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Pandas

Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

Pandas Alternatives

The best Pandas alternatives based on verified products, votes, reviews and other factors.
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  1. scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

  2. NumPy is the fundamental package for scientific computing with Python

  3. OpenCV (Open Source Computer Vision) is a library of programming functions for real time computer...

  4. Dataiku is the developer of DSS, the integrated development platform for data professionals to turn raw data into predictions.

  5. Exploratory enables users to understand data by transforming, visualizing, and applying advanced statistics and machine learning algorithms.

  6. WEKA is a set of powerful data mining tools that run on Java.

  7. htm.java is a Hierarchical Temporal Memory implementation in Java, it provide a Java version of NuPIC that has a 1-to-1 correspondence to all systems, functionality and tests provided by Numenta's open source implementation.

  8. Figure Eight is the essential Human-in-the-Loop Machine Learning platform.

  9. GraphLab Create is an extensible machine learning framework that enables developers and data scientists to easily build and deploy apps.

  10. Logical Glue helps Lenders and Insurance organisations make better decisions with a highly intuitive and user-friendly Machine Learning Platform.

  11. The DimML programming language enables users to run any data solution on any website with only a single line of code.

  12. RapidMiner is a software platform for data science teams that unites data prep, machine learning, and predictive model deployment.

  13. DataScience combines human intellect with machine-powered analysis to create actionable insights from complex data.

Pandas Reviews

External sources with reviews and comparisons of Pandas

Python & ETL 2020: A List and Comparison of the Top Python ETL Tools
When it comes to ETL, you can do almost anything with Pandas if you're willing to put in the time. Plus, pandas is extraordinarily easy to run. You can set up a simple script to load data from a Postgre table, transform and clean that data, and then write that data to another Postgre table.
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This article was published on | Author: | Publisher: SaaSHub
Categories: Data Science And Machine Learning, Data Dashboard, Data Science Tools