Introduction by Qijin Fang From now on, let data speak. Data-driven management is not just for large enterprises. It starts with a well-designed maintenance request form, grows through a simple Excel sort, and matures as teams develop the habit of “making decisions based on data”. This is the concluding piece in the equipment management series. … Read more
1. Why choose log transformation? When we perform regression modeling,the target variable (the metric being predicted, such as house price SalePrice) does not conform to a normal distribution, we usually opt for log transformation, mainly for the following reasons: 1. Make the distribution closer to normal distribution Many real-world values (house prices, income, sales, population … Read more
Author: Li Shengsheng (A Little Ant in Management) Email:[email protected] Data Source: National Office for Philosophy and Social Science Work Using Python coding for statistics, due to some units not being included in the following codes, the counts for youth projects and general projects may be slightly underestimated. I have not verified this, so I hope … Read more
1. Basic Principles Three-dimensional fluorescence spectroscopy (EEM) constructs a three-dimensional data matrix (sample×excitation wavelength×emission wavelength) by scanning the fluorescence intensity of the sample at different excitation wavelengths (Ex) and emission wavelengths (Em). Parallel factor analysis (PARAFAC) is a mathematical algorithm based on trilinear decomposition theory, which uses alternating least squares (ALS) to decompose the complex … Read more
Click the blue text above to follow us 📋📋📋 The content of this article is as follows: 🎁🎁🎁 Table of Contents 💥1 Overview 📚2 Results 🎉3 References 🌈4 Matlab Code, Data, Documentation 1 Overview The Monte Carlo method is used to simulate the charging methods of electric vehicles, including regular charging, fast charging, and battery … Read more
Introduction to the Python Statistics Module For small statistical analyses, there is really no need to install a bunch of large libraries. If you want to calculate an average or check the distribution of sales data, you might end up spending a lot of time installing pandas, numpy, etc., and by then, your enthusiasm might … Read more
——A one-stop process for data cleaning, feature engineering, and visualization In the era of data explosion, whether in academic research, financial analysis, or business decision-making, efficient data processing capabilities have become a core competitive advantage. The three libraries in the Python ecosystem—NumPy, Pandas, and Matplotlib—have become the “golden combination” for data scientists and engineers due … Read more
👩💻 Are you also confused about this? Want to learn Python but have no idea where to start; Online tutorials are too scattered, and I give up after a couple of days; Classes are too expensive, and I can’t make up my mind to spend thousands on a course; I clearly want to take on … Read more
Source: Data STUDIO This article is approximately 4000 words long and is recommended for a 10-minute read. This article will systematically introduce six widely used time series smoothing techniques, analyzing them from multiple dimensions including technical principles, parameter configurations, performance characteristics, and applicable scenarios. In time series data analysis, the issue of noise is an … Read more
Recently, while chatting with several heads of data teams from major companies, I heard a painful truth: “Currently, resumes for data analyst positions that do not include Python go straight to the recycling bin.” Do you think being proficient in Excel functions and writing SQL quickly will keep you safe? Sorry, times have changed. From … Read more