Course Summary

Key takeaways

Data wrangling is the process of cleaning and organizing data for analysis. The data wrangling process includes tasks such as removing duplicates, filling in missing values, and formatting data for use in a specific analysis or application.

The data wrangling process

Data wrangling is an important part of the data science process, and we typically perform this process during the data preparation phase of a data science project. In a typical data science project, data wrangling is one of several phases, including data gathering, data preparation, modeling, and evaluation.

Data wrangling tools

There are a variety of data wrangling tools and techniques that can be used in Python, including built-in functions and libraries, such as pandas and ...