Downloading Images from a Website with R and rvest

In this article, we will learn how to use R and the rvest package to download all the images from a Wikipedia page.

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Overview

The goal is to extract the names, breed groups, local names, and image URLs for all dog breeds listed on this Wikipedia page. We will store the image URLs, download the images and save them to a local folder.

Here are the key steps we will cover:

1. Load required packages
2. Send HTTP request to fetch the Wikipedia page
3. Parse the page HTML using rvest
4. Find the table with dog breed data using a CSS selector
5. Iterate through the table rows
6. Extract data from each column
7. Download images and save locally
8. Print/process extracted data

Let's go through each of these steps in detail.

Packages

We need these packages:

library(rvest)
library(xml2)

Send HTTP Request

To download the web page:

url <- "<https://commons.wikimedia.org/wiki/List_of_dog_breeds>"

page <- rvest::read_html(url)

rvest provides the read_html() function to fetch the page.

Parse HTML

The returned page object contains parsed HTML.

Find Breed Table

We use a CSS selector to find the table element:

table <- page %>% html_nodes("table.wikitable.sortable")

This selects the

Iterate Through Rows

We loop through the rows like this:

table %>%
  html_nodes("tr") %>%
  .[. != 1] %>%
  html_nodes("td, th") %>%
  {

    # Extract data

  }

We filter to skip the header row.

Extract Column Data

Inside the loop, we extract the column data:

name <- html_text(.[[1]])
group <- html_text(.[[2]])

local_name <- html_text(.[[3]])
if(local_name == ""){
  local_name <- NA
}

img_url <- xml_attr(.[[4]], "src")

We use html_text() and xml_attr() to extract elements.

Download Images

To download and save images:

if(!is.na(img_url)){

  img <- GET(img_url)
  writeBin(img, paste0("dog_images/",name,".jpg"))

}

We use the GET() function to download the image and write it to a file.

Store Extracted Data

We store the extracted data in vectors:

names <- c(names, name)
groups <- c(groups, group)
local_names <- c(local_names, local_name)
photos <- c(photos, img_url)

The vectors can then be processed as needed.

And that's it! Here is the full code:

# Load packages
library(rvest)
library(xml2)

# Vectors to store data
names <- character()
groups <- character()
local_names <- character()
photos <- character()

# Fetch HTML
url <- "<https://commons.wikimedia.org/wiki/List_of_dog_breeds>"
page <- rvest::read_html(url)

# Find table
table <- page %>% html_nodes("table.wikitable.sortable")

# Iterate rows
table %>%
  html_nodes("tr") %>%
  .[. != 1] %>%
  html_nodes("td, th") %>%
  {

    # Extract data
    name <- html_text(.[[1]])
    group <- html_text(.[[2]])

    local_name <- html_text(.[[3]])
    if(local_name == "") {
      local_name <- NA
    }

    img_url <- xml_attr(.[[4]], "src")

    # Download image
    if(!is.na(img_url)){

      img <- GET(img_url)
      writeBin(img, paste0("dog_images/",name,".jpg"))

    }

    # Store data
    names <- c(names, name)
    groups <- c(groups, group)
    local_names <- c(local_names, local_name)
    photos <- c(photos, img_url)

  }

This provides an R solution using rvest to scrape data and images from HTML tables. The same approach can apply to many websites.

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