Data Analysis with Pandas and Python Specialization (Packt)

These are the Jupyter notebooks for the lab sessions of the Data Analysis with Pandas and Python Specialization offered by Packt on Coursera.

🔗 Specialization Link on Coursera

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About the Specialization

This specialization by Boris Paskhaver covers Python programming and data analysis with Pandas, including installation, core Python concepts, Series and DataFrame manipulation, text data handling, GroupBy methods, DataFrame merging, date and time management, I/O operations, data visualization, and Pandas customization.

Key Features:

• Setting up Anaconda and Jupyter Lab for Python and Pandas
• Foundational Python knowledge
• Series and DataFrame manipulation for data analysis
• Handling dates and performing file input/output operations
• Advanced data visualization using Matplotlib
• Customizing Pandas for advanced use cases

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Specialization Structure

1. Foundations of Data Analysis with Pandas and Python

Modules:

• Installation and Setup
• Python Crash Course
• Exploring Pandas Series for Data Analysis

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2. Intermediate Data Analysis Techniques with Pandas

Modules:

• DataFrames I: Introduction
• DataFrames II: Filtering Data
• DataFrames III: Data Extraction
• Working with Text Data
• MultiIndex
• GroupBy
• Merging DataFrames

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3. Advanced Data Analysis and Visualization with Pandas

Modules:

• Working with Dates and Times
• Input and Output
• Visualization
• Options and Settings
• Conclusion

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Instructor

This specialization is taught by Boris Paskhaver member of the team Packt - Course Instructors.

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Repository Structure

This repository contains the Jupyter notebooks organized by modules corresponding to the specialization’s courses and topics.

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Feel free to contribute by submitting issues or pull requests to improve the repository.

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