This course begins by setting up Anaconda and Jupyter Lab for Python and Pandas, providing foundational Python knowledge before diving into Pandas for data analysis. You'll learn Series and DataFrame structures for effective data management and manipulation. Key topics include
- Handling dates
- Performing file input/output operations crucial for real-world data tasks
- Advanced data visualization using Matplotlib.
- Advanced Pandas features and settings are explored to enhance data manipulation capabilities.
By the course's end, you'll master data analysis techniques, adept at handling complex datasets, conducting detailed analysis, and presenting insights visually, preparing you for advanced roles in data analytics and manipulation. Ideal for data analysts, aspiring data scientists, and professionals aiming to deepen their skills in data manipulation and analysis using Pandas, this course bridges basic Python knowledge to advanced data handling and visualization techniques.
Applied Learning Project
Learners will tackle real-world projects such as filtering and extracting data from complex DataFrames, merging datasets, and performing GroupBy operations to uncover insights. They will work with text data, dates, and times, applying advanced Pandas features to solve authentic data analysis problems. Through hands-on projects, learners will visualize data using Matplotlib, effectively presenting their findings and preparing for professional data analysis roles.
