Data Science Mastery 7 of 20 - Data Manipulation with Python Pandas

Welcome to session 7 of 20 : Data Manipulation and Analysis with Pandas! In this series, we take a deep dive into mastering Pandas, one of the most powerful Python libraries for data manipulation. Whether you're a beginner or a seasoned data analyst, this module will equip you with the skills to manipulate, clean, and analyze your data with ease.

What You'll Learn:
DataFrames & Series: Introduction to Pandas data structures and how to create and manipulate them.
Loading & Exporting Data: Practical examples of loading and exporting data in CSV, Excel, SQL, and from web sources.
Data Cleaning: Learn techniques to handle missing values and duplicates to prepare clean datasets.
Data Transformation: How to filter, sort, and group data to uncover hidden insights and transform your dataset.
Merging, Joining, & Concatenating DataFrames: A comprehensive guide to combining multiple datasets into a single, unified dataset.
Video Chapters:
0:00 - Introduction to DataFrames and Series
3:30 - Loading and Exporting Data: CSV, Excel, SQL
8:15 - Data Cleaning: Handling Missing Values and Duplicates
12:45 - Data Transformation: Filtering, Sorting, Grouping
17:20 - Merging, Joining, and Concatenating DataFrames

By the end of this module, you'll be proficient in working with data using Pandas, setting a strong foundation for further data analysis and machine learning projects.

🔔 Subscribe for more in-depth tutorials on data science, Python, and real-world projects!

#Pandas #Python #DataScience #DataAnalysis #DataCleaning #DataFrames #PracticalDataScience #MachineLearning