Now, save the app.py file and click on Always rerun in the web app (in the top-right corner); in this way, all the new lines of code will be immediately executed as soon as we save them. As shown in Figure 4.11, we have added the menu on the left-hand side of our web app. […]
App skeleton building First of all, we need a main function – a function that contains all the business logic of our app and the frontend too. This is the power of Streamlit – building the frontend directly inside Python code. There’s no need for different programming languages, files, and so on; everything is in […]
Adding the Text Analysis part In this part, we will use textblob, a Python library for processing textual data. It provides a simple API for diving into common NLP tasks such as part-of-speech tagging, sentiment analysis, classification, and more. For more details, visit pypi.org (the famous Python Package Index). As usual, we need to install […]
Adding the two basic functions Let’s start with the first basic function: Basic Info. Expanding Basic Info, we get Text Stats. In Chapter 4, among others, we imported the neattext package, which is very useful for our statistics as it has a function named word_stats. If you haven’t already imported it, it’s time to do […]
Adding a wordcloud Since the Basic Functions layer is now unbalanced, let’s add a beautiful wordcloud on the right, just to make everything much more symmetric. Please double-check that you already imported the Wordcloud library, as suggested in Chapter 4. This time, we can add another expander into the second column and write a few […]
