Introduction
Missing values
Duplicate rows
Outliers
10. Sorting to find outliers
Joining datasets
Summary

Instruction

Good job. You could see that the temperature value for the year 2000 was 280. This is obviously impossible.

Outliers are a very broad topic. For instance, there are numerous ways to identify outliers in a given dataset. You could draw a histogram, calculate the standard deviation and compare it against all values, and so on. In short, there are many options.

An easy way is to sort the values by a given column and see what comes at the very beginning and at the very end of the DataFrame.

Exercise

Sort the values in the temperatures variable by temperature in ascending order.

You can see that there are no specific outliers at the beginning of the sorted dataset, but there is indeed one huge value at its end (280.0 for the year 2000).

Stuck? Here's a hint!

Use function sort_values(by='column')