Accessing data within a DataFrame
A data frame consists of both rows and columns, and has constructs to select data from specific rows and columns. These selections use the same operators as a Series, including [], .loc[], and .iloc[].
Because of the multiple dimensions, the process by which these are applied differs slightly. We will examine these by first learning to select columns, then rows, a combination of rows and columns in a single statement, and also by using Boolean selections.
Additionally, pandas provides a construct for selecting a single scalar value at a specific row and column that we will investigate. This technique is important and exists because it is a very high-performance means of accessing these values.
Selecting the columns of a DataFrame
Selecting the data in specific columns of a DataFrame is performed by using the [] operator. This differs from a Series, where [] specified rows. The [] operator can be passed either a single object or a list of objects representing...
