AI · alternatives · 2026
24 alternatives to How to analyse 100 GB of data on your laptop with Python
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This is a guide for developers on analyzing large datasets using Python on standard laptops. Published in 2019, it addresses the practical challenge of working with 100 GB files without requiring specialized… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. How to analyse 100 GB of data on your laptop with Python launched in 2019; newer entries below may have overtaken it.
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Pandas is the most common python library for data analytics
2016 · amazon.com · its alternatives →
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All-pair set similarity search on millions of sets in Python and on a laptop - GitHub - ekzhu/SetSimilaritySearch: All-pair set similarity search on millions of sets in Python and on a laptop
2018 · github.com · its alternatives →
- 31R
2016 · magic.io · its alternatives →
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- 5BA
2019 · bamboolib.com · its alternatives →
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Analyzing and visualizing data from CSV files
2025 · claude.com · its alternatives →
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Yeah, there's AI, but I added it because I found it easier to find answers I'm looking for. For the data scientists, you can download the CSV and go crazy. Would love to know what discoveries or learnings can be found from it. To download the raw scraped data you need to become a paid member but you don't really need it unless you're wanting to finesse a table of data for a particular need. The cost is mostly just an incentive to help me pay the bills for running the website. The bunch of available CSV files contain large amounts of data which has everything from tags, genres, pricing,…
2025 · gginsights.io · its alternatives →
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The source for financial, economic, and alternative datasets, serving investment professionals.
2013 · quandl.com · its alternatives →
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An on-disk B+tree for Python 3. Contribute to NicolasLM/bplustree development by creating an account on GitHub.
2018 · github.com · its alternatives →
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Hi HN, Over the past 6 months I've been working on a technical book focused on helping aspiring data scientists to get hands-on experience with cloud computing environments using the Python ecosystem. The book is targeted at readers already familiar with libraries such as Pandas and scikit-learn that are looking to build out a portfolio of applied projects. To author the book, I used the Leanpub platform to provide drafts of the text as I completed each chapter. To typeset the book, I used the R bookdown package by Yihui Xie to translate my markdown into a PDF format. I also used Google docs…
2020 · its alternatives →
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Process large (e.g. 4GB+) data sets in a spreadsheet. Load GB/32 million-row files in seconds and use them without any crashes using up to about 500GB RAM. Load/edit in-place/split/merge/clean CSV/text files with up to 32 million rows and 1 million columns. Use your Python functions as UDF formulas that can return to GS-Calc images and entire CSV files. Use a set of statistical pivot data functions. Solver functions virtually without limits for the number of variables. Create and display all popular chart types with millions of data points instantly. Suggestions…
2025 · citadel5.com · its alternatives →
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Beautiful Data Science
2020 · shahinrostami.com · its alternatives →
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A container for dataclasses with multi-indexing and bulk operations. - joshlk/dataclassframe
2020 · github.com · its alternatives →
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Data Science and Python, starting at zero
2015 · joelgrus.com · its alternatives →
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Today I'm open sourcing "Grid studio", a web-based spreadsheet application with full integration of the Python programming language.
2019 · hackernoon.com · its alternatives →
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A practical book on Data Analysis with Rust Notebooks that teaches you the concepts and how they’re implemented in practice.
2020 · datacrayon.com · its alternatives →
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Explore and Analyze Big Data from any Notebook
2019 · hi-bumblebee.com · its alternatives →
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I got tired of the overhead required to run even a simple data analysis - cloud setup, ETL pipelines, orchestration, cost monitoring - so I built a fully local data-stack/IDE where I can write SQL/Py, run it, see results, and iterate quickly and interactively. You get data lake like catalog, zero-ETL, lineage, versioning, and analytics running entirely on your machine. You can import from a database, webpage, CSV, etc. and query in natural language or do your own work in SQL/Pyspark. Connect to local models like Gemma or cloud LLMs like Claude for querying and analysis. You…
Apr 2026 · stream-sock-3f5.notion.site · its alternatives →
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Learning machine learning has never been easier
2017 · amazon.com · its alternatives →
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Learn machine learning through over 30 interactive notebooks
2021 · github.com · its alternatives →
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I built CSV GB+ by Data.olllo, a local data tool that lets you open, clean, and export gigabyte-sized CSVs (even billions of rows) without writing code. Most spreadsheet apps choke on big files. Coding in pandas or Polars works—but not everyone wants to write scripts just to filter or merge CSVs. CSV GB+ gives you a fast, point-and-click interface built on dual backends (memory-optimized or disk-backed) so you can process huge datasets offline. Key Features: Handles massive CSVs with ease — merge, split, dedup, filter, batch export Smart engine switch: disk-based "V Core" or RAM-based "P…
2025 · apps.microsoft.com · its alternatives →
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