Pandas >> Data Combination(1): merge()

In this tutorial, we will explain how to combinate/join multiple DataFrames using merge().

Table of Contents

• Introduction to merge()
• Data Preparation
• JOIN
  - INNER JOIN
  - LEFT JOIN
  - RIGHT JOIN
  - OUTER JOIN
  - CROSS JOIN
  - LEFT EXCLUSIVE/ANTI JOIN
  - RIGHT EXCLUSIVE/ANTI JOIN
  - FULL OUTER EXCLUSIVE/ANTI JOIN
• JOIN by multiple columns
• Removing duplicate columns
• Specify suffixes for columns with the same name
• Conclusion

Introduction to merge()

Firstly, let’s see the definition of the merge() function.

pandas.merge: Merge DataFrame or named Series objects with a database-style join.
https://pandas.pydata.org/docs/reference/api/pandas.merge.html

pandas.merge(left, right, how=‘inner’, on=None, left_on=None, right_on=None, left_index=False, right_index=False, sort=False, suffixes=(‘_x’, ‘_y’), copy=True, indicator=False, validate=None)

Let’s explain the main parameters.

• left: The DataFrame on the left.
• right: The DataFrame on the right.
• how: How to join the two DataFrames. There are…