📚 Open Source Technology DailyExploring the Infinite Possibilities of Open Source2025/6/8âš¡Linux 6.16 Introduces New Helper Function to Restrict Symbols to Specific Kernel ModulesLinux 6.16 merge window is about to close, and all updates to the kernel build system “Kbuild” have been merged today, with the release of Linux 6.16-rc1 expected tomorrow. The most notable feature … Read more
In the field of Python data analysis, programmers often focus on discussing Pandas for data cleaning, Matplotlib for visualization, or Scikit-learn for machine learning models. However, few realize that a hidden core technique can significantly enhance data processing efficiency, potentially determining the success or failure of a project. Today, we will unveil this “killer feature” … Read more
import pandas as pd import numpy as np Date: May 8, 2025 Pandas and NumPy are the cornerstones of Python data analysis. Combined with SciPy, Seaborn, and Matplotlib, they provide a complete workflow from numerical computation to visualization. This article compiles and answers the 11th to 20th common questions, covering NumPy array operations, broadcasting, linear … Read more
I tested that the MKL library’s Python version should ideally be kept at 3.9, and not greater than 3.9, such as 3.10, 3.11, 3.12, or 3.13, as they are currently not very compatible.Therefore, when configuring, it is best to use conda, and thencreate a virtual environment. conda create -n my_env python=3.9 Activate the virtual environment … Read more
Among Python’s data processing libraries, NumPy is undoubtedly the most fundamental and powerful. Today, we will discuss how to use NumPy for complex data operations to help everyone better master this powerful tool. As a library that supports efficient array operations, NumPy has significant advantages when handling large-scale data and performing mathematical calculations. 1. Basic … Read more
Author: Jeff Knupp Translation: Wu Lei, Huo Jing It is well known that Python is currently the most widely used and fastest-growing programming language. Its elegant and concise syntax, along with strong support from third-party libraries, are reasons why Python is thriving across various industries. However, you may not know that the rapid growth of … Read more
(Click the public account above to quickly follow) NumPy is a scientific computing library for Python that provides matrix operations and is generally used alongside SciPy and matplotlib. Today, on NumPy’s GitHub homepage, it was announced that the NumPy library will drop support for Python 2 starting January 1, 2019. Excerpt from ‘Python Developers’: The … Read more
The core functionality of NumPy (Numerical Python) is specifically designed to handle multidimensional arrays, but its capabilities extend far beyond that. As the foundational library for scientific computing in Python, it centers around N-dimensional arrays (ndarray), deriving a full range of functionalities covering mathematical operations, linear algebra, data preprocessing, and more. 1. ndarray: NumPy’s Exclusive … Read more
Click the blue text above to follow us! To learn GNN, you will definitely use the torch_geometric package. PyG (PyTorch Geometric) is a library built on PyTorch that allows easy writing and training of Graph Neural Networks (GNNs), suitable for various applications related to structured data. A GCNConv can be easily called with just one … Read more
In the field of data science, Python has become the preferred programming language for data analysts and data scientists due to its simple syntax, powerful capabilities, and rich community resources. To help everyone better conduct data analysis, the following will introduce the 7 commonly used open source libraries in Python data analysis. 1. NumPy NumPy … Read more