CSV using write.csv().

write.csv(data, 'output.csv')

Summary

In this lesson, you learned:

• How to import data from CSV, Excel, JSON, and databases.
• How to inspect imported data.
• How to handle missing values.