Data Serialization and Representation Online Course
Data Serialization and Representation Online Course
This course helps you master essential data formats for data-driven roles. You'll start with CSV files, learning how to manipulate them using Python's csv module, pandas, and tablib. The course then covers JSON files, including advanced handling with pandas, simplejson, ujson, and more. You'll also explore YAML, XML, and HTML files, gaining expertise with tools like PyYAML, xmltodict, lxml, and BeautifulSoup. By the end, you'll be proficient in managing various data formats to enhance your data processing skills.
Who is this Course for?
This course is ideal for data scientists, analysts, and developers with a basic understanding of Python. It’s perfect for those looking to enhance their data manipulation skills across various data formats. A fundamental knowledge of Python programming is a prerequisite.
What you will learn
Learn to explore and manipulate CSV files using the csv module, pandas, and tablib. Gain skills in managing JSON files with json, pandas, simplejson, and ujson. Work with YAML files using PyYAML and tablib, and handle XML and HTML files using xml, lxml, xmltodict, and BeautifulSoup for efficient data processing across multiple formats.
Course Table of Contents
CSV
- Overview
- What is CSV
- Explore CSV Files
- Use csv Module
- Use csv Module Part 2
- Use the pandas Package
- Use the tablib Package
JSON
- What is JSON
- Explore JSON Files
- JSON: Use the json Module
- JSON: Use the pandas Package
- Use the simplejson and ujson Packages
- JSON: Use the tablib Package
YAML
- What is YAML
- Explore YAML Files
- Use the PyYAML Package
- YAML: Use the tablib Package
XML and HTML
- What is XML
- Explore XML Files
- What is HTML
- Explore HTML Files
- Use the xml Module
- Use the lxml Package
- Use the xmltodict Package
- Use the BeautifulSoup Package
