Data Cleaning and Preprocessing using Python

Python数据清洗与预处理实战教程

本课程由IT博士Rocio Chavez主讲，系统教授Python数据清洗与预处理技术，涵盖缺失值处理、重复记录删除、数据格式转换、多源数据合并及数据降维等核心技能，适合所有水平学习者，8小时实操训练助你掌握数据分析关键步骤。

Published 10/2025
Created by IT Phd Rocio Chavez
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All | Genre: eLearning | Language: English + subtitle | Duration: 114 Lectures ( 8h 6m) | Size: 2.32 GB

Learn to Clean and Transform Your Data Step by Step

What you’ll learn
Fundamentals of programming in Python — data types, operators, data structures, and control flow structures.
To detect and handle errors, remove duplicate records and handle missing values
To adapt variables into suitable formats for analysis, ensuring coherence and compatibility among them
To combine data from multiple sources into the same dataset
Data reduction, which involves simplifying the dataset while keeping only the most relevant information
To organize and structure the dataset correctly in a format compatible with the analysis or model to be developed
How to apply both simple and advanced techniques to carry out these stages of data cleaning and preprocessing using Python

Requirements
No programming experience nor statistical knwoledge needed