#343: Do Excel things, get notebook Python code with Mito

#343: Do Excel things, get notebook Python code with Mito

Here's a question: What's the most common way to explore data? Would you say pandas and matplotlib? Maybe you went more general and said Jupyter notebooks. How about Excel, or Google Sheets, or Numbers, or some other spreadsheet app? Yeah, my bet is on Excel. And while it has many drawbacks, it makes exploring tabular data very accessible to many people, most of whom aren't even developers or data scientists. On this episode, we're talking about a tool called Mito. This is an add-in for Jupyter notebooks that injects an Excel-like interface into the notebook. You pass it data via a pandas dataframe (or some other source) and then you can explore it as if you're using Excel. The cool thing is though, just below that, it's writing the pandas code you'd need to do to actually accomplish that outcome in code.

Episoder(544)

#529: Computer Science from Scratch

#529: Computer Science from Scratch

A lot of people building software today never took the traditional CS path. They arrived through curiosity, a job that needed automating, or a late-night itch to make something work. This week, David ...

3 Des 20251h 17min

#528: Python apps with LLM building blocks

#528: Python apps with LLM building blocks

In this episode, I’m talking with Vincent Warmerdam about treating LLMs as just another API in your Python app, with clear boundaries, small focused endpoints, and good monitoring. We’ll dig into patt...

30 Nov 20251h 16min

#527: MCP Servers for Python Devs

#527: MCP Servers for Python Devs

Today we’re digging into the Model Context Protocol, or MCP. Think LSP for AI: build a small Python service once and your tools and data show up across editors and agents like VS Code, Claude Code, an...

10 Nov 20251h 6min

#526: Building Data Science with Foundation LLM Models

#526: Building Data Science with Foundation LLM Models

Today, we’re talking about building real AI products with foundation models. Not toy demos, not vibes. We’ll get into the boring dashboards that save launches, evals that change your mind, and the shi...

1 Nov 20251h 7min

#525: NiceGUI Goes 3.0

#525: NiceGUI Goes 3.0

Building a UI in Python usually means choosing between "quick and limited" or "powerful and painful." What if you could write modern, component-based web apps in pure Python and still keep full contro...

27 Okt 20251h 17min

#524: 38 things Python developers should learn in 2025

#524: 38 things Python developers should learn in 2025

Python in 2025 is different. Threads really are about to run in parallel, installs finish before your coffee cools, and containers are the default. In this episode, we count down 38 things to learn th...

20 Okt 20251h 9min

#523: Pyrefly: Fast, IDE-friendly typing for Python

#523: Pyrefly: Fast, IDE-friendly typing for Python

Python typing got fast enough to feel invisible. Pyrefly is a new, open source type checker and IDE language server from Meta, written in Rust, with a focus on instant feedback and real-world DX. Toda...

13 Okt 20251h 7min

#522: Data Sci Tips and Tricks from CodeCut.ai

#522: Data Sci Tips and Tricks from CodeCut.ai

Today we’re turning tiny tips into big wins. Khuyen Tran, creator of CodeCut.ai, has shipped hundreds of bite-size Python and data science snippets across four years. We dig into open-source tools you...

6 Okt 20251h 9min

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