Advanced Data Wrangling with Pandas: Mastering Advanced Techniques for Efficient Data Manipulation, Cleaning, and Analysis

Course Instructor: Ridwan Adejumo (SuleimanCode)
Course Title: Advanced Data Wrangling with Pandas

Course Description:

Are you ready to elevate your data manipulation skills to the expert level? Our Advanced Data Wrangling with Pandas course is designed for those who have already taken their first steps into the world of data analysis with pandas. If you're familiar with the basics, it's time to dive deeper and unlock a universe of advanced techniques that will enable you to handle complex data challenges with greater efficiency and precision.

Course Structure:

• Pandas Refresher: A quick recap of the fundamentals to ensure everyone is on the same page.

• Advanced String Manipulation: Learn powerful string manipulation techniques for text data processing.

• DateTime Handling: Master the art of manipulating and analyzing DateTime objects in Pandas.

• Multi-Indexing Techniques: Discover how to organize, select, and analyze data with multi-level indexing.

• Managing Missing Data: Understand techniques for dealing with NaN values and empty data frames.

• Outlier Detection: Learn methods to detect and handle outliers in your datasets.

• Merging & Joining Operations: Explore sophisticated operations that combine data from different sources.

• Regular Expressions for Text Cleaning: Utilize advanced regex patterns for cleaning and preparing textual data.

• Time-Series Analysis: Analyze time series data with advanced techniques, including rolling window statistics, date offsets, and period-over-period analysis.

What You'll Learn:

• Regular Expressions for Text Cleaning: Advanced regex patterns will help you clean textual data efficiently, ensuring high data quality.

• Advanced DateTime Handling: You'll learn to manipulate dates and times with precision, including creating custom date ranges and performing time series analysis.

• Multi-Indexing Techniques: Discover the power of multi-indexing to organize complex datasets and simplify data selection and aggregation.

• Managing Missing Data: Learn how to handle missing data with techniques like imputation, filtering, and visualization.

• Outlier Detection & Handling: Detect outliers in your datasets and understand how to manage them to improve the accuracy of your analysis.

• Sophisticated Merging & Joining Operations: Master merging and joining large datasets with complex key structures.

• Memory Optimization Techniques: Learn to work efficiently with large datasets by optimizing memory usage.

• Custom Function Creation: Extend Pandas' functionality by creating custom functions to handle unique data challenges.