PythonDataScienceHandbook
NumPy
PythonDataScienceHandbook | NumPy | |
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98 | 272 | |
41,485 | 26,360 | |
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0.6 | 10.0 | |
8 days ago | 5 days ago | |
Jupyter Notebook | Python | |
MIT License | GNU General Public License v3.0 or later |
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PythonDataScienceHandbook
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About Data analyst, data scientist and data engineer, resources and experiences
Python Data Science Handbook
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Where to learn data science with python??
Python Data Science Handbook — learn to use Python libraries such as NumPy, Pandas, Matplotlib, Scikit-Learn, and related tools to effectively store, manipulate, and gain insight from data
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Book Recommendations
I don't know what tools you will be using but if you will be using Python you can start with Python Data Science Handbook by Jake VanderPlas and Data Science & Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting DataData Science & Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data which gives a very good outlook on the data science and big data frame work. PS: Jake's book is also available as jupyter notebooks so you can read and run the code at the same time.
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Other programing options?
Python Data Science Handbook by Jake VanderPlas (https://jakevdp.github.io/PythonDataScienceHandbook/)
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Pathways out of GIS?
Otherwise you can work through courses on Datacamp, Coursera, Udemy, etc, or check out this book for a more general non-spatial perspective.
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Mastering Data Science: Top 10 GitHub Repos You Need to Know
7. Data Science Handbook Are you looking for a comprehensive guide to data science with Python? Look no further than the Data Science Handbook by Jake VanderPlas. This repository contains the entire book, which introduces essential tools and techniques used in data science, including IPython, NumPy, Pandas, Matplotlib, and Scikit-Learn. It’s a fantastic resource for anyone looking to deepen their understanding of data science concepts and best practices.
- Help a lady out (career advice(
- Resources for Current DE Interested in Learning Data Science
- Good book or course to learn Python for someone who is fluent in R?
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Python equivalent to R's ecosystem of open source educational materials
I can recommend https://jakevdp.github.io/PythonDataScienceHandbook/
NumPy
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Dot vs Matrix vs Element-wise multiplication in PyTorch
In NumPy with @, dot() or matmul():
- NumPy 2.0.0 Beta1
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Element-wise vs Matrix vs Dot multiplication
In NumPy with * or multiply(). ` or multiply()` can multiply 0D or more D arrays by element-wise multiplication.
- JSON dans les projets data science : Trucs & Astuces
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JSON in data science projects: tips & tricks
Data science projects often use numpy. However, numpy objects are not JSON-serializable and therefore require conversion to standard python objects in order to be saved:
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Introducing Flama for Robust Machine Learning APIs
numpy: A library for scientific computing in Python
- help with installing numpy, please
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A Comprehensive Guide to NumPy Arrays
Python has become a preferred language for data analysis due to its simplicity and robust library ecosystem. Among these, NumPy stands out with its efficient handling of numerical data. Let’s say you’re working with numbers for large data sets—something Python’s native data structures may find challenging. That’s where NumPy arrays come into play, making numerical computations seamless and speedy.
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Why do all the popular projects use relative imports in __init__ files if PEP 8 recommends absolute?
I was looking at all the big projects like numpy, pytorch, flask, etc.
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NumPy 2.0 development status & announcements: major C-API and Python API cleanup
I wish the NumPy devs would more thoroughly consider adding full fluent API support, e.g. x.sqrt().ceil(). [Issue #24081]
What are some alternatives?
django-livereload-server - Livereload functionality integrated with your Django development environment.
SymPy - A computer algebra system written in pure Python
Exercism - Scala Exercises - Crowd-sourced code mentorship. Practice having thoughtful conversations about code.
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
Serpent.AI - Game Agent Framework. Helping you create AIs / Bots that learn to play any game you own!
blaze - NumPy and Pandas interface to Big Data
lego-mindstorms - My LEGO MINDSTORMS projects (using set 51515 electronics)
SciPy - SciPy library main repository
OSQuery - SQL powered operating system instrumentation, monitoring, and analytics.
Numba - NumPy aware dynamic Python compiler using LLVM
devdocs - API Documentation Browser
Nim - Nim is a statically typed compiled systems programming language. It combines successful concepts from mature languages like Python, Ada and Modula. Its design focuses on efficiency, expressiveness, and elegance (in that order of priority).