Programming & Development

Data Wrangling with Python


In this course you will start with the absolute basics of Python, focusing mainly on data structures. Then you will delve into the fundamental tools of data wrangling like NumPy and Pandas libraries. You’ll explore useful insights into why you should stay away from traditional ways of data cleaning, as done in other languages, and take advantage of the specialized pre-built routines in Python. This combination of Python tips and tricks will also demonstrate how to use the same Python backend and extract/transform data from an array of sources including the Internet, large database vaults, and Excel financial tables. To help you prepare for more challenging scenarios, you’ll cover how to handle missing or wrong data, and reformat it based on the requirements from the downstream analytics tool. The course will further help you grasp concepts through real-world examples and datasets.

Who Should Attend
Data Wrangling with Python takes a practical approach to equip beginners with the most essential data analysis tools in the shortest possible time. It contains multiple activities that use real-life business scenarios for you to practice and apply your new skills in a highly relevant context.

Course Objectives
By the end of this course, you will be confident in using a diverse array of sources to extract, clean, transform, and format your data efficiently.

Course Outline:

Python for Data Wrangling
Lists, Sets, Strings, Tuples, and Dictionaries
Advanced Data Structures
Basic File Operations in Python
NumPy Arrays
Pandas DataFrames
Statistics and Visualization with NumPy and Pandas
Using NumPy and Pandas to Calculate Basic Descriptive Statistics on the DataFrame
Subsetting, Filtering, and Grouping
Detecting Outliers and Handling Missing Values
Concatenating, Merging, and Joining
Useful Methods of Pandas
Reading Data from Different Text-Based (and Non-Text-Based) Sources
Introduction to BeautifulSoup4 and Web Page Parsing
Advanced List Comprehension and the zip Function
Data Formatting
Basics of Web Scraping and BeautifulSoup libraries
Reading Data from XML
Refresher of RDBMS and SQL
Using an RDBMS (MySQL/PostgreSQL/SQLite)
Applying Your Knowledge to a Real-life Data Wrangling Task
An Extension to Data Wrangling

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