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Data Miner
Data Miner

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SciPy
SciPy

50
21
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0
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SciPy vs Data Miner: What are the differences?

What is SciPy? Scientific Computing Tools for Python. Python-based ecosystem of open-source software for mathematics, science, and engineering. It contains modules for optimization, linear algebra, integration, interpolation, special functions, FFT, signal and image processing, ODE solvers and other tasks common in science and engineering.

What is 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.

SciPy and Data Miner belong to "Data Science Tools" category of the tech stack.

SciPy is an open source tool with 6.28K GitHub stars and 2.95K GitHub forks. Here's a link to SciPy's open source repository on GitHub.

- 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 SciPy?

Python-based ecosystem of open-source software for mathematics, science, and engineering. It contains modules for optimization, linear algebra, integration, interpolation, special functions, FFT, signal and image processing, ODE solvers and other tasks common in science and engineering.
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            What are some alternatives to Data Miner and SciPy?
            TensorFlow
            TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.
            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.
            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.
            Anaconda
            A free and open-source distribution of the Python and R programming languages for scientific computing, that aims to simplify package management and deployment. Package versions are managed by the package management system conda.
            Pentaho Data Integration
            It enable users to ingest, blend, cleanse and prepare diverse data from any source. With visual tools to eliminate coding and complexity, It puts the best quality data at the fingertips of IT and the business.
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