Streamlit 101: The fundamentals of a Python data app

1. streamlit101

   1 1 1 9.3 Python

   

   In this blog post, we'll cover the fundamentals of Streamlit, how it works, and how you can get started with it. You can find the example code for this post here or watch the step-by-step video tutorial on YouTube.

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3. population-dashboard

   2 1 188 9.0 Jupyter Notebook

   A dashboard web app template built in Python using Streamlit.

   

   @st.cache_data def load_data(): return pd.read_csv("https://github.com/dataprofessor/population-dashboard/raw/master/data/us-population-2010-2019-reshaped.csv", index_col=0

4. Pandas

   3 425 45,388 9.9 Python

   Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

   

   It's compatible with a wide range of data libraries, including Pandas, NumPy, and Altair. Streamlit integrates with all the latest tools in generative AI, such as any LLM, vector database, or various AI frameworks like LangChain, LlamaIndex, or Weights & Biases. Streamlit’s chat elements make it especially easy to interact with AI so you can build chatbots that “talk to your data.”

5. NumPy

   4 301 29,483 10.0 Python

   The fundamental package for scientific computing with Python.

   

   It's compatible with a wide range of data libraries, including Pandas, NumPy, and Altair. Streamlit integrates with all the latest tools in generative AI, such as any LLM, vector database, or various AI frameworks like LangChain, LlamaIndex, or Weights & Biases. Streamlit’s chat elements make it especially easy to interact with AI so you can build chatbots that “talk to your data.”

6. Altair

   5 46 9,766 9.1 Python

   Declarative visualization library for Python

   

   It's compatible with a wide range of data libraries, including Pandas, NumPy, and Altair. Streamlit integrates with all the latest tools in generative AI, such as any LLM, vector database, or various AI frameworks like LangChain, LlamaIndex, or Weights & Biases. Streamlit’s chat elements make it especially easy to interact with AI so you can build chatbots that “talk to your data.”

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