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Identifying outliers

Let's keep at it with our laptops dataset and tackle some outliers hiding away. In this exercise, we'll stick to the first technique we discussed in the slides using standard deviations to identify extreme values, since this method is more common in practice.

You'll compute the descriptive statistics and outlier boundaries, and then identify the rows with them before dropping them from the dataset. You'll be working primarily with the Price column here.

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Practicing Statistics Interview Questions in Python

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# Calculate the mean and std
mean, std = ____, ____
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