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40+ live apps, open data APIs, MCP servers, and 200+ guides - more than anyone wants to click through. Point your AI here and it reads the whole map and does the work: finds the tool, pulls the data, runs the analysis, and hands you the links.

Here for the open-source code? Your agent finds the right repo for you - and can even clone and deploy it.

Prefer to explore on your own? Go right ahead.

Paste this to Claude Code, Codex, or any AI agent:
Go to tigzig.com and read tigzig.com/llms.txt. It is a practitioner toolkit - 40+ analytics apps, open no-auth data APIs, MCP servers, open-source repos (github.com/amararun), and 200+ build guides. Help me [your task]. Surface the exact links; where there is an API or MCP, call it directly; and if I want to self-host, find the repo and help me deploy it.

Releasing Module 02 - Practitioner's Series on xlwings Lite. Python in Excel. Data Cleaning & Rule Based Transformation

Published: July 6, 2025

I've put up a new guide on my site: Module 02 of my practitioner's series on xlwings Lite, focused on data cleaning.

My go-to for any Python-in-Excel work is xlwings Lite from Felix Zumstein. The guide uses a real-world mobile number example to show how to handle multi step rule-based transformations with xlwings Lite.

This same methodology can be used for data cleaning of other variables. As well create complex derived variables- from analysis datasets to campaign files.

But it's really about the process: how to instruct AI, how to use AI Coder file to provide context, and most importantly, validation of output.

This brings me to a core lesson from my years in the trenches: Validations are sacrosanct. AI didn't do the work- you did. It's a tool that helps, that's it. If it's not validated, it does not go out. No matter what AI says. No matter the pressure. Period.

Get the full module- including the workbook and AI Coder file at Tigzig xlwings Lite section

xlwings-lite.tigzig.com

xlwings Lite official site: lite.xlwings.org