@SamiMouloudMerkouche

Im datascience learner I use datacamp as my learning platform and your video has helped a lot with that.Thanks for the amazing explanation and keep going we need more people like you.

@Richardo-o3z

Right away from Ghana , every bit of your explanation is on point and you have had so much impact on my journey as a data analyst. Thank you  Alex

@casual_gaming001

Thanks alot, i have been on youtube and Stack overflow all evening. Best explanation

@venudunde3453

thanks Alex, nice explanation

@abdulkadirguven1173

Nice tuto. Thank you very much.

@kennyc4666

Thank you, that is very useful information!

@pamm6281

Well Explained Sir.... Thanku so much

@t_millagain5255

Definitely what i needed 👍🏽

@danielachugo5737

Thanks so much Alex ❤

@josemariahernandezlara4061

The best!

@vidyutroy2868

thank you for sharing such tutorials

@shalinivijayravikumar9713

"Hi Alex, could you please upload a video on NumPy for beginners? It would be incredibly helpful for me, and I would greatly appreciate it."

@stefanvilcu8260

wonderful video

@hello-fs9bt

Thank you very much! I don't know how to tell you how much this video help me but you just saved me a lot of time! Very well-explained, easy to understand! I wish you all the good things in life.

@khadijashaikh9617

please make a video on numpy library in python

@sachinmaroky4600

thank you

@ArtyomAshigov-l8j

I watched other videos about Pandas, they were really good.
I just wrote a comment here, that was probably deleted and I am not sure why

@AidenWithers37

What are most people using as a solution to merging 3 or more dataframes, just running multiple merges separately, or is there a better way to handle this?

@garvjain3462

🎯 Key Takeaways for quick navigation:

Merging, joining, and concatenating data frames in Pandas is crucial for combining separate data frames into one.
Types of joins: inner join (default), outer join, left join, and right join.
Cross join compares each value from the left data frame with every value from the right data frame.
The join function is used to join data frames based on specified indexes, but it requires more manual configuration compared to the merge function.
Concatenation places one data frame on top of another (vertically) or side by side (horizontally).
The append function is deprecated and should be replaced with the pandas.concat function for appending rows from one data frame to another.
Understanding these operations is essential for working with multiple data sources in Pandas.

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@yilmazah

Selam. Oglun cok sansli, ona duskun bir babasi var masallah