UFOs and preprocessing
1. UFOs and preprocessing
Now it's time for you to apply the concepts you've learned throughout this course to a brand new dataset.2. Identifying areas for preprocessing
The final chapter in this course will walk you through an entire preprocessing workflow on a dataset related to UFO sightings. Each row in this dataset contains information like the location, the type of the sighting, the number of seconds and minutes the sighting lasted, a description of the sighting, and the date the sighting was recorded. As you might imagine, there are a number of preprocessing tasks that need to be done prior to doing any modeling on this dataset.3. Important concepts to remember
In the very first chapter of this course, we covered things like removing missing data, altering the type of columns in a DataFrame, and creating training and test sets based on class distribution. Some useful pandas functions to remember are dropna and isna for missing data, astype for type conversion, and the stratify parameter in the train_test split_function.4. Let's practice!
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