Moving from categories to values.

1. Create an additional column(s) that converts the income ranges to a number.
2. Create an additional column(s) that converts the age ranges to a number.
3. Create an additional column(s) that converts the school groupings to a number.

• str.replace('’, ‘9’)
• astype(‘float’)
• pd.concat(axis=1)

Why are we converting the columns to numerical values?

One-hot encoding

1. One-hot encode all columns that have categories.
2. Convert all yes/no responses to 1/0 numeric.

• pd.get_dummies
• pd.factorize(x)
• What is the difference?

Which columns are going to be problematic for the function pd.get_dummies()?

What is pd.get_dummies() default behavior for the columns that are created? Should we change that behavior?