Merging DataFrames in Pandas | Python Pandas Tutorials 

This is such a solid explanation on this. If someone is familiar with SQL JOINS, they should feel right at home here (with a few exceptions of course). Don't sleep on Pandas, and don't sleep on AtA videos.

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.

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

Really appreciate how you explain these concepts so clearly. As always, THANK YOU ALEX! You are the BEST!

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

you explain better than my professor....thank you!

Thank you Alex ! Well explained and very simple to understand ! Great as always!! 👏

Excellent Video. Very well explained. Thanks for doing it.

Thank you alex. You are amazing....

Thanks Alex for the amazing Explanation. I learn a lot by watching your video. Are we expecting more pandas tutorials in the upcoming video?

Dear Alex, Thanks for your nice explanation..!

Thanks for the amazing explanation. This is the first playlist I know you from and Your way of illustration is pretty simple and helped me get confusing pandas terms. Many thanks again ❤

This is so helpful. Thank you!

thanks Alex, nice explanation

You nailed it! Thank u very much sir!!!

Very useful series, very well explained. Thank you very much for sharing your knowledge.

Nice tuto. Thank you very much.

Many thanks, clear and useful

Thank you!)

Many Thanks for this clear explanation :)

Well Explained Sir.... Thanku so much

Love this explanation. It will help me to go through my exam :))

Excellent Thanks

Wished I saw this video earlier....I would have saved days of wasted hours with simple concatenate function. Tnk Alex

hi, thank you for the explanation. I liked it already but still want to comment to appreciate your effort.

Definitely what i needed 👍🏽

Thank you for concise and interesting video. I ve learned everything I wanted

thank you for sharing such tutorials

Awesome ❤❤ Very well explained.....

You have a new subscriber here

wonderful video

The best!

Alex the king 👑👑

bro I'm a data scientist student, it's the first time I understand that in such a stunningly beautiful way

Thanks. What do you think about capability of these compared to power query in excel?

please make a video on numpy library in python

I don't know if its because I learnt sql first but I feel its more straight forward than python... Also doing this a month later, the append still works without any warning 😅 I wonder python would decide to remove

thank you

This is set theory... union, intersection, set difference and cross product

wonder how many Data Analysts you made out there !!

Qestion is there a function of merge as well in Sql specifically PostgeSQL?

Just one doubt is it possible to join on any condition other than equality condition in pandas like we do in SQL for example T1.Col1 < T2.Col1

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

Need notes for this. Could you please share this

how do you put image in the notebook?

"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."

I got an error message on the cross join and it isn't visible in the menu with SHIFT + TAB either. Interesting.

Can we do 2 dataframes side by side in pyspark? Similar to concatenate here

Great

merge doesnt work in vsc? says no attribute

how to do union in dataframe?

Alex tell me the truth, are you a divine angel?

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.

Merge is bettter hands down.

wait how did you get the file path link? Sorry I am not computer savy

🎯 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. Made with HARPA AI

Barromir :O

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

Dark mode when?

Barromir= Boromir

1:38 😂🤣🤣

Legolas 😂😂

I thought Lord of the Rings sponsored this video.

Hey Alex, thanks for these videos they are great :) However i am getting different results from you when using df1.merge(df2), its showing IDs 1001,2,6,7,8 - and i cant figure out why, has soimething changed in the most up to date python? (also shows the same if i use df1.merge(df2, how = 'inner', on = ['FellowshipID', 'FirstName'])but with _x and y_ for Age. FellowshipID FirstName Age_x Age_y 0 1001 Frodo 50 50 1 1002 Samwise 39 39 2 1006 Legolas 2931 2931 3 1007 Elrond 6520 6520 4 1008 Barromir 51 51