Another part of tidying data involves transforming the existing data into another presentation. This may be needed for the following reasons:
- Values are not in the correct units
- Values are qualitative and need to be converted to appropriate numeric values
- There is extraneous data that either wastes memory and processing time, or can affect results simply by being included
To address these situations, we can take one or more of the following actions:
- Map values to other values using a table lookup process
- Explicitly replace certain values with other values (or even another type of data)
- Apply methods to transform the values based on an algorithm
- Simply remove extraneous columns and rows
We have already seen how to delete rows and columns with several techniques, so we will not reiterate those here. Now we will cover the facilities provided by pandas for mapping...