Categorical variables and standardization

1. Categorical variables and standardization

The next tasks we're going to tackle are dealing with some of the categorical variables and standardization in the UFO dataset.

2. Categorical variables

Recall that there are a number of categorical variables in the UFO dataset, including location data and the type of the encounter. The following exercises will be about dealing with these categorical variables. There are a number of categorical variables that need to be one hot encoded. Remember that we can one hot encode variables with pandas' get_dummies function.

3. Standardization

In addition, we need to standardize the seconds column. Recall that we can check the variance of a column with the var method. After we've done that, we can log normalize the column using NumPy's log function.

4. Let's practice!

Now you'll take the next steps in preprocessing the UFO dataset.

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