Pydata 代替案 & 競合他社
代替品と競合他社 pydata.org コンテンツ、トラフィック、構造に関して
Matplotlib — Visualization with Python.
Code faster with Kite’s AI-powered autocomplete plugin for over 16 programming languages and 16 IDEs, featuring Multi-Line Completions. Works 100% locally.
Learn Data Science & AI from the comfort of your browser, at your own pace with DataCamp's video tutorials & coding challenges on R, Python, Statistics & more.
Review our step-by-step Data Science tutorials using a variety of tools, such as Python, SQL, MS Access, MS Excel, and more!
Why NumPy? Powerful n-dimensional arrays. Numerical computing tools. Interoperable. Performant. Open source.
Why SciPy? Fundamental algorithms. Broadly applicable. Foundational. Interoperable. Performant. Open source.
Home | Pythonic Perambulations.
The Python Graph Gallery displays hundreds of charts made with Python, always with explanation and reproduciible code
ThisPointer – Programming Tutorials.
Do you want to learn Python from scratch to advanced, check out best way to learn python and machine learning from experts.
Learn Python online: Python tutorials for developers of all skill levels, Python books and courses, Python news, code examples, articles, and more.
Your home for data science. A Medium publication sharing concepts, ideas and codes.
Analytics Vidhya - Learn Machine learning, artificial intelligence, business analytics, data science, big data, data visualizations tools and techniques.
R news and tutorials contributed by hundreds of R bloggers
Python tutorials: Pandas, Statsmodels, Seaborn, Matplotlib. R tutorials: descriptive statistics, importing data, and many more.
Statology is a website that makes learning statistics easy by explaining concepts in simple, straightforward ways.
Spark By Examples | Learn Spark Tutorial with Examples In this Apache Spark Tutorial, you will learn Spark with Scala code examples and every sample example explained here is available at Spark Examples Github Project for reference. All Spark examples provided in this Apache Spark Tutorials are basic, simple, easy to practice for beginners who
Scikit-learn: machine learning in Python — scikit-learn 0.16.1 documentation.
Scipy Lecture Notes — Scipy lecture notes.
Learn Data Science with Python and R
Learn to Make Plots in Python and R
The official home of the Python Programming Language
Learn to code in Python, C/C++, Java, and other popular programming languages with our easy to follow tutorials, examples, online compiler and references.
Python Examples – Learn Python Programming - Python Examples.
Making developers awesome at machine learning.
This Python Tutorial helps you learn Python programming from scratch. If you want to master Python fast, this tutorial is a good start.
The Python Package Index (PyPI) is a repository of software for the Python programming language.
Python Pool is a platform where you can learn and become an expert in every aspect of Python programming language as well as in AI, ML and Data Science.
Python Tutorials for Beginners and Experienced Programmers
Kaggle is the world’s largest data science community with powerful tools and resources to help you achieve your data science goals.
STHDA est dédié à l'analyse statistique des données en utilisant le langage R.
Easily search the documentation for every version of every R package on CRAN and Bioconductor.
Statistics Globe is an education platform providing free programming tutorials - R programming & Python - Statistics & data science.
Bot Verification.
Definitive Python, Pandas, Machine learning and AWS tutorials with working examples and step by step guides.
Piles of precious data
R: The R Project for Statistical Computing.
ProgrammingR is your one-stop source for learning the R programming language, finding R jobs, hiring R programmers or R consultants, and getting R related help.
Home - DataScience Made Simple.
Hundreds of statistics how to articles and step by step videos for elementary statistics and probability, plus AP and advanced statistics topics.
Scikit-image: Image processing in Python — scikit-image.
Over 1400 graphs with reproducible code divided in 8 big categories and over 50 chart types, in addition of tools to choose and create colors and color palettes