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Products that do what Emancipation Edutech Pvt Ltd does
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Hey, guys. I've just made a plugin which turns your pandas dataframe into a tableau-style component. It allows you to explore the dataframe with easy drag-and-drop UI. You can use PyGWalker in Jupyter, Google Colab, or even Kaggle Notebook to easily explore your data and generate interactive visualizations. PyGWalker (pronounced like "Pig Walker", just for fun) is named as an abbreviation of "Python binding of Graphic Walker". Here are some links to check it out: The Github Repo: https://github.com/Kanaries/pygwalker Use PyGWalker in Kaggle:…
2023 · github.com
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2019 · bamboolib.com
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Paste in my prompt to Claude Code with an embedded API key for accessing my public readonly SQL+vector database, and you have a state-of-the-art research tool over Hacker News, arXiv, LessWrong, and dozens of other high-quality public commons sites. Claude whips up the monster SQL queries that safely run on my machine, to answer your most nuanced questions. There's also an Alerts functionality, where you can just ask Claude to submit a SQL query as an alert, and you'll be emailed when the ultra nuanced criteria is met (and the output changes). Like I want to know when somebody posts about…
Dec 2025 · exopriors.com
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Probly was built to reduce context-switching between spreadsheet applications, Python notebooks, and AI tools. It’s a simple spreadsheet that lets you talk to your data. Need pandas analysis? Just ask in plain English, and the code runs right in your browser. Want a chart? Just ask. While there are tools available in this space like TheBricks, Probly is a minimalist, open-source solution built with React, TypeScript, Next.js, Handsontable, Hyperformula, Apache Echarts, OpenAI, and Pyodide. It's still a work in progress, but it's already useful for my daily tasks.
2025 · github.com
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Learn SQL - the preferred tool of data analysts everywhere …
2015
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Hey HN! I’m excited to share sketch: a tool to help anyone who uses python and pandas quickly iterate and get to answers for their data questions. Sketch installs as a pandas extension that offers utility functions that operate on natural language prompts. Using the `ask` interface you can get answers in natural language. Using the `howto` interface you can get get python and pandas code directly. The primary benefit of this over copilot and chatGPT is that this adds data-content based context so that the generated answers are much more accurate and relevant to the data problem at hand.…
2023 · github.com
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Hey HN! We’ve built Pretzel, an open-source data exploration and visualization tool that runs fully in the browser and can handle large files (200 MB CSV on my 8gb MacBook air is snappy). It’s also reactive - so if, for example, you change a filter, all the data transform blocks after it re-evaluate automatically. You can try it here: https://pretzelai.github.io/ (static hosted webpage) or see a demo video here: https://www.youtube.com/watch?v=73wNEun_L7w You can play with the demo CSV that’s pre-loaded (GitHub data of text-editor adjacent projects) or upload…
2024 · github.com
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2020 · github.com
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Hi HN: I published part one of my free NLP course. The course is intended to help anyone who knows Python and a bit of math go from the very basics all the way to today's mainstream models and frameworks. I strive to balance theory and practice and so every module consists of detailed explanations and slides along with a Colab notebook (in most modules) putting the theory into practice. In part one, we cover text preprocessing, how to turn text into numbers, and multiple ways to classify and search text using "classical" approaches. And along the way, we'll pick up useful bits on how to use…
2022 · nlpdemystified.org
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2022 · github.com
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Dear HN, I am Riwaj, the cofounder of dstack.ai (https://github.com/dstackai). A few months ago, we built an online service that allows users to publish data visualizations from Python or R. The idea was to build a tool that did not require additional programming or front-end development for publishing data visualizations. Such a code can be invoked from either Jupyter notebook, RMarkdown, Python, or R scripts. Once the data is pushed, it can be accessed via a browser. Open-sourcing dstack: During our customer discovery phase, we realized that dstack.ai should integrate a lot…
2020
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2021 · hairysun.com
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2019 · github.com
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2014 · github.com
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I've been doing some data cleaning for my fine tuning projects using LLMs, and decided to just build a package for it as a side project. Check it out here: https://github.com/databonsai/databonsai Some features: - categorization (labelling), transformation and decomposition (text into structured format) - validates llm outputs - batch mode batches up the inputs/outputs so you don't send the prompt (schema, fewshot examples) for every row of data, saving a significant amount of tokens There are some similarities to the Instructor repo, but this is simpler and made for…
2024 · github.com
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Sep 2025 · github.com
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Visions is a python library for working with user defined data type systems. Out of the box, it provides type inference and automated data cleaning of sequence data with backend specific implementations for pandas, spark, python, and numpy. We often use it as a first pass cleaning step when working with tabular data and to simplify the backend logic of both pandas-profiling[1] and our tabular data compression library compressio[2]. Because data types are user defined, we can build user customizable libraries based around types without adding code complexity. In the case of compressio that…
2022 · github.com
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