Data wrangling is an important part of the data science process and it is essential to master it before moving on to machine learning. This course is here for you if you want to learn how to do data wrangling in Python and are looking for a good selection of resources to help you with that.
This course is NOT for you if you don't know the basics of Python yet or if you want to jump directly to machine learning modeling (stay tuned for the Introduction to Python and Introduction to Machine Learning courses).
The course consists of the following topics:
- Introduction to NumPy.
- Introduction to Pandas and its data types.
- Processing of different data formats like XML, JSON, CSV, or text.
- Introduction to APIs.
The prerequisite of this course is the basic knowledge of Python, including the syntax and its data types. The exercises are shared through GitHub, so basic knowledge of GIT is also required.
By the end of the course, you will be able to:
- Process and convert raw data into formats needed for analysis.
- Define the basic Pandas and NumPy functions and data types.
- Apply different data wrangling techniques to prepare JSON and XML files.
- Understand the concept of APIs and access data through different ones
- Solve various data wrangling and reporting challenges using Pandas functions and data types.
You can select one of three available pricing plans. Each will give you an access to all course materials including the quizzes and challenges. Additionally, you can opt for mentor support through Slack and weekly mentor calls.
Course duration: ~50h