Understanding readHTMLTable and Data Frame Column Names
In this article, we’ll delve into the intricacies of reading HTML tables using R’s readHTMLTable function. We’ll explore why it often returns data frame column names as integers rather than strings, and how to correct this issue.
Background on HTML Tables and Data Frames
When working with web scraping or data extraction, it’s not uncommon to encounter HTML tables that contain valuable information. R provides an easy-to-use readHTMLTable function for parsing these tables into data frames. However, the process can be nuanced due to differences in table structure, formatting, and encoding.
A data frame is a fundamental data structure in R that stores a collection of observations (rows) and variables (columns). When we read HTML tables using readHTMLTable, it automatically creates a data frame with the parsed information. However, this function often returns column names as integers instead of strings, which can lead to confusion when working with the data.
Strings-as-Factors Problem
One common issue when reading HTML tables is the presence of strings-as-factors (SAF) in the data frame. SAF occurs when stringsAsFactors is set to TRUE by default, causing all character columns to be converted to factors. Factors are a type of object in R that represent categorical variables.
In the context of our example, when we read the HTML table using readHTMLTable, it returns a data frame with column names as integers instead of strings. This is because the function automatically sets stringsAsFactors to TRUE, causing all character columns to be converted to factors.
library(XML)
url <- 'http://qpublic7.qpublic.net/ga_subdivison.php?county=ga_clarke&searchType=nbhd&numberValue=4025R&nameValue=&sectionValue=&townshipValue=&rangeValue=&startDate=01-1998&endDate=&startPrice=&endPrice=&startArea=&endArea=&startAcreage=&endAcreage=&saleQualification=All&saleVacant=All&propertyType=All&reasonType=All&start=0'
data <- readHTMLTable(url, header = FALSE, as.data.frame = TRUE, stringsAsFactors = FALSE)[[2]]
Fixing the Issue
To fix the issue of column names being integers instead of strings, we need to set stringsAsFactors to FALSE when reading the HTML table. We can do this by adding the stringsAsFactors = FALSE argument to the readHTMLTable function.
library(XML)
url <- 'http://qpublic7.qpublic.net/ga_subdivison.php?county=ga_clarke&searchType=nbhd&numberValue=4025R&nameValue=&sectionValue=&townshipValue=&rangeValue=&startDate=01-1998&endDate=&startPrice=&endPrice=&startArea=&endArea=&startAcreage=&endAcreage=&saleQualification=All&saleVacant=All&propertyType=All&reasonType=All&start=0'
data <- readHTMLTable(url, header = FALSE, as.data.frame = TRUE, stringsAsFactors = FALSE)[[2]]
Correcting Column Names
Once we’ve set stringsAsFactors to FALSE, we can correct the column names by using the gsub function to remove any spaces from the column names.
colnames(data) <- gsub(" ", "", colnames(data))
This step ensures that the column names are in the expected format and can be easily accessed and manipulated in our R code.
Modern Alternative: xml2
For modern versions of R, we can use the xml2 package to parse HTML tables. The xml2 package provides a more elegant and efficient way to work with HTML documents, including parsing tables.
To use xml2, we need to install and load the package first.
install.packages("xml2")
library(xml2)
We can then read the HTML table using the read_html function from the xml2 package.
url <- 'http://qpublic7.qpublic.net/ga_subdivison.php?county=ga_clarke&searchType=nbhd&numberValue=4025R&nameValue=&sectionValue=&townshipValue=&rangeValue=&startDate=01-1998&endDate=&startPrice=&endPrice=&startArea=&endArea=&startAcreage=&endAcreage=&saleQualification=All&saleVacant=All&propertyType=All&reasonType=All&start=0'
pg <- read_html(url)
csv2 <- html_table(html_nodes(pg, "table")[[1]], fill = TRUE)
Correcting Column Names with xml2
To correct the column names using xml2, we can use a similar approach as before.
colnames(csv2) <- gsub(" ", "", colnames(csv2))
Conclusion
In this article, we’ve explored the intricacies of reading HTML tables using R’s readHTMLTable function. We’ve discussed the issue of column names being integers instead of strings and provided a solution by setting stringsAsFactors to FALSE when reading the HTML table.
We’ve also introduced a modern alternative using the xml2 package, which provides a more elegant and efficient way to work with HTML documents, including parsing tables. By following the steps outlined in this article, you should be able to read HTML tables correctly and manipulate the data as needed.
Additional Resources
- readHTMLTable: The
readHTMLTablefunction from R’s base package. - xml2: The
xml2package, a modern alternative to reading HTML documents. - [gsub](https://stat.ethz.ch/R manual/html/stat.html#function.gsub): The
gsubfunction in R for removing spaces from strings.
Last modified on 2024-06-01