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Pandas functions: merge vs. join vs. concat

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Pandas is very useful but sometimes it could be hard to understand the differences between some functions that work towards similar goals. In this video, let's see how merge, join and concat works and what their differences are.
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Опубликовано:

14 авг 2024

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Комментарии : 62

@misraturp 2 года назад

Which Pandas functions would you like me to compare/explain next?

@YogiNotTheBear007 2 года назад

hi, could you please explain cut, apply and map?

@misraturp 2 года назад

@@YogiNotTheBear007 Added to the list! Thank you!

@arshad1781 2 года назад

Make a complete video series A to Z step by step on Data science, Machine learning, Deep learning like hot 🔥 topic

@misraturp 2 года назад

@@arshad1781 Good idea, thanks Arshad!

@zulhishamtan4308 6 месяцев назад

Merge_asof() is awesome for time series merging. Hope you can consider to make a video for it. Thanks again.

@mosama22 5 месяцев назад

Do you know what I really LOVE about your videos, you COVER THE WHOLE TOPIC, so if we talking about reshaping for example you mentioned all the 8 functions could be used and then you chose. Having the full picture really helps a lot. Even if you are an expert, going back to your videos, sometimes help remind us what other options do we have, or what other functions we might forget about.

@mosama22 5 месяцев назад

Thank you for the beautiful videos, I'd just appreciate if you added a link to the data set and the notebook you use for each video please, so we can follow up with you. Thanks a million again for the beautiful videos 🙂

@bethuelthipe-moukangwe7786 Год назад

The lessons about pandas are now making sense to me, especially on how to use groupby, apply ,apply map and lambda function. Big thanks Ms Misra Turp.

@oscar-expertprojectmanager6733 11 месяцев назад

Thank you Misra. Great explanation on the Pandas functions: merge vs. join vs. concat. One comment I would make about using pd.set_options('display.max_rows', None) and pd.set_options('display.max_columns', None); If your dataset is large, you run the risk of crushing your notebook, and you would have to go through a process to fix it.

@kentjordan4658 Год назад

May you provide the dataset? Thanks! 😄

@gaganbhattacharya9890 8 месяцев назад

I didn't know what does ''left_on & right_on' means in merge & the difference between merge & join but now I understand! Thanks!

@zulhishamtan4308 6 месяцев назад

Thank you for the sharing... Awesome... I learnt a lot...

@Xirato95 Год назад

Thank you for your clear explanations! I love it how you explain it while using a simple example and go through it step by step. I’m new to Python and Pandas library and while looking up different functions the explanations can be a little bit overwhelming. You made this noobie prove! Keep up the good work and much appreciated!

@misraturp Год назад

This is awesome to hear, you're welcome!

@harishpoalampalli9637 Год назад

Hey Turp !! great explanantion !! Is it possibe to provide the data sets !! Thanks

@blackpenny9628 Год назад

great...concise and straight

@SESHUNITR 2 года назад

loved it Misra. clear explanation and a quick reference if we forget.

@misraturp Год назад

Great to hear!

@ArunKumar-sc9dl 2 года назад

Thank you, very simple explanation.

@misraturp 2 года назад

You're welcome!

@ahmedalhomeidy Год назад

clear explanation and precise and on to the point, I love it

@misraturp Год назад

Thank you!

@loordgo8772 Год назад

thanx for the video. what about Merge Conflict? can be detected using Pandas?

@kennethstephani692 Год назад

Great video!!

@misraturp Год назад

Thanks!

@khemrajpatil5683 2 года назад

Thanks for the vide!. It gives me clarity.

@misraturp 2 года назад

You're welcome!

@tusharwarade4603 10 месяцев назад

plz add datasets used in this video😊😊

@avirajankitjain256 Год назад

Hi , where is the data set?

@batyratayev2230 10 месяцев назад

Thanks @misraturp!

@ishanseth4442 7 месяцев назад

Thanks a lot

@domillima Год назад

When you merge left_on='ID', right_on='ID2'.. two columns of different names with the same IDs, is there a way to drop one of these, other than adding .dop(col_name) at the end? thanks

@ahamedsuhails Год назад

Thank you

@anurajms 9 месяцев назад

thank you

@ashwinr1407 Год назад

clear and informative ! thanks.

@misraturp Год назад

You're very welcome

@mariaclaraceballos3488 2 года назад

thanks for the explanation! what happens if we use the function concat with 2 dataframes that have repeated data, i mean an ID that is in both dataframes?

@vaibhavk2430 2 года назад

In streamlit can you implement direction feature like we have in google maps i.e. we choose our starting point and ending point and and there is a direction showing the way

@misraturp 2 года назад

I don't think so but then again I never tried doing that.

@86Maryj Год назад

Hi can you please help to do pivot with multiple sheets

@nicknicknick7860 2 года назад

Nailed the explanation, thank youu!

@misraturp 2 года назад

You're welcome :)

@GregThatcher 3 месяца назад

Thanks!

@misraturp 3 месяца назад

Thank you!

@AmitMishra-xd7yo 2 года назад

Thanks! It's pretty useful!

@misraturp 2 года назад

Great to hear!

@abinetayele7901 2 года назад

Perfect video.

@misraturp 2 года назад

Glad you think so!

@bryan-9742 Год назад

I never got sent any of the cheat sheets. Are you sure that links is still functioning?

@misraturp Год назад

Hey Bryan, it should still be working. Could you check your spam folder. I see that someone with the name Bryan submitted the form but never confirmed their email. (Don't want to share the last name here but that could be you). Either way, if you cannot find the mail in your spam folder, you can get it here too: misraturp.gumroad.com/l/pandascs