Merge, Join, and Concatenate DataFrames using Pandas:

A data frame is a 2-D data structure in which the data is aligned in the form of rows and columns. A data frame is capable of performing arithmetic and conditional operations. It also has a mutable size in Python for data science.

For performing this operation e need the pandas and the numpy module.

Code 1: Concatenation of DataFrames.

The function concat() is a function that is responsible for all the concatenation operations along an axis while the performance of optional set logic (union or intersection) of the indexes on the other axes.

Merge, Join, and Concatenate DataFrames using Python for Data Science

OUTPUT:

Merge, Join, and Concatenate DataFrames using Python for Data Science

Code 2: Merging of DataFrames.

In pandas, there is a single function merge() which acts as the entry point for all standard database join operations between the data frame objects.

Merge, Join, and Concatenate DataFrames using Python for Data Science

OUTPUT:

Code 3: Joining of DataFrames.

OUTPUT:

So, to learn more about it in python for data science, you can check this and this as well.

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