07-04, 17:00–17:20 (Africa/Cairo), Hall 2 (Ground Floor)
Missing data is common when working with real-world data.
In this talk, we will visualize missing data and discuss patterns of missing data and how to handle them.
Did the cat eat your CSV file? Did it eat only every third record?
Missing data is prevalent in real-world data and can be missing for various reasons.
In this talk, we will talk about the different patterns of missing data and what are the best practices for handling each. In addition, we will show how to visualize missing data as part of our data exploration phase to understand our data better.
As python is the leading programing language for data scientists and data analysts, we will use pandas, missingno, scikit-learn and other tools to demonstrate those ideas and explore the data.
Hebrew
Target audience –Data Scientists
A Data Scientist turned into an Engineering Manager