16. Merge, join, and concatenate
Merge, join, and concatenate
pandas provides various facilities for easily combining together Series, DataFrame, and Panel objects with various kinds of set logic for the indexes and relational algebra functionality in the case of join / merge-type operations.
Concatenating objects
The concat function (in the main pandas namespace) does all of the heavy lifting of performing concatenation operations along an axis while performing optional set logic (union or intersection) of the indexes (if any) on the other axes. Note that I say “if any” because there is only a single possible axis of concatenation for Series.
Before diving into all of the details of concat and what it can do, here is a simple example:
In [1]: df1 = pd.DataFrame({'A': ['A0', 'A1', 'A2', 'A3'],
...: 'B': ['B0', 'B