Simple, easy to use package with minimalistic code to write with a ton of features to leverage (we all want that, right?). CleanText is an open-source python package (common for almost every package we see) specifically for cleaning raw data (as the name suggests and I believe you might have guessed). This blog is about such a new library (released only last year, January 2020) called CleanText. Using NLTK and Regex is known all over the community so much that we often undermine what else is really there that we can use for this hefty task. The Python Community hosts a ton of libraries to make data orderly and umm…legible? This can vary from never-ending data frames to stylizing them or whether it be analyzing datasets. The task is to make this crucial and vital task more bearable (at least a little more bearable). Yeah, it’s enjoyable.īut we know that data cleaning is time-consuming, right? Also, lots of tools have popped up from time to time. Unfortunately, approximately 50-55% find it quite enjoyable. So messy that in a survey, it was mentioned that data scientists spend around 60% of their time cleaning data. Everyone has different opinions, but they can’t help but agree on this fact! What else is messy? Data !! Lots and lots of data which we collect, scrape or extract from numerous sources. We will look for a word Vilnius and then extract the text before it to the new field.The real world is a messy, messy place. Let's name it ExtractedShippingProviders and thats it. To solve this select Find all text before the chosen matching text or offset and select Vilnius.Īll you have to do is give the new field a name. With every order there is a shippingProvider information attached. Imagine you are working with a list or orders. You can use one of these options:įind all text after the chosen matching text or offsetįind all text before the chosen matching text or offsetįind a set length of text after the chosen matching text or offsetįind a set length of text before the chosen matching text or offset. You may use this to get various names, emails or to remove any unwanted items. If you want to learn more, here is our getting started guide.Įxtracts a portion of the text based on your condition. On your left, you can choose which fields you want to modify, and on your right, you can see the result in real-time. You can add as many of these as you want. We would like to draw you attention to the builder image below. The second part of the process is what this app is all about. For example, it might be a form submit or a new order request.įinally, you choose whether to pass that data through Zapier or your own API endpoint. You select a trigger and the information that comes with that trigger. You set up the no-code app that you want to automate. The UI is designed to be similar with the tools use already use. Let's take a quick look at the builder itself. It seamlessly integrates into the workflow by reshaping the data as it travels to the automation platform. Reshape API works as a mediator between your tools helping them to communicate. What happens if the API Response you get is not what you expected? How do you change the text casing or remove an unwanted trailing character? Or even parse email addresses? Just pass the data along, and automagically, both tools connect. No problem! Automation tools like Zapier or Integromat can help. For example, it might be lacking a good email builder to send transactional emails. However, you run into a problem that the tool lacks some functionality. The design is sleek, and the animations are smooth. It might be in Squarespace or Webflow, or some other builder. Imagine you are building your next no-code project.
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