Web Scraping With Python vs R: Which Is Better?

Many programming languages are being used for data scraping. But web scraping with Python and R are gaining lot of tration in the field of data science. Each language has its unique features, perks as well as some limitations. 

In this article, we will discuss pros and cons of web scraping with Python vs R? So you decide which is better and you can choose a programming language that suits you.

What Is Web Scraping?

Before we get into Web Scraping Python vs R comparison, let us first understand what web scraping is.

Web scraping is also called data extraction or web harvesting. As the name implies, it’s about extracting data from websites. Many web scraping softwares are also available that direct access to the website via a browser. They also get access via Hypertext Transfer Protocol (HTTP) 

Web scraping can be done manually, but it’s a time-consuming process. This is why it is better to use automated Web scraping Bots and Web crawlers. It does work efficiently and easily without any time delay. The automated web scrapers extract the required data from a website. Copy and paste it to the excel spreadsheet or CSV file. This data can then be used for further analysis. 

Web scraping can be done for various purposes. Like searching product prices and their comparison. Copying contact details of local and international companies. Understanding Product reviews to make their product better. Or to see what’s trending in the market etc. 

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Web Scraping With Python

Python is considered to be one of the best web scraping languages.

Its programming functionality is high level. It allows users to make desktop (Graphical User Interface) GUI and web applications. It has simple syntax rules so the codebase is easy to understand. 

Python is a hub of useful features, some of which are:

Easy to use: Python is pretty easy to code. You do not need to add any braces or semicolons in Python coding. It is an ideal programming language for beginners or for those into web scraping. 

Rich in Libraries: Python is supported by a large number of libraries. It includes Numpy, Pandas, and Matlolotlib. It is ideal for both data scraping and data manipulation. 

Dynamically typed: Using python for web scraping, you don’t need to define types for variables. You can use the variables whenever it is required.

The syntax is Understandable: Python syntax is easy to understand. Reading Python code is very simple to read. 

Small codes: Programming in Python, you can write small codes for conducting voluminous web scraping. The purpose of automated web scrapers is to save time and human energy. If you will spend maximum time writing the code. The whole purpose becomes useless. 

Python Community: Usually beginners get stuck away while writing code. In the case of coding Python, there is a large online community available. You can ask for help whenever you want. In fact, if you search a little someone might already have had your kind of problem. And the solution is already there. 

Related: Web Scraping Node JS vs Python

Web Scraping With R

Just like Python, R is a web scraping programming language. It is also used by statisticians. It allows data scrapers to collect and analyze data. It includes mathematics and statistics formulas. R is rich with functions that make data mining easier. R packages include RCrawler and RVest. Both of them are used for data mining.

For R web scraping. First, you access the website with R, Then you instruct R, what data to select for extraction. Then use R to convert it into a readable format. 

Along with data scraping, R is also used for machine learning. It can also be utilized in the field of scientific computing. 

Similarities in Web Scraping With Python Vs R

• They are open-source programming languages.
• They both have large communities. 
• The catalog is being updated with new libraries and tools.
• They both extract data from online sources.

Differences Between Web Scraping With Python Vs R

• R focuses on statistical analysis. Whereas Python focuses on general purposes. 
• R is functional and Python is object-oriented. 
• Python is based on packages and R has in-built data analysis. 
• Web scraping is much easier in Python than R. 

Pros and Cons of Web Scraping With R

Pros

•  Open Source: R is an open-source programming language. Users don’t need to pay a fee or get a license. Users can also customize their packages, hence contributing to its development.
• Organized Data: With R, you can arrange the data in an organized form. 
• Rich Source of Packages: R has more than 10,000 packages.

Cons

• Weak Origin: R does not support dynamic graphics or 3D. 
•  High Memory Usage: R uses a lot of memory in comparison to Python. This is why Python is better for web scraping than R.
• Complicated Language: R is much more difficult to learn for beginners.

Pros & Cons Of Web Scraping With Python

Pros

•  Easy To Use: Python is very easy to learn.
• Community Support: Python has a large online community. So you can get help from the community if you get confused while coding. 
•  Open Source: It is an open-source coding language. 
• Rich in Libraries: Python has many libraries for web and game development.

Cons 

• Speed: Python is slower than R
• Threading Problem: Python has GIL (Global Interpreter Lock) so you will experience slow threading. 
• Not Mobile Friendly: Python doesn’t support iOS or Android.

Conclusion

So,  who wins the battle? Is web scraping better with Python or R?

If you want an easy-to-read coding language. A language that has a large collection of libraries. Then choose Python for web scraping. Yet, do remember that Python has no support for iOS or android.

Whereas if you want a data-specific language. Web scraping R is better than Python. 

We hope this article, Python Vs R web scraping comparison will help you choose a better option. 

Related: Web Scraping vs APIs