Concatenate DataFrames along row and column.In this tutorial, you will practice a few standard techniques. Thankfully you have the most popular library in python, pandas to your rescue! pandas provides various facilities for easily combining together Series, DataFrames, and Panel objects with various kinds of set logic for the indexes and relational algebra functionality in the case of join / merge-type operations. Even if you want to build some machine learning models on some data, you may need to merge multiple csv files together in a single DataFrame. People who work with SQL like query languages might know the importance of this task. You may need to bring all the data in one place by some sort of join logic and then start your analysis. It is one of the toolkits which every Data Analyst or Data Scientist should master because in almost all the cases data comes from multiple source and files.
Joining and merging DataFrames is the core process to start with data analysis and machine learning tasks. Well, what is the first thing that comes to your mind? Join them of course!
Have you ever tried solving a Kaggle challenge? If yes, you might have noticed that in most of the challenges, the data provided to you is present in multiple files, with some of the columns present in more than one files.
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