Handling Missing Data p. 10 Data Analysis with Python and Pandas Tutorial

Welcome to Part 10 of our Data Analysis with Python and Pandas tutorial. In this part, we re going to be talking about missing or not available data. We have a few options when considering the existence of missing data. Ignore it Just leave it there Delete it Remove all cases. Remove from data entirely. This means forfeiting the entire row of data. Fill forward or backwards This means taking the prior or following value and just filling it in. Replace it with something static For example, replacing