I am a decent Excel user who has been so reluctant to learn any programming language. Your video changed my mind and after few hours of watching this video, I feel I can learn the basics of python in a short period of time. Your teaching style is amazing and your ability to explain things is fascinating. Thank you so much.
Ikii ma iikiii lkkiiki Li mn ik lol kki kkilliikkkikiki ki ki likii Kim kikikikiiikiikilikikikkilikiliiikkikile likikikkkikikkikikikikikikiiki mom ikililikililiikilikililikiikilikilkiliikiikikiii Ii ikkkiikii Kikikiliki iikikiki kikikikikikikikikikkikikikkililikilikiiikillikikil mom ilikilikikilikikililiikilikkliikikikikiikiikikiki ikikikkiliiklikiliiikikikikiikilikilikikikiklilikikikiklilikikikililikilikikilikii Ikkikikiikilikilikikikikikikkilikkikikikli lk kii mll illikikkiikkikikilikiilii Liikikiki kill ili ikikikilikiliik kiikikikik Kim ikilikili Kikilkiki Ilikikikkiiikikkikilikikiliikikilikikkikilikikii kim iiilikkikililiiiklili kiliiikilikikikiikikikilikilikikilkiliiikklikikikiklikkiiikikililii Ikilikikikiliilikikikilikikilikikikilikiliii mom ikikiikilikiikilikikilikikikikikkikikikiliikikili kikilkiikikikikililikilikilikiikikkikikikikiki likikikilliikikkikikikilikiikiikikki mom iliikilililikikikiii Kiikikiikiikiiik mom i mll kikikikilikiki I Iikiki Mmmmmm kikkikiikiikii Ilikikikikikilikililkilikiikikiiiikki lk ikikikilikikiikikilikiiki m ikiklikimiikiikikikiikil Iikikikikiikikikikiikiliikiiilikiliiilikiikikikiikikikikikiikiliikiikikikikilikikikkililikiiikikkilikikilikikikikililikiliikililiiikikikikiikikkikikililikikikikilikilikilikikikkikiikikiklikilikikkilikiikikikiiiliikiliiikiiliikikililiilikikiikkikikikikiikikkikilikikkilikikikikiikliikilikikiiliikikikilikikiikikilikikiiiikikkikikikiiilikikiliikiiikilikikikiiilikkikiiilikikiikiiikkilikiikilikikikilikiikikikikilikikiliikikilikiklikikikiimikilikikililiikiikikikii Ikikikikikiikiiikikilikikikikiklikikikikikilkilikikikikilikiikikikikiikilikikikilikiiikikikililikikikikiukikikikimikkikikikilikikiilikililikiliikikikiliimilimilkilikiikikikikikikikiklikikkikikikikikilikililikikikikililikikiikkikikilikikiikikikikililiikikikilikikililiiikilikikikilikikilikililikikikikililikikikilikiikikilikikiikikikiliikiikikilikikilililikikiikiikikikikiiiliikikiikikikikikikiikilikikilikikikikiikikikiliiikikikilikikilikikikikilikikiikikikikilikilikikilillilikilikikikikiliiilikikilikilikilikilikiikikikikiiliiikiikilililiikiikiilikikikikikikikiliilikikikikilililikilikiliikikikilikikiiklililiikikiimikilikiikilikiikikikikikikikililikikiikiikikiikiliikiliikikililimikikiikikiliikilikiikilililililiikikikiikikilikikililililikikikiiikilikiikilikiikikiliiiiikilikilililililimilikiikiikiliikikiikiikikiiikililililililikiikiikikiikikiiikikiikilikiiikiikilikikikiikilililimiikimilikiikikilikikiliikikilikilikiiiikikililikililiikiliikiiiikililiiikiikikilikikiikikiiiiikilimiliimililikikikimilililikikiliikikikililiikililiikikikililikililililiikikikililikikiikikiilikililiiilililiiikikilikiikiliiikiikikikiikiikiikililikiiilikikimimiliikikikiikiikiikiiikikikiliikilikiliiiikikilikiiiiiiiiimiliiiliiikiiikikiliiiiiiikikiikimiliikiiikiliikikiiiiiikiikikikikiikiiiiiiiiiikiiiiiiikikiikikimkiilikilikiiiikiikiimiikiikikiiiiiilikikiiiiiiiikilikiiiikiiiikikiikiiikiikiiiimiiikikiimiiiiiiiikiiiiiii lk ik LLLLL lk iliii m iliimimi mmmmmmm ili m i LLLLLLL imimiiikikiki mll ii m mlk i LLLLLLLL mikii m imii kmi ikiii LLLLLLL ikiki lk i ii LLLLLLL i mi lk imiliiki LLLLLLLL i LLLLLLLL ili lk ilii lk i LLLLLLLL i lk imi LLLLLL