Data Wrangling With Python/

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Merging DataFrames

Merging DataFrames

Learn how to merge DataFrames using Python.

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Introduction

Merging DataFrames involves combining two or more DataFrames into one. We combine DataFrames using the merge() function and the concat() function to create a new rich dataset we can use for further analysis, such as descriptive analysis or machine learning.

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Example of merging DataFrames
Example of merging DataFrames

Merging using a common column

We use the merge() function to combine data from two or more DataFrames based on a common column. This function can be particularly useful when working with large datasets because it allows us to quickly and easily merge them without manually matching and combining them.

It's important to note that the final DataFrame will only include records in which the values of the common column match. Records that only exist in only one table will be excluded.

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main.py
employment-data.csv
demographics.csv
ID,Company,Position,Salary,Start Date
1,Acme Inc,Manager,50000,01/01/2020
2,XYZ Corporation,CEO,100000,01/01/2021
3,ABC Company,CTO,80000,01/01/2019
4,Def Corp,Developer,70000,01/01/2018
5,MNO Enterprises,Sales Representative,40000,01/01/2017
6,PQR Inc,HR Manager,60000,01/01/2016
7,STU Enterprises,Marketing Manager,50000,01/01/2015
8,VWX Group,Accountant,40000,01/01/2014
9,YZ Companies,Technical Writer,60000,01/01/2013
10,123 Enterprises,Project Manager,70000,01/01/2012
11,223 Treva,Technical Manager,170000,01/01/2012
12,133 Leakey,Project Manager,80000,01/01/2012
13,213 Yuno,Operations Director,250000,01/01/2012
14,134 Hons,Project Manager,90000,01/01/2012

We see a forward slash displayed in the first line of the output because we have further columns in our file to ...