Data from two or more DataFrames can be combined using a left outer join in Pandas. In a left outer join, all the rows from the left DataFrame are included in the result, along with the matching rows from the right DataFrame.
Several use cases exist for a left outer join when using the Pandas library in Python. Here are a few examples:
- Data cleaning: A left outer join can be match and merge data from two DataFrames with different formats or structures. This can be useful when trying to standardize or clean up data from different sources.
- Data exploration: A left outer join can be used to combine data from different DataFrames to create a new DataFrame with additional columns for analysis and visualization.
- Data pre-processing: A left outer join can be used to combine the data from different data sources. It is useful in data pre-processing, where we can merge data from different data sources and remove duplicate data entries.
- Data manipulation: A left outer join can be used to combine data based on a common key and manipulate the data to create a new DataFrame for further analysis.
- Combining datasets: When combining data from two or more datasets, a left outer join can be employed. In this case, the right DataFrame represents the "additional" or "supplementary" data, and the left DataFrame represents the "primary" or "base" dataset.
Here is how you can implement a left outer join using Pandas:
Preview of the output that you will get on running this code from your IDE.
In this solution we used pandas library of python.
Follow the steps carefully to get the output easily.
- Download and install PyCharm on your Computer.
- Create new python file in your IDE.
- Copy the code using the "Copy" button above, and paste it in a Python file.
- Install Pandas from settings (python interpreter).
- Import Pandas library.
- Run the file to generate the output.
I hope you found this useful. I have added the link to dependent libraries, version information in the following sections.
I found this code snippet by searching for ' Pandas left outer join' in kandi. You can try any such use case!
I tested this solution in the following versions. Be mindful of changes when working with other versions.
- The solution is created in PyCharm 2022.3.
- The solution is tested on Python 3.11.1
- Pandas version-1.5.2.
Using this solution, we are able to do Pandas left outer join with simple steps. This process also facilities an easy way to use, hassle-free method to create a hands-on working version of code which would help us to use Pandas left outer join.
Python 38689 Version:v2.0.2 License: Permissive (BSD-3-Clause)