Description
Build a Data Analysis Library from Scratch in Python course. Building a Data Analysis Library from Scratch in Python is aimed at those who want to immerse themselves in a single, long, comprehensive project that covers several advanced Python concepts. By the end of the project, you will have built a fully functional Python library capable of completing many common data analysis tasks. This library will be called Pandas Cub and will have the same functionality as 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 must complete to complete the project. During each step, you’ll be tasked with writing code that adds functionality to the library. To complete each step, you must pass the previously written unit tests. After passing all the unit tests, the project is complete. Almost 100 unit tests give you instant feedback on whether your code completed the steps correctly. There are many important concepts that you will learn when making a 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 subsets of data with the bracket operator
- Aggregation methods – sum, minimum, maximum, average, median, etc.
- Non-cumulative methods such as isna, unique, rename, drop
- Group by one or two columns to create a pivot table
- Special methods for handling string columns
- Read data from a comma-separated value file
- A beautifully formatted display of a DataFrame in a notebook
My experience is that many people learn enough of a programming language like Python to do basic work, but not the skills to complete larger projects or build complete libraries. This course aims to provide a means for students looking for a challenging and exciting project that requires serious effort and a 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 Build a Data Analysis Library from Scratch in Python course
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Build 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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Creating an environment with Konda
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Advanced Python topics such as special methods and property decorators
This course is suitable for people who
- Students who understand the basics of Python and are looking for a longer, more comprehensive project that covers advanced topics that they can immerse themselves in.
Specifications of Build a Data Analysis Library from Scratch in Python course
- Publisher: Udemy
- teacher: Ted Petrou
- Training level: beginner to advanced
- Training duration: 7 hours and 36 minutes
Titles of Build a Data Analysis Library from Scratch in Python course
Prerequisites of the Build a Data Analysis Library from Scratch in Python course
- Students must know the fundamentals of Python. This is an intermediate/advanced course.
- Must feel comfortable using and iterating through lists, tuples, sets, and dictionaries
- Exposure to numpy and pandas is helpful
Images of Build a Data Analysis Library from Scratch in Python course
Sample video of the course
Installation guide
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English subtitle
Quality: 720p
download link
File(s) password: www.downloadly.ir
Size
3.6 GB
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