Concatenation in pandas is the process of combining the data from two or more pandas objects into a new object. Concatenation of the Series objects simply results in a new Series, with the values copied in sequence.
The process of concatenating the DataFrame objects is more complex. The concatenation can be applied to either axis of the specified objects, and along that axis pandas performs relational join logic to the index labels. Then, along the opposite axis, pandas performs alignment of the labels and filling of missing values.
Because there are a number of factors to consider, we will break down the examples for concatenation into the following topics:
- Understanding the default semantics of concatenation
- Switching the axis of alignment
- Specifying the join type
- Appending data instead of concatenation
- Ignoring the index labels