Data-Analysis-with-Python---Zero-to-Pandas

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"Data Analysis with Python: Zero to Pandas" is a practical, beginner-friendly and coding-focused introduction to data analysis covering the basics of Python, Numpy, Pandas, data visualization and exploratory data analysis. This course runs over 6 weeks, with a 2-hour video lecture every week with live interactive coding using Jupyter notebooks.

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Lesson 1 - Introduction to Programming with Python

• Course overview & curriculum walkthrough
• First steps with Python and Jupyter notebooks
• A quick tour of variables and data types
• Branching with conditional statements and loops

Assignment 1 - Python Basics Practice

• Solve word problems using variables & arithmetic operations
• Manipulate data types using methods & operators
• Use branching and iterations to translate ideas into code
• Explore the documentation and get help from the community

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Lesson 2 - Next Steps with Python

• Branching with conditional statements and loops
• Write reusable code with Functions
• Working with the OS & Filesystem
• Assignment and course forum walkthrough

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Lesson 3 - Numerical Computing with Numpy

• Going from Python lists to Numpy arrays
• Working with multi-dimensional arrays
• Array operations, slicing and broadcasting
• Working with CSV data files

Assignment 2 - Numpy Array Operations

• Explore the Numpy documentation website
• Demonstrate usage 5 numpy array operations
• Publish a Jupyter notebook with explanations

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Lesson 4 - Pandas for working with tabular data

• Series
• Dataframes
• Operations
• Merging
• Grouping
• Joining

Assignment 3 - Pandas Practice

• Read and write different file types using Pandas data frames
• Manipulate rows, columns, empty values in data frames
• Merge, join and query data from multiple data frames
• Explore interoperability between Numpy & Pandas

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Lesson 5 - Visualization with Matplotlib and Seaborn

• Basic visualization with Matplotlib
• Beautiful visualizations with Seaborn
• Plotting directly from Pandas
• Other libraries: Plotly, Bokeh, Folium etc.

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Lesson 6 - Exploratory Data Analysis: A Case Study

• Working with Images using PIL
• Loading a dataset with Pandas
• Operations with numpy
• Visualization with Matplotlib & Seaborn

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Course Project - Exploratory Data Analysis

• Find a real-world dataset of your choice online
• Use Numpy & Pandas to parse, clean & analyze data
• Use Matplotlib & Seaborn to create visualizations