Don't do THIS Pandas mistake!

𝗗𝗘𝗦𝗖𝗥𝗜𝗣𝗧𝗜𝗢𝗡
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In this video, I'm going to show you the pandas mistake that many people make when using groupby and how you can avoid it.

🌍 𝗟𝗜𝗡𝗞𝗦:

𝗧𝗢𝗢𝗟𝗦 𝗔𝗡𝗗 𝗥𝗘𝗦𝗢𝗨𝗥𝗖𝗘𝗦
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𝗖𝗢𝗡𝗡𝗘𝗖𝗧 𝗪𝗜𝗧𝗛 𝗠𝗘
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☕ 𝗕𝘂𝘆 𝗺𝗲 𝗮 𝗰𝗼𝗳𝗳𝗲𝗲?
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[jonathanlegendre]

The last trick on calculating how much of the data is missing in percentage terms was neat. I have been tripped up by this before and I did the long fix of actually correcting the source data to no longer have the NaN so it would group properly. This is definitely a nice trick to quickly get the totals and then you can worry about if the source data needs correcting.

[carlos-ferreira]

Great video.
Took me a while to discover why my group by were out putting the wrong values.

[bc]

Oh my, these are some tasty tips!
I just found this months later - sorry i missed it, but glad to have it now 😊

[sandrakyoutube]

I am so happy 🤩that I found this channel! Another short, to the point and very helpful video. Loved the easy percentage calculation! Danke you very much. 😃

[michalbotor]

oh, yes, indeed it was helpful. thx!

[tayfundogruer]

dafaq. I just terrified that didnt know

[shrey]

Ohh nice... After that tutorial I'm always going to use dropna = False.

[michocha]

hello
your videos are really good thank you very much
please is there any method to email sms to any number in the world for free

[CameLinis]

Totally true, i’ve faced this issue with pivot tables, thus i used df.fillna at the beginning of the analysis, bro you have really inspired me to learn py..pandas from scratch! Ty!