US $19.97

Build a Data Analysis Library from Scratch in Python

——   Created by Ted Petrou

Immerse yourself in a long, comprehensive project that teaches advanced Python concepts to build an entire library

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Course
58
Lessons
7h 32m
Lesson time
intermediate
Skill level

More about this course

Build a Data a Data Analysis Library from Scratch in Python targets those that have a desire to immerse themselves in a single, long, and comprehensive project that covers several advanced Python concepts. By the end of the project you will have built a fully-functioning Python library that is able to complete many common data analysis tasks. The library will be titled Pandas Cub and have similar functionality to the popular pandas library.

This course focuses on developing software within the massive ecosystem of tools available in Python. There are 40 detailed steps that you must complete in order to finish the project. During each step, you will be tasked with writing some code that adds functionality to the library. In order to complete each step, you must pass the unit-tests that have already been written. Once you pass all the unit tests, the project is complete. The nearly 100 unit tests give you immediate feedback on whether or not your code completes the steps correctly.

There are many important concepts that you will learn while building Pandas Cub.

  • Creating a development environment with conda
  • Using test-driven development to ensure code quality
  • Using the Python data model to allow your objects to work seamlessly with builtin Python functions and operators
  • Build a DataFrame class with the following functionality:
  • Select subsets of data with the brackets operator
  • Aggregation methods - sum, min, max, mean, median, etc...
  • Non-aggregation methods such as isna, unique, rename, drop
  • Group by one or two columns to create pivot tables
  • Specific methods for handling string columns
  • Read in data from a comma-separated value file
  • A nicely formatted display of the DataFrame in the notebook

It is my experience that many people will learn just enough of a programming language like Python to complete basic tasks, but will not possess the skills to complete larger projects or build entire libraries. This course intends to provide a means for students looking for a challenging and exciting project that will take serious effort and a long time to complete.

This course is taught by expert instructor Ted Petrou, author of Pandas CookbookMaster Data Analysis with Python, and Exercise Python.

Who this course is for:

  • Students who understand the fundamentals of Python and are looking for a longer more comprehensive project covering advanced topics that they can immerse themselves in.

58 Lessons

3 mins
Introduction
free preview
Project Genesis
10 mins
Project Overview
free preview
14 mins
Pandas Cub Examples
3 mins
Downloading the Material from GitHub
Environment Setup
3 mins
Opening the Project in VS Code
9 mins
Setting up the Development Environment
8 mins
Test-Driven Development
14 mins
Installing an IPython Kernel for Jupyter
Getting Ready to Code
7 mins
Inspecting the __init__.py File
7 mins
Importing Pandas Cub
9 mins
Manually Test in a Jupyter Notebook
2 mins
Getting Ready to Start
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About the instructor

Ted  Petrou
Ted Petrou
  • 1 review
  • 1 courses

I am the author of Pandas Cookbook and Master Data Analysis with Python, highly rated texts on performing real-world data analysis with Pandas.

I am …

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Class benefits

  • Certificate of Completion
  • 30 day satisfaction guarantee
  • 24/7 streaming access
  • Direct teacher access
  • 7h 32m of on-demand video
  • 1 downloadable file
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