Difference(s) between merge() and concat() in pandas

Michael Zippo

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What"s the essential difference(s) between pd.DataFrame.merge() and pd.concat()?

So far, this is what I found, please comment on how complete and accurate my understanding is:

.merge() can only use columns (plus row-indices) and it is semantically suitable for database-style operations. .concat() can be used with either axis, using only indices, and gives the option for adding a hierarchical index.
Incidentally, this allows for the following redundancy: both can combine two dataframes using the rows indices.
pd.DataFrame.join() merely offers a shorthand for a subset of the use cases of .merge()

(Pandas is great at addressing a very wide spectrum of use cases in data analysis. It can be a bit daunting exploring the documentation to figure out what is the best way to perform a particular task. )

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Manuel Nickolson

Massachussetts | 2023-03-29

Thanks for explaining! I was stuck with Difference(s) between merge() and concat() in pandas for some hours, finally got it done 🤗. Will get back tomorrow with feedback

Xu Wu

Prague | 2023-03-29

io Python module is always a bit confusing 😭 Difference(s) between merge() and concat() in pandas is not the only problem I encountered. Will use it in my bachelor thesis

Schneider Lehnman

Singapore | 2023-03-29

exp is always a bit confusing 😭 Difference(s) between merge() and concat() in pandas is not the only problem I encountered. Will use it in my bachelor thesis