Web Scraping with R: Selecting Specific Words from an HTML Webpage and Appending to a Data Frame
In this article, we will explore how to select specific words from an HTML webpage using the rvest package in R. We will also discuss how to append these selected words to a data frame.
Introduction
HTML webpages are often structured in a way that makes it difficult to extract specific information. However, with the use of web scraping techniques and libraries like rvest, it is possible to extract data from HTML webpages programmatically. In this article, we will focus on selecting specific words from an HTML webpage and appending them to a data frame.
Prerequisites
Before we begin, make sure you have the following libraries installed:
rvestxml2purrrdplyr
You can install these libraries using the install.packages() function in R.
Step 1: Inspecting the HTML Webpage
To start web scraping, we need to inspect the HTML structure of the webpage. We can use the read_html() function from the rvest package to read the HTML content of the webpage.
library(rvest)
url <- "https://www.basketball-reference.com/boxscores/201410280LAL.html"
webpage <- read_html(url)
Step 2: Identifying the Relevant Nodes
Once we have inspected the HTML structure, we need to identify the nodes that contain the relevant information. In this case, we are interested in selecting team names from the strong tags.
abbr <- webpage %>%
html_nodes('strong') %>%
html_text() %>%
.[5:6]
In this code snippet, we use the html_nodes() function to select all strong nodes on the webpage. We then convert the HTML text within these nodes to plain text using the html_text() function. Finally, we extract the relevant team names from the last two elements of the vector.
Step 3: Extracting Team Names
To extract the team names from the selected strong tags, we need to identify the specific words that contain the team names.
team_names <- abbr
In this code snippet, we simply assign the extracted team names to a new variable called team_names.
Step 4: Appending Team Names to Data Frames
To append the selected team names to our data frames, we can use the dplyr package.
library(dplyr)
away_team <- awaybas %>%
mutate(team = abbr) %>%
filter(team != "Team")
In this code snippet, we use the mutate() function to add a new column called team to our data frame. We then use the filter() function to exclude rows where the team name is not equal to “Team”.
Step 5: Merging Data Frames
To merge the updated data frames with the original data, we can use the merge() function.
merged_data <- merge(away_team, awaybas, by = c("team", "Player"))
In this code snippet, we use the merge() function to join our updated data frame with the original data frame. The resulting merged data frame will contain both the team names and player information.
Conclusion
In this article, we have explored how to select specific words from an HTML webpage using the rvest package in R. We have also discussed how to append these selected words to a data frame using the dplyr package. By following these steps, you can extract relevant information from HTML webpages and work with it in your R projects.
Example Use Cases
- Extracting team names from sports websites
- Scraping data from e-commerce websites
- Web scraping for market research
Code Repository
You can find the complete code repository for this article on GitHub at https://github.com/username/web-scraping-r.
Last modified on 2024-02-25