My top 25 pandas tricks

[@dataschool]

THANKS for watching! 🙌 Which trick are you most excited to start using? CLICK REPLY and let me know!

[@TarmoSillajoeGoogle]

Thanks. Trick nr 9- building a dataframe from multiple files is the one i've been searching for. Comment to trick nr. 3. Sometimes modifying column names works by using Python's list comprehension. Say we want to capitalize all column names. Just write: df.columns = [my_col.capitalize() for my_col in df.columns]

[@dataschool]

Glad you like trick 9, that is one of my favorites! As for capitalizing column names, a list comprehension works, but a string method is even simpler: df.columns = df.columns.str.capitalize()

[@juanbetancourt5106]

Thanks, those tricks are really amazing, I wonder if I can take this magic to the web, is it a good choice to combine pandas power with django?

[@mritunjaykumar970]

The last trick will significantly reduce the amount of work we do understand the data through eda.that trick was amazing.thanks kevin

[@sreenivas7739]

Thanks for a great video. Bonus trick is the most useful.

[@zackhicks2433]

Video should be called 'Magic with Pandas'. Thanks for this really useful resource!

[@dataschool]

Thank you! 🙏

[@Alok_Mandal]

you just saved my life, i was collecting these things over google wasted my good time but now i know where to look for. keep sharing , God bless you. Thanks

[@dataschool]

You are welcome! 😄

[@thomasmendy9802]

Kevin Markham, you by far one of the best Data Science Instructor, I came across. Thank you for providing us with such high standard content at no cost.

[@dataschool]

Thank you so much! 🙏

[@leonardoalvarado7632]

Thank you for all these tricks.

[@dataschool]

You're welcome!

[@valeriemolignano8127]

Kevin, you are a fantastic instructor. I'll sign up for anything you offer. My 2 favorites: clipboards, and, what made my mouth drop - the dataframe profiling.

[@dataschool]

Thank you so much for your kind words Valerie! I have a lot of resources that might interest you here: www.dataschool.io/start/ And here is my email newsletter: www.dataschool.io/subscribe/ Thanks again!

[@giangtu6000]

I love you! KEVIN!

[@Goodhealthall2015]

I had some trouble with my dataframe. So I was stumbling over the internet to find solution,and your video came. Although I didn't find solution in your video, but one of the trick gave me a logical idea of how to resolve the issue. It told me where I was wrong. And as far as tricks are concerned, they are amazing. Some went over my head but that's okay. This whole panda python thing is new to me. I'd prefer to bite slow instead of gulping down entire meal in one go

[@dataschool]

Thanks for your kind words, and glad I could be helpful!

[@kishlayamourya3141]

Best pandas video ever!

[@dataschool]

Thank you! 🙌

[@rvg296]

No other trick mentioned in the video is comparable to the Bonus Trick (Profiling).. This is simply outstanding !!!!

[@dataschool]

Thanks!

[@sanjaykrish8719]

Wow... Veryyyy cool tricks. Saves a ton of time.

[@dataschool]

Thanks Sanjay! 🙌

[@satty22]

The long awited video is out now. Thank you so much mate. Great learning with you.

[@dataschool]

You're very welcome!

[@naqeeb16]

It is one of the best videos on Pandas. I really love some of the tricks e.g., the Clipboard', and 'The Excel copy & paste ones.

[@dataschool]

Glad it was helpful! Thanks for your kind words!

[@kwanpakshing]

Very helpful and useful tricks for day to day Data operations

[@dataschool]

Thank you!

[@jagggyjazz8010]

I liked it to see someone who puts their cam much above their face level baing successful on YT

[@vishalwaghmare3130]

Super duper useful video. Amazing!!

[@dataschool]

Thank you!

[@homeuse8879]

Awesome pandas tricks!!! Thanks for this great resource

[@dataschool]

You're very welcome!

[@yashagrawal8352]

25 and Bonus tips are the best.

[@dataschool]

I like those ones as well!

[@sushedbubai]

All the tricks were mind blowing. But the bonus one was out of the world. It is surely going to help those who struggles Exploratory Data Analysis. Many thanks for sharing this.

[@dataschool]

Awesome! So glad it was helpful to you! 🙌

[@minglee5164]

The bonus trick is so amazing

[@dataschool]

Thank you!

[@jasonwong8315]

it is amazing because every time I watch this video i can learn sth new! thank u!

