Learning Pandas

Transforming Data

Another part of tidying data involves transforming 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 ...