Data cleaning is the least glamorous segment of a data scientist's routine, yet easily takes up over 80% of the show. Today, we'll cover our bases in pandas by learning how to (1) deal with missing data, (2) create new features using lambda apply, and (3) data from several sources. Later in the week, we'll get introduced to handling time series data and text data.
| Activity | Content Link | Last Updated |
|---|---|---|
| Workshop Activities |  |
09-22-2020 |
| Lab |  |
09-27-2021 |
| Project 2 | |
09-19-2020 |
Today's cleaning.ipynb notebook was adapted from Ben Artuso, s/o for his help!