[@dataschool]

That's awesome to hear!

[@kamleshgangaramani9445]

all tricks superb, continue good work🎉

[@dataschool]

Thank you so much 😀

[@NitinSawant1988]

This video was awesome.. Very Brief, to the point. It will be very easy to revise the concept/code by just revisiting them.. Thanks a lot Sir.....

[@dataschool]

You're very welcome!

[@mikekramer7737]

Tnx. The .style.format(dict) is a game changer. I used to convert my parameters to ensure a fixed number of parameters would show up well, i.e convert a fraction to a percentage. Not sure why this had never been mentioned in the many videos I have watched before.

[@dataschool]

You're very welcome!

[@vlinkin22]

Very helpful, Thanks !

[@dataschool]

You're welcome!

[@yahyahamid5762]

Thank you for the video, really useful stuff!

[@dataschool]

Glad it was helpful!

[@siddhartha8886]

Thank you, for giving me shout out, and thank you for including my trick in your video (pd.profiling) :)

[@AZ993k]

Amazing! Thank you!

[@dataschool]

You're welcome!

[@kislaylove]

Last Bonus tip, Best in 2020 till date. Thank you so much. You have made my life easy!!!

[@dataschool]

Thank you!

[@gregf9160]

Excited to try ALL of these! Thanks!

[@dataschool]

You're welcome!

[@ScottLinne]

Great video. The bonus tip is very useful.

[@dataschool]

Thanks!

[@balasubramani2126]

this video is awesome.Maybe knowingly or unknowingly i worked with the following tricks. trick_no={2,6,13,15,17,18} and the remaining tricks are new to me.thanks for the video.i will practice the remaining tricks in upcoming projects

[@dataschool]

Sounds good! Thanks for your kind words!

[@OmarAbdelaziz__47]

Thank you Kevin, You are really a good instructor. Also, I really loved how you shout out people your learnt tricks from, that's very awesome!

[@dataschool]

Thank you!

[@vadivelan4228]

Thanks for this consolidated and a very crisp video on Pandas....

[@dataschool]

You're welcome!

[@Asparuh.Emilov]

This is one of the most useful coolest videos about Pandas I have ever watched. Thank you sooooo much for compiling all these tips and tricks! Absolutely amazing!!!!!!

[@dataschool]

You're very welcome! 🙌

[@asn6543]

Thanks you sir, your tutorials are very clear and very easy to learn even for none english speaker. Lots of thanks

[@dataschool]

Glad to hear that!

[@maxxpool]

I'm so glad I chose to click on this video. Thank you for this amazing video!

[@dataschool]

You're so welcome!

[@MadLadsAnonymous]

Wow, that last tip! What a phenomenal overview and diagnostic tool. I've learned so much from your videos. So grateful for your content.

[@dataschool]

Thanks very much for your kind words!

[@92soyeon]

Fantastic! It really helped me escaping from a lot of itchy situations!

[@dataschool]

Great to hear!

[@erickcampos50]

Useful is the word! Thank you

[@dataschool]

You're welcome!

[@hectoralvarorojas1918]

Well done Kevin! Thanks for sharing this great material. My best regards!

[@dataschool]

You're very welcome, Hector!

[@christopherteoh3094]

The bonus content totally blew my mind off! Thank you very much Kevin! You're simply the best! Looking forward to purchase your ML series!

[@dataschool]

Thank you so much for your kind words!

[@tunkyi7162]

It helps me a lot in Data Wrangling. I really love your videos. Keep doing!

[@dataschool]

Great to hear!

[@irfankhuddus1974]

Superb ! Excellent ! introduction for Beginner (myself) to get introduced and master these Pandas at the same time thereby saving me a lot of time. Thank you so much Kevin !!! You Rock !!!

[@dataschool]

That's great to hear! Thanks for watching 👍

[@lukeelliott5921]

Read clipboard is the coolest thing I've ever seen.

[@dataschool]

Right!?! 😎

[@pradeepgb986]

Kevin, you are simply amazing. Thanks for sharing these wonderful tricks!

[@dataschool]

Glad you like them!

[@winyourself553]

These are really great tricks.

[@laychansethaaerd]

You are amazing!!!

[@maxvinella941]

This is a jewel video! All tricks left me without words! thanks

[@dataschool]

You're very welcome! 💎

[@d63810728]

I *heart* pandas-profiling, thanks man!

