Combining and Merging Datasets

Data contained in a pandas objects can be combined together in a number of ways:

• The merge() method connects rows in DataFrames based on one or more keys.
• The concat() method concatenates or “stacks” together objects along an axis.

The merge() method may be familiar to users of SQL or other relational databases. If you aren’t familiar with it, don’t worry! It’s easy to learn and we’ll present the concepts of merging with very simple examples to make the steps easy to follow. Our focus here is not to learn SQL, we only want to go through the widely used and very important inner and outer joining operations for data wrangling.

It’s important to note that merging operations may give NaN in the output. They also need to be treated according to the circumstances or requirements during data analysis.

Let’s learn these methods with examples.

Database-style DataFrame joins

Merge or join operations combine datasets by linking rows using one or more keys. These operations are central to relational databases (for example, SQL-based databases).

Let’s create two DataFrames, df1 and df2 ...