A quick how-to guide for merging Pandas DataFrames in Python. Today we are going to look at using Pandas built-in .merge() function to join two data sources using several different join methods.
As Data Scientist, we will often find that we are required to analyse data from multiple data sources at the one time. To be successful at achieving this, we need to be able to merge different data sources using a variety of methods efficiently. Today we are going to look at using Pandas built-in
.merge() function to join two data sources using several different join methods.
For those of you that are new to data science or haven’t been exposed to Python Pandas yet, we recommend first beginning with Pandas Series & DataFrame Explained or Python Pandas Iterating a DataFrame. Both of these articles will provide you with the installation instructions and background knowledge for today's article.
The Pandas built-in function
.merge() provides a powerful method for joining two DataFrames using database-style joins.
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