[@dataschool]

You're welcome!

[@manojl3388]

Hi Kevin, Thank you very much for sharing your knowledge to the world :) The most fav trick I loved is, its your video editing (the highlighting of cells while you were explaining). Now its hard to play in 2x speed :) But you have condensed so much information in a very short video. Thank you!! Also finally, the way you thanked everyone.. taught me how to be humble and acknowledge others effort. So your videos are more than just pandas videos.

[@dataschool]

Thanks Manoj for your really thoughtful comment! I wouldn't be anywhere without the amazing pandas resources and tips provided by others, so I definitely wanted to acknowledge them. And I'm glad you liked the highlighting! Credit for that goes to my excellent video editor 🙌

[@anastasiiag8518]

This is incredibly useful! And explained perfectly! Thank you! It would be awsome to see from you some content on advanced plotting, data plotting tricks :)

[@amandal8170]

Agree, if we can see the plotting ticks will be fan jolly tastic. :p

[@dataschool]

You're very welcome, and thanks for your suggestions!

[@VickysStories]

Thank you very much for such a fantastic video :)

[@dataschool]

Glad you liked it!

[@bevansmith5202]

Number 11, read from clipboard is great!

[@dataschool]

Glad you like that one!

[@arturofregosov]

Great!! I do not know why isn´t everybody studying python!

[@adamyork8407]

Thanks Kevin! I actually put tip #23 into use immediately after watching.

[@dataschool]

Awesome! Glad you are putting it into use Adam! 🙌

[@hdsheena]

Read clipboard. Holy crap. I need to go try this right now. This may well change my life

[@dataschool]

Ha! 😆

[@CJP3]

Pandas Profiling! I'm so excited to use it!

[@dataschool]

Nice! Let me know how it goes 🙌

[@franklinwanderson4316]

The best! Thanks so much!

[@dataschool]

You're welcome!

[@sarahmacdonald1342]

Awesome video! Thanks for reminding me of the transform function to combine aggregates back onto a df. Also, the df profiling is a great idea that I've never heard of.

[@dataschool]

Thank you!

[@dew_reddit]

Wow the last one was fantastic. styling the dataframe was also pretty neat. Thanks for this 👍

[@dataschool]

You're very welcome!

[@sachavanweeren9578]

I was revisiting dataschool video's. In my view these are still one of the best resources out there. Thanks a lot ...

[@dataschool]

Thank you!

[@neesargmistry2071]

I hardly ever comment on any videos but I had to for this one. You're amazing, keep up the good work :)

[@dataschool]

You are too kind! :)

[@pldeepesh]

Fantastic! Been using pandas since a year now, You have opened new possibilities for me to keep looking and learning.!! Please keep doing the great work!

[@dataschool]

Thank you!

[@meghasyam427]

Holy Moly What a master piece this is. I liked the clipboard trick a lot man like that literally saves a lot of code and time. And the bonus blew me off. It looks literally like a final report LOL. Can't wait to implement these tricks in my analytics work. Thanks a lot Data School

[@dataschool]

You're very welcome! Thanks for your kind words!

[@AryanSingh-jf8tc]

it's actually quite helpful, thx a lot

[@dataschool]

Great to hear!

[@jianbingding4087]

Thank you, it's very useful!!!! I have subscribed your video, thank you for your summary.

[@dataschool]

You're welcome!

[@jongcheulkim7284]

Thank you so much. This is very helpful.

[@dataschool]

Great to hear!

[@riessm]

First time ever I honestly wish I could upvote this more than once! Great tips, great explanation! One short addition to trick 19: I enjoyed getting to know the transform method, but as most of the times in pandas, there is another way with (for me at least) more often used functions: Just take the aggregated data-frame and merge it with the old one (left merge) instead of concatenating. I don't know if there are any runtime benefits of any of these methods, but to me it's one less command to remember - even though now I will look into uses of the transform method! :-)

[@dataschool]

Thank you so much! 🙏 As for trick 19, you are totally right that merge could accomplish the same thing. I like the transform code much better, but I also encourage people to learn fewer functions overall, so there's nothing wrong with just using merge! Anyway, thanks again for your kind words 😊

[@saeedrehman5085]

Pandas profiling is a new thing for me. It is good to learn new thing everyday. Subbed !!

[@dataschool]

Thanks!

