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Course Recap
3. Data preprocessing
Final challenge


Great! In Part 4 of the course, we learned some basic data preprocessing. Let's make use of that knowledge now.


The country column is full of NaN values. Let's change that – replace all those NaN values with "New Zealand"

Sort the whole dataset by the price column – we want to identify outliers. You can see that the first few rows look okay, but the very last row is definitely incorrect. Apart from that, you can see that the last few rows have much higher prices than the rest of the set, exceeding 4500 NZD.

Stuck? Here's a hint!

Use the .fillna() and .sort_values() functions.

Do not assign sorted dataset to the variable.