iiilimi lk i mll ii LLLL mmmm ii lk m i lk iliimimikmiiikiikiimiikmimiikkiikiiliimimiiiikiiimi LLLLLLLL iiii m iiiiliiiii LLLLLLLL ii m i LLLLLLLL ii iumii mom ilii lk iikiiiiki iimi lk ii mmmmmm imiimiimiimiliiiimiimiii milk liiiiliiii imki ji iikiikiliimiliiiliik Kiiliikiiikiiiiiimiikii iililiimiiii lk iiii I’m iii LLLLLLLL imiiiiiii LLLLLLLL iliiikiikii LLLL ii miki mmmm l ol l pop oooooooooooooo o op ploll i mik😮😮i ii la😮 is lk l u ki iim😮😮 l LiIm mi😮 mi u li u ii u iki i have i ii I kam i😮iiiikik imik la 😮😮 i have u i ui ki I lk i iimi 😮 iiikm Ui Kiil 😮iui m u mu m😮kuuikmk mk kimmimm im mk kk mk kmmlimkmmmk uk mkmkk kkkmmmkk m lmm mmmk mm mkmk kkklkkmkmu kkkmkkkmmm k k kmkkmm kkmkmmkmkkm mm mmkkmkmmoooooooooooooiooool😊poooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooiouyioooooooooooooooplo😊o😊lol😊popgb gbgg bg g g. gbg bg. g gbg gb gg b gbg ng g bg
Every time i open TH-cam it goes right to this video and forces me to reread every single comment, no matter what I do or how i try to stop it 😭😭 god help us all.
That's the best content I've seen on jupyter and pandas so far! well done champ! I've spent my whole weekend going along on this course and I totally love it! Very well structured and full of examples you can run and you can test out on your own. had a minor set back on opening the csv file dgp but added the encoding parameter: df_gdp = pd.read_csv("gdp.csv" , encoding="latin-1")
BEST PYTHON COURSE i EVER SEEN. i LITERALLY ENJOYED AND SPEND MY WEEKEND CONSUMING THESE CONTENT WITH PLEASURE. THANK YOU FOR YOUR MASSIVE SUPPORT FRANK
I just finished this python course and I have to say it was so fascinating to learn about this language. Frank did a great job at breaking everything down !!
@@focus1007 for an entry level actually a combination of sql+excel only is fine, but as you level up you'll eventually need Python/R. I was like that too at first.
@@rafimaulana8294 thankyou so much fr replying🙏...sir so acc to you ,can i start applying for data analyst with the knowledge of excel and SQL only? Or should i learn anything else also?
@@focus1007 Yes, but try learning any data viz either google data studio/tableau/power BI. This would make an extra bonus point and quite easy to learn.
Best Tutorial on Python for Data Analytics I have seen so far... Your approach is commendable. Well done! I need to see more of your contents. This is good stuff!
Best INSTRUCTOR with the best English accent that we can easily understand and you never miss any step for running Python, even though I'm a beginner but now I know How to use python because of this video 😍, some tutorial they skip some step and even we try to follow their instructions but we got lost 😊😊😊Thank you Instructor ❤
When I saw the title when it was posted, I genuinely lost everything like my world had “imploded.” Words of wisdom by Arun. 😎 PS- I think I started watching the channel in 2022, and before that, I thought of tech as just an object/screen that we use. It made me change the way I think of technology. 🎮
Simply the best!. I was stuck on "Hello World!!!" Your method of teaching really elevates the experience of learning. I love the little reminders you throw in along the way. This course will be my "Go To" as I progress on my Python Journey. Thank you.
Thanks team, for working out for us, I had zero knowledge when I had started but you have cleared very basic aspects for the first steps of learning, Highly recommended content thoese who wants to start from zero.
