Description
Build a Data Analysis Library from Scratch in Python course. Build a Data Analysis Library from Scratch in Python is for those who want to immerse themselves in a single, long, comprehensive project that covers many advanced Python concepts. By the end of the project, you will have built a fully functional Python library that will be able to perform many common data analysis tasks. This library will be called Pandas Cube and will have similar functionality to the popular Pandas library. This course focuses on developing software within the vast ecosystem of tools available in Python. There are 40 precise steps you will need to complete to complete the project. During each step, you will be tasked with writing code that adds functionality to the library. To complete each step, you will need to pass previously written unit tests. After passing all unit tests, the project is complete. Nearly 100 unit tests give you instant feedback on whether your code completed the steps correctly or not. There are several important concepts you will learn while creating Baby Panda.
- Creating a development environment with conda
- Use test-driven development to ensure code quality
- Use the Python data model to allow your objects to work seamlessly with Python’s built-in functions and operators
- Create a DataFrame class with the following functionality:
- Select a subset of data with the bracket operator
- Aggregation Methods – Sum, Min, Max, Average, Median, etc.
- Non-cumulative methods like isna, unique, rename, drop
- Group by one or two columns to create a pivot table
- Special ways to handle string columns
- Read data from a comma separated values file
- Beautifully formatted display of a DataFrame in a notebook
My experience is that many people learn a programming language like Python to do basic tasks, but do not learn the skills to complete larger projects or create entire libraries. This course aims to provide a means for students looking for a challenging and exciting project that requires serious effort and long time to complete. This course is taught by expert instructor Ted Petro, author of Pandas Cookbook, Data Analysis with Python, and Python Fundamentals Professor.
What you will learn in the Build a Data Analysis Library from Scratch in Python course
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Create a fully functional Python library similar to pandas that you can use for data analysis.
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Complete a large and comprehensive project
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Test-Driven Development with Pytest
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Setting up an environment with conda
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Advanced Python topics such as special methods and property decorators
This course is suitable for those who
- Students who understand the basics of Python and are looking for a longer, more comprehensive project that covers in-depth topics.
Specifics of building a data analysis library from scratch in a Python course
- Publisher: Udemy
- Lecturer: Ted Petro
- Training level: Beginner to advanced
- Training duration: 7 hours and 36 minutes
Title of Build a Data Analysis Library from Scratch in Python Course
Prerequisites for Building a Data Analysis Library from Scratch in Python Course
- Students should know the fundamentals of Python. This is an intermediate/advanced course.
- Should feel comfortable using and iterating over lists, tuples, sets, and dictionaries
- Exposure to numba and pandas is helpful
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