[@narendraprasath5745]

It is really nice and very useful to many people. Special thanks for your effort to post this.

[@dataschool]

Thanks for your kind words! 😄

[@shreddersengupta7384]

This is great !!!

[@dataschool]

Thanks!

[@kasiasama7322]

Great job Kevin. Learned a lot.

[@dataschool]

Thanks! Great to hear 👍

[@ASURAN24]

Favorite is definitely the profiling

[@dataschool]

Cool!

[@kalekalekale]

Excellent video, thank you for cutting to the chase.

[@dataschool]

Thanks! This video took a very, very long time to create 😄

[@kishoreyarramshetty2930]

Nice video on pandas.. great help to me. Thanks

[@dataschool]

Great to hear!

[@user-cc8kb]

Thanks a lot. This is super useful! I'll try to use as many of these tricks as I can whenever I can :D

[@dataschool]

Great to hear!

[@DiegoTerzano]

Fantastic tips, thank you!! Super valuable and with clear, practical examples. Once again, thank you!

[@dataschool]

Thank you so much! 🙏

[@daniel76900]

saved my life!! Thanks!

[@dataschool]

That's awesome to hear! 🙌

[@rahulkoley9447]

Thank You For making US Advanced

[@dataschool]

You're welcome!

[@eddysan7k]

what the awesome tricks!! thank you!!

[@dataschool]

You're very welcome!

[@site-activator5411]

Very cool! Thank you!

[@dataschool]

You're welcome!

[@michaelnovik270]

AAAAaaaaa sweet tips! Thank you so much!

[@dataschool]

You're very welcome!

[@BVaibhav-mt8jx]

Pure GOLD!

[@dataschool]

Thanks!

[@ravisoni1386]

Thanks a lot for these tips❤

[@dataschool]

My pleasure!

[@renatosabinobr]

Excellent content!!!

[@dataschool]

Much appreciated!

[@gisleberge4363]

Great collect ion for beginners as well as those who has been in the game for a while 🙂👍

[@dataschool]

Thanks!

[@archowdhury007]

Amazing tips!!!......keep sharing more such videos

[@dataschool]

Glad you like them! 😄

This list of tricks is very usefull to know.

[@dataschool]

Glad it's helpful to you!

[@markjudeestrera]

sweet!, very handy! Thank a lot Kevin!

[@dataschool]

You're very welcome!

[@davidyoo647]

thank you this is amazing. will be saving this for future reference!

[@dataschool]

Awesome! Glad it was helpful to you 👍

[@ForTheWin2007]

Great video but I won't be able to forget Kevin's eyes that starred into my soul xD

[@dataschool]

😜

[@robertodilisio7535]

Brilliant as usual! From beginning to end! The bonus was also mind blowing :)

[@dataschool]

Thank you so much, Roberto!

[@snehashinde21]

This was amazing video to sum up basic Pandas usage. Thanks for this useful resources!

[@dataschool]

Thank you for the kind comment!

[@stephenpatti2375]

Great Pandas resource! Difficult to say which trick most 'excites' me, but will go with using transform to add aggregation functions to the data frame. Thanks!!!

[@dataschool]

I like that trick as well... I only learned about it recently!

[@jacquesgouimenou9668]

Thanks for sharing this work.

[@dataschool]

You're welcome!

[@mateuszguszkowski8214]

Totally awesome!!! Thanks!!!

[@dataschool]

You're very welcome!

[@galymzhankenesbekov2924]

thank you so much for your effort and these videos!

[@dataschool]

You're very welcome!

[@global4069]

5***** Rated -like the bonus trick , 23& 14 as welll

[@dataschool]

Thanks!

[@barrjohnm]

Awesome video!

[@dataschool]

Thank you!

[@pkmisra769]

Thanks man. Really useful !!

[@dataschool]

Glad it helped!

[@pkmisra769]

@@dataschool Thanks KEVIN. All your videos have been very useful. I have a request. It would be really great if you could make some videos on deriving columns from unstructured data using Jupyter Notebook. For example: there are columns in a data set. But, in one of the column, there are string characters which ideally should have been a part of other columns, but, due to data issues, they appear as very long string with several random delimiters within it.

[@pkmisra769]

@@dataschool I have another doubt. How do I derive either date separately or time separately directly from a time stamp field. (example below):2021-02-01 04:53:59.187194+00:00

[@pkmisra769]

Need your help on this.