Thank you for taking the time to create this course and sharing your knowledge with others. Just some constructive criticism here, based on my experience using Excel for many years. In my opinion people looking to move to pandas from Excel are serious users of this package. I didn't find content here that will make me think I really need to move away from Excel to gain this capability. Also Excel's PowerQuery has a lot of powerful transformation capabilities. Instead of doing the visualizations, people may have benefitted more from examples covering merge, groupby, stack, unstack, melt, resampling and even how list comprehensions can be used to add columns based on conditions.
Hi Frank! Many thanks for creating this wonderful course. You have taken humungous efforts for creating such a long and flawless content for everyone to learn. Highly commendable efforts!!
Extraordinary content, crystal clear explanation. Pure gold. We should be able to like the video a couple of times. Thanks a ton for such an wonderful content.
In the section on reading a csv file to create a Dataframe, the syntax used by you, i.e df_exams = pd.read_csv('file_name.csv') doesn't execute as the file local directory is gonna be whole different as when tried in different PC local systems. Instead we can try using df_exams = pd.read_csv(r"file_name.csv") This syntax works perfectly.
The course is really good but has a few caveats: 1. The Dataframe CSV for the short .pivot() method demonstration is not included. 2. The file gdp.csv is in Windows-1252 encoding in the zip file. This cannot be imported into a Dataframe without prior recoding into UTF-8. 3. The .pivot_table() example throws a FutureWarning. I had to list all features in values=['Quantity', 'Rating',...] to make it working. The problem comes from the attempt to sum non-numerical values. So only include columns with numerical values in values=[ ].
Thank you! I had the same problems and I was so lost on trying to figure out what to do with the pivot_table() method's problem till I saw your comment. Helped me a lot!
I didn't understand the use of the lambda function in the ordering section (3:09:40), as you are trying to lower() the values but none of those are becoming lower. Could you explain deeper what failed there?
![Vue.js Course for Beginners [2021 Tutorial]](http://i.ytimg.com/vi/FXpIoQ_rT_c/mqdefault.jpg)
50% are people complimenting the guy for this great useful python video
50% have no idea how they end up here
Coming fast eait
8u🎉
True
Fell asleep listening to a random video, woke up 7 hours later to this
Me too 😂😂
Me too, mate. I wondered why I was having coding related nightmares. Really brought back the trauma from high school.
I fell asleep at night watching some TH-camr, and woke up in the morning only to realize I had watched three 3-hour videos.
You are not alone brother 😅
I am a decent Excel user who has been so reluctant to learn any programming language. Your video changed my mind and after few hours of watching this video, I feel I can learn the basics of python in a short period of time. Your teaching style is amazing and your ability to explain things is fascinating. Thank you so much.
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Every single morning i wake up to this.. no matter what i watch or do😭
Every time i open TH-cam it goes right to this video and forces me to reread every single comment, no matter what I do or how i try to stop it 😭😭 god help us all.
I slept watching "How time works in space" but end up with this
i was watching a reaction vid, dk how i ended up here
I slept watching a Veritasium video on what is time
Same here, some guy in my dream kept talking about jupyter notebooks....
That is one gorgeous cheat sheet. Thanks for everything you're doing for the global developer community, Frank. This course is gold.
Can you please share the link for the cheat sheet?
@@levarish it's in the video description
@@levarishbb😅
Good morning everyone
i just woke up
Same bruh
Me too
Same lol
Same
same
Why didn’t wake up in the middle of the night with this on
Lol same
That's the best content I've seen on jupyter and pandas so far! well done champ! I've spent my whole weekend going along on this course and I totally love it! Very well structured and full of examples you can run and you can test out on your own. had a minor set back on opening the csv file dgp but added the encoding parameter: df_gdp = pd.read_csv("gdp.csv" , encoding="latin-1")
Thanks! Was stumped there :)
thanks man
BEST PYTHON COURSE i EVER SEEN. i LITERALLY ENJOYED AND SPEND MY WEEKEND CONSUMING THESE CONTENT WITH PLEASURE. THANK YOU FOR YOUR MASSIVE SUPPORT FRANK
I just finished this python course and I have to say it was so fascinating to learn about this language. Frank did a great job at breaking everything down !!
