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NumPy vs Data Miner: What are the differences?

NumPy: Fundamental package for scientific computing with Python. Besides its obvious scientific uses, NumPy can also be used as an efficient multi-dimensional container of generic data. Arbitrary data-types can be defined. This allows NumPy to seamlessly and speedily integrate with a wide variety of databases; Data Miner: Extract Data From any Website in Seconds. It is a Google Chrome extension that helps you scrape data from web pages and into a CSV file or Excel spreadsheet.

NumPy and Data Miner can be primarily classified as "Data Science" tools.

Some of the features offered by NumPy are:

  • a powerful N-dimensional array object
  • sophisticated (broadcasting) functions
  • tools for integrating C/C++ and Fortran code

On the other hand, Data Miner provides the following key features:

  • Scrape with one click
  • No coding
  • No bots

NumPy is an open source tool with 11.8K GitHub stars and 3.86K GitHub forks. Here's a link to NumPy's open source repository on GitHub.

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    - No public GitHub repository available -

    What is Data Miner?

    It is a Google Chrome extension that helps you scrape data from web pages and into a CSV file or Excel spreadsheet.

    What is NumPy?

    Besides its obvious scientific uses, NumPy can also be used as an efficient multi-dimensional container of generic data. Arbitrary data-types can be defined. This allows NumPy to seamlessly and speedily integrate with a wide variety of databases.

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    What are some alternatives to Data Miner and NumPy?
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    Pandas
    Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more.
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