Data Wrangling Tools

Most data analysts spend the majority of their time wrangling data instead of analyzing data. Data wranglers are frequently employed if they possess knowledge of a statistical language such as R or Python as well as knowledge of SQL, Scala, PHP, and other programming languages. Alongside these skills, it's advantageous to know the tools frequently used in data wrangling. Below is a list of such commonly used tools.

Tabula

Tabula is a tool that extracts data from .pdf files. Tabula provides a simple, user-friendly interface for extracting data into a CSV or Microsoft Excel spreadsheet. Tabula is available for Mac, Windows, and Linux.

Talend

Talend is a collection of tools for data wrangling, data preparation, and data cleansing. It's a browser-based platform with a simple point-and-click interface that's ideal for businesses. This simplifies data manipulation far more than it would be with heavy code-based programmers.

Parsehub

If you're new to Python or are having trouble with it, Parsehub is a good place to start. Parsehub is an online scraping and data extraction tool that has a user-friendly desktop interface for extracting data from a variety of interactive websites. You can simply click on the data you want to collect and extract it into JSON format, an Excel spreadsheet, or API forms without having to use any code. The fact that Parsehub includes a graphical user interface is its key selling point for newcomers.

Scrapy

Scrapy is a popular web scraping tool that is more complicated than code-free alternatives like Parsehub, but Scrapy is much more versatile. It's a Python-based open-source web scraping framework that's completely free to use. Scrapy is lightweight and scalable which makes it ideal for a wide range of projects.