GitHub - facebookresearch/Kats: Kats, a kit to analyze time series data, a lightweight, easy-to-use, generalizable, and extendable framework to perform time series analysis, from understanding the key statistics and characteristics, detecting change point
Kats is a toolkit to analyze time series data, a lightweight, easy-to-use, and generalizable framework to perform time series analysis. Time series analysis is an essential component of Data Science and Engineering work at industry, from understanding the key statistics and characteristics, detecting regressions and anomalies, to forecasting future trends. Kats aims to provide the one-stop shop fo
Home — Spyder IDE
Spyder is a free and open source scientific environment written in Python, for Python, and designed by and for scientists, engineers and data analysts. It features a unique combination of the advanced editing, analysis, debugging, and profiling functionality of a comprehensive development tool with the data exploration, interactive execution, deep inspection, and beautiful visualization capabiliti
Metaflow - a framework for real-life ML, AI, and data science
A framework for real-life ML, AI, and data science Open-source Metaflow makes it quick and easy to build and manage real-life ML, AI, and data science projects. Modeling Use any Python libraries for models and business logic. Metaflow helps manage library dependencies, locally and in the cloud. Deployment Deploy workflows to production with a single command and integrate with other systems through
Another Book on Data Science
Why am I writing this book? Maybe a major reason is an existential crisis. The feedback from readers is another important reason. I submitted a git repo with three Chapters of this book in PDF format to Hacker News, and surprisingly the repo got 500 stars in a week. I received a few emails expressing thanks and interests in more Chapters. About There has been considerable debate over choosing R vs
GitHub - vaexio/vaex: Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python, ML, visualization and exploration of big tabular data at a billion rows per second 🚀
Vaex is a high performance Python library for lazy Out-of-Core DataFrames (similar to Pandas), to visualize and explore big tabular datasets. It calculates statistics such as mean, sum, count, standard deviation etc, on an N-dimensional grid for more than a billion (10^9) samples/rows per second. Visualization is done using histograms, density plots and 3d volume rendering, allowing interactive ex
GitHub - manga109/manga109api: Simple python API to read annotation data of Manga109
import manga109api from pprint import pprint # (0) Instantiate a parser with the root directory of Manga109 manga109_root_dir = "YOUR_DIR/Manga109_2017_09_28" p = manga109api.Parser(root_dir=manga109_root_dir) # (1) Book titles print(p.books) # Output: ['ARMS', 'AisazuNihaIrarenai', 'AkkeraKanjinchou', 'Akuhamu', ... # (2) Path to an image (page). print(p.img_path(book="ARMS", index=3)) # the 4th
Python 3.7: Introducing Data Classes | The PyCharm Blog
IDEs AppCode CLion DataGrip DataSpell Fleet GoLand IntelliJ IDEA PhpStorm PyCharm RustRover Rider RubyMine WebStorm Plugins & Services Big Data Tools Code With Me Quality Assurance JetBrains Platform Scala Toolbox App Writerside Team Tools Datalore Space TeamCity Upsource YouTrack Hub Qodana .NET & Visual Studio .NET Tools ReSharper C++ Languages & Frameworks Kotlin Ktor MPS Education & Research J
Python Data Science Handbook | Python Data Science Handbook
This website contains the full text of the Python Data Science Handbook by Jake VanderPlas; the content is available on GitHub in the form of Jupyter notebooks. The text is released under the CC-BY-NC-ND license, and code is released under the MIT license. If you find this content useful, please consider supporting the work by buying the book!
Python for Finance Tutorial: Algorithmic Trading
This Python for Finance tutorial introduces you to algorithmic trading, and much more. Technology has become an asset in finance: financial institutions are now evolving to technology companies rather than only staying occupied with just the financial aspect: besides the fact that technology brings about innovation the speeds and can help to gain a competitive advantage, the rate and frequency of
Bonobo • Data-processing for humans • Python ETL
Write atomic data transformations using simple python callables. Connect them in a directed graph. Execute. Bonobo is a lightweight Extract-Transform-Load (ETL) framework for Python 3.5+. It provides tools for building data transformation pipelines, using plain python primitives, and executing them in parallel. Bonobo is the swiss army knife for everyday's data.
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GitHub - capitalone/DataProfiler: What's in your data? Extract schema, statistics and entities from datasets
GitHub - google-deepmind/tree: tree is a library for working with nested data structures
GitHub - python-streamz/streamz: Real-time stream processing for python
GitHub - plotly/dash: Data Apps & Dashboards for Python. No JavaScript Required.
GitHub - jakevdp/PythonDataScienceHandbook: Python Data Science Handbook: full text in Jupyter Notebooks
GitHub - facebook/prophet: Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
Python Data Visualization — Comparing 5 Tools
https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/README.md
GitHub - robdmc/pandashells: :panda_face: Bringing the python data stack to the shell prompt