How to do a vLookup in Python Using Pandas?

Introduction:

In this tutorial we are learning about how we can Do a vLookup in Python using pandas. Vlookup is mostly used for vertical files. Vlookup is a function that connects two different tables according to certain conditions, where at least 1 common attribute (column) must exist between the two tables. After doing this, we get a table containing all the data from the two tables where the data matches. We can do Vlookup in pandas by using the merge() function. Joins work the same way as Joins in SQL. We can work together on Table 1 or Table 2. Merging 2 tables can do many things.

Syntax:

The syntax to do a vLookup in Python using pandas is given below -

Parameter:

The parameter to do a vLookup in Python using pandas is given below -

• dataframe1: The dataframe1 must be merged.
• dataframe2: The dataframe2 must be merged.
• how: {left, right, inner, outer} indicates the merging system.
• on: Specifies the column or index name used to perform the join.
• suffixes: Suffix for overlapping columns. Use values for exceptions (False, False).
• validate: If specified, the merging type is checked. The merging can be (one-one, one-many, many-one, many-many).

Program Code:

Let us consider the 2 tables we want to work on. The first table contains the students' data, and the second column contains the data about the courses they took. The code displays data in two tables. So, the code is given in below -

Output:

Now, we compile the given code in Python. Then after successful compilation, we run this code. The occuring output is given below -

We can also perform vLook in different types of joining like Right Joining, Left Joining, Inner Joining, and Outer Joining. Now we discuss these in below -

1. Right Join:

The right join is similar to the left join. Here, the output file contains all the rows from the second file or dataframe and the matching rows from the first file. If the rows in the first row do not match, they will be replaced with NaN.

Program Code:

Now, we give a program code to do a vLookup in Python using the pandas Right Join concept. So, the code is given in below -

Output:

Now, we compile the given code in Python. Then after successful compilation, we run this code. The occurring output is given below -

2. Left Join:

The left join is similar to the Right join. The Left join function returns all rows from the first dataframe and matching rows from the second file. If the lines in the second dataframe do not match, they will be replaced with NaN.

Program Code:

Now, we give a program code to do a vLookup in Python using the pandas Left Join concept. So, the code is given in below -

Output:

Now, we compile the given code in Python. Then after successful compilation, we run this code. The output is given below -

3. Inner Join:

Inner joins produce data only for rows where two rows meet the condition. To do an inner join, you can specify inner as a keyword in the how.

Program Code:

Now, we give a program code to do a vLookup in Python using the pandas Inner Join concept. So, the code is given in below -

Output:

Now, we compile the given code in Python. Then after successful compilation, we run this code. The occurring output is given below -

4. Outer Join:

An Outer join provides an output file consisting of rows from two dataframes. If the rows match, the value will be displayed; otherwise, NaN will be displayed for the rows that do not match.

Program Code:

Now we give a program code to do a vLookup in Python using pandas outer Join concept. So, the code is given in below -

Output:

Now, we compile the given code in Python. Then after successful compilation, we run this code. The occurring output is given below -

Conclusion:

In this tutorial we are learning about how to Do a vLookup in Python using pandas. The Pandas library makes it very easy to simulate the VLOOKUP function. Mapping and organizing information is an important step in the data preparation process, especially when working with normalized datasets from databases. Pandas is a powerful data processing tool that provides a rich set of tools to process and manage data for analysis. We can do Vlookup in pandas by using the merge() function. Vlookup is a function that connects two different tables according to certain conditions, where at least 1 common attribute (column) must exist between the two tables. VLookup can perform different types of joining like Right Joining, Left Joining, Inner Joining, and Outer Joining. Here, we also share the program code of these joining to Do a vLookup in Python using pandas.