Data source: User purchase details of CDNow website. Total user ID, purchase date, purchase quantity, purchase amount of four fields. 1. Data preprocessing is enabled...
Guide language: learn data analysis from scratch, what degree can you look for a job? Ant Financial data analysis experts start from three key questions...
We mainly do flow learning of data analysis, mainly including data cleaning, data feature processing, data reconstruction and data visualization. These contents are a preparation...
Start by importing the scientific computing packages numpy, PANDAS, matplotlib, Seaborn, and sklearn to use. The data is then imported and preliminary observations are made,...
Project Background: A fresh food delivery APP was established on January 1, 2018, specializing in fresh vegetables, fruits, seafood, meat and poultry. After the launch...
This is the sixth chapter in the pandas series. The text describes the basic operations for previewing data, including data size, column type, value distribution,...
This article continues with another common problem in data cleaning: outlier detection and handling. In machine learning, anomaly detection and processing is a branch of...
In the process of data cleaning, missing values, outliers and duplicate values are mainly dealt with. The so-called cleaning refers to the operation of discarding,...
How to obtain more reliable evaluation indicators under inconsistent data distribution? What difference would it make if you simply calculated the metrics? This article uses...
The jump diffusion process provides a modeling method for deviations in continuous evolution. However, the calculus of jump diffusion process makes it difficult to analyze...
Digital transformation is an unavoidable topic in modern enterprises. First of all, let's take a look at the basic definition of digital transformation: Digital transformation...
1. Data analysis step map asking questions → data preparation → data cleaning → model building → data visualization 2. Essential skills of data analyst...
Rmarkdown is a series of Rmarkdown tutorials you've written in the past. Public number established more than half a year of time, review this series,...
Today, I will talk about an important topic that is common both in algorithm modeling and data analysis: data normalization and standardization. Before you start,...
This paper will continue the data mining modeling and prediction after the data analysis in the previous paper. These two parts constitute a simple complete...
Introduction: When we develop background applications or middleware, we store some data in memory to speed up access. As the amount of data increases, it...