holoviews - Stop plotting your data - annotate your data and let it visualize itself.

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Stop plotting your data - annotate your data and let it visualize itself. HoloViews is an open-source Python library designed to make data analysis and visualization seamless and simple. With HoloViews, you can usually express what you want to do in very few lines of code, letting you focus on what you are trying to explore and convey, not on the process of plotting.




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Lux is a Python library that facilitate fast and easy data exploration by automating the visualization and data analysis process. By simply printing out a dataframe in a Jupyter notebook, Lux recommends a set of visualizations highlighting interesting trends and patterns in the dataset. Visualizations are displayed via an interactive widget that enables users to quickly browse through large collections of visualizations and make sense of their data. Here is a 1-min video introducing Lux, and slides from a more extended talk.

pycon-2019-tutorial - Data Science Best Practices with pandas

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evidently - Interactive reports to analyze machine learning models during validation or production monitoring

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Interactive reports and JSON profiles to analyze, monitor and debug machine learning models. Evidently helps evaluate machine learning models during validation and monitor them in production. The tool generates interactive visual reports and JSON profiles from pandas DataFrame or csv files. You can use visual reports for ad hoc analysis, debugging and team sharing, and JSON profiles to integrate Evidently in prediction pipelines or with other visualization tools.

Bokeh - Interactive Data Visualization in the browser, from Python

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Read about the series, and view all of the videos on one page: Easier data analysis in Python with pandas.

NFStream - A Flexible Network Data Analysis Framework

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NFStream is a Python package providing fast, flexible, and expressive data structures designed to make working with online or offline network data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world network data analysis in Python. Additionally, it has the broader goal of becoming a common network data processing framework for researchers providing data reproducibility across experiments. NFStream extracts +90 flow features and can convert it directly to a pandas Dataframe or a CSV file.

xarray - N-D labeled arrays and datasets in Python

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data-science-with-ruby - Practical Data Science with Ruby based tools.

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Data Science is a new "sexy" buzzword without specific meaning but often used to substitute Statistics, Scientific Computing, Text and Data Mining and Visualization, Machine Learning, Data Processing and Warehousing as well as Retrieval Algorithms of any kind. This curated list comprises awesome tutorials, libraries, information sources about various Data Science applications using the Ruby programming language.

Zipline - A Pythonic Algorithmic Trading Library

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pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data

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data-visualization - Misc data visualization projects, examples, and demos: mostly Python (pandas + matplotlib) and JavaScript (leaflet)

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Misc data visualization projects, examples, and demos: mostly Python (pandas + matplotlib) and JavaScript (leaflet).

data-science-your-way - Ways of doing Data Science Engineering and Machine Learning in R and Python

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These series of tutorials on Data Science engineering will try to compare how different concepts in the discipline can be implemented in the two dominant ecosystems nowadays: R and Python. We will do this from a neutral point of view. Our opinion is that each environment has good and bad things, and any data scientist should know how to use both in order to be as prepared as posible for job market or to start personal project.

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