The pandas DataFrame object extends the capabilities of the Series object into two-dimensions. A Series object adds an index to a NumPy array but can only associate a single data item per index label, a DataFrame integrates multiple Series objects by aligning them along common index labels. This automatic alignment by index label provides a seamless view across all the Series at each index label that has the appearance of a row in a table.

A DataFrame object can be thought of as a dictionary-like container of one or more Series objects, or as a spreadsheet, probably the best description for those new to pandas is to compare a DataFrame object to a relational database table. However, even that comparison is limited, as a DataFrame object has very distinct qualities (such as automatic data alignment of series) that make it much more capable for exploratory data analysis than either a spreadsheet or relational database table.

Because of the increased dimensionality...