3 Pandas Functions for DataFrame Merging

It's common in the data work to have multiple datasets from the data source or as the result of data analysis. Sometimes, we want to merge two or more different datasets for various reasons. For example: <ul> <li>We want to integrate data from multiple data sources into one dataset for deeper analysis</li> <li>We want to perform missing value imputation from one dataset to another dataset</li> <li>We split the dataset to perform different analyses on each dataset, and we want to return them into one dataset</li> </ul> Merging datasets is possible with the available functions from the Pandas package. In this article, we will learn three different functions for merging with the coding example. Let's get into it. <h1>1. merge</h1> The <code>merge</code> function is the go-to function in Pandas to perform basic dataset merging. This function would combine two datasets based on the given dataset index or column. For example, let's create a dataset example to show how <code>merge</code> function works. <a href="https://pub.towardsai.net/3-pandas-functions-for-dataframe-merging-5ad29de0b5b3">Read More</a>