The presentation is engaging and makes it easy to follow the instructions.
Definitely the best Python course for a data analyst who wants to level up from sql and excel only!!! Would recommend it!
Sir currently I am working in excel only..will this course help me in getting job? I mean is it sufficient to land a job as data analyst? Pls guide🙏
@@focus1007 for an entry level actually a combination of sql+excel only is fine, but as you level up you'll eventually need Python/R. I was like that too at first.
@@rafimaulana8294 thankyou so much fr replying🙏...sir so acc to you ,can i start applying for data analyst with the knowledge of excel and SQL only? Or should i learn anything else also?
@@focus1007 Yes, but try learning any data viz either google data studio/tableau/power BI. This would make an extra bonus point and quite easy to learn.
@@rafimaulana8294 thankyou so much sir for replying..means a lot to me🙏
as a junior data analyst i found this video very useful keep going my friend!!!
A very good begginer's course; it covers the basics of Python with Juipter Notebook IDE in a simple and understable way.
Best Tutorial on Python for Data Analytics I have seen so far... Your approach is commendable. Well done! I need to see more of your contents. This is good stuff!
Frank went all out with this course. perfect beginner course. hope we all make you proud
Best INSTRUCTOR with the best English accent that we can easily understand and you never miss any step for running Python, even though I'm a beginner but now I know How to use python because of this video 😍, some tutorial they skip some step and even we try to follow their instructions but we got lost 😊😊😊Thank you Instructor ❤
Just finished this video. It is my first introduction to python and you did an excellent job. I appreciate this thanks
When I saw the title when it was posted, I genuinely lost everything like my world had “imploded.” Words of wisdom by Arun. 😎
PS- I think I started watching the channel in 2022, and before that, I thought of tech as just an object/screen that we use. It made me change the way I think of technology. 🎮
I already know Frank for writing exceptional technical articles! Good to see you here too 😁😁
Nice meeting you on TH-cam too! :)
one of the best if not the best tutorial this channel has ever presented. Excellent job!
Simply the best!. I was stuck on "Hello World!!!" Your method of teaching really elevates the experience of learning. I love the little reminders you throw in along the way. This course will be my "Go To" as I progress on my Python Journey. Thank you.
Neolife ❤
This Channel deserves 100M Subscribers Hats Off You Guys👏👏👏
Thanks team, for working out for us, I had zero knowledge when I had started but you have cleared very basic aspects for the first steps of learning, Highly recommended content thoese who wants to start from zero.
I been listening this video for 3rd time and just started practicing by myself.Feelings smart and creative ❤
I still didn't finish the full course but I already find it very useful and well explained. Thank you Frank!
have you finished it by now?
@@boknows8263 Not yet
@@gorke6565 he will never finish it, he is watching TV now lol
Watched it during Chrismas Holiday. Enjoyed it and learned something new. Thank you!
Thank you for taking the time to create this course and sharing your knowledge with others.
Just some constructive criticism here, based on my experience using Excel for many years.
In my opinion people looking to move to pandas from Excel are serious users of this package. I didn't find content here that will make me think I really need to move away from Excel to gain this capability.
Also Excel's PowerQuery has a lot of powerful transformation capabilities.
Instead of doing the visualizations, people may have benefitted more from examples covering merge, groupby, stack, unstack, melt, resampling and even how list comprehensions can be used to add columns based on conditions.
My thoughts as well
From Kenya much Appreciated - Asante Sana-
I have just finished this. Love it. So easy to follow and Frank was amazing. best video so far.
Thanks for this tutorial! It would have also been nice to show how to concatenate or merge multiples data frames (inner, left, right join).
Don't know where you watching this from my brother but I wished you all the best in life ❤️❤️
This was a refresher course for me but notwithstanding, I learnt a whole lot.. Well done
You are an excellent teacher but your TH-cam channel has very little content. Can you upload more videos?
@@nriezedichisom1676 Sure! More videos coming soon on my channel
Hi Frank! Many thanks for creating this wonderful course. You have taken humungous efforts for creating such a long and flawless content for everyone to learn. Highly commendable efforts!!
Amazing content Frank.. How effortlessly you explained everything in the most simplistic way
Frank Andrade, thank you for the best, and most helpful tutorial of
this type and this subject that I have ever seen.
3:23:26 df_