Here are the 5 lesser-known Python libraries worth exploring, like, streamlit, Rich, Text blob, etc

We couldn't function without well-known data science libraries like streamlit and Rich, but there are also several lesser-known libraries that can help you out when working on a project.

1. Streamlit: Want to quickly and easily create engaging and beautiful web applications? With just a few lines of Python code, you can create and distribute data-centric web apps with Streamlit. Leave the headache of using HTML, CSS, and JavaScript behind!

2. Rich: Tired of the console output in plain text? It is simpler to read and comprehend logs, data, and error messages when you develop command-line interfaces using Rich's gorgeous formatting and vibrant colors.

3. TextBlob: Use TextBlob to dive into natural language processing with ease! With little setup required, this straightforward package provides functions including part-of-speech tagging, language translation, and sentiment analysis.

4. PyCaret: With PyCaret, a low-code package that automates the process of building, fine-tuning, and deploying ML models, you can speed up your machine-learning workflow. Spend more time studying the outcomes and less time coding!

5. Dash: Dash is a potent framework for web apps that may be used to create analytical and interactive ones. You may easily generate unique, feature-rich visuals using it because it interfaces with well-known data visualization frameworks like Plotly.

Take advantage of these fantastic Python libraries. Test them out, and then tell me which one you like! Leave a comment below if you've utilized any of them before or if you know of any other undiscovered treasures! Let's continue to explore Python's infinite possibilities together.