pandas has an array of special operators for generating, aggregating, transforming, reading, and writing data from and to a variety of data types, such as number, string, date, timestamp, and time series. The basic operators in pandas were introduced in the previous chapter. In this chapter, we will continue that discussion and elaborate on the methods, syntax, and usage of some of these operators.

Reading this chapter will allow you to perform the following tasks with confidence:

• Writing custom functions and applying them on a column or an entire DataFrame
• Understanding the nature of missing values and handling them
• Transforming and performing calculations on series using functions
• Miscellaneous numeric operations on data 

Let's delve into it right away. For the most part, we will generate our own data to demonstrate the methods.

The following topics will be covered in this chapter: 

• Writing and applying one-liner custom functions
• Handling missing values
• A survey of methods on series
• pandas string methods
• Binary operations on DataFrames and series
• Binning values
• Using mathematical methods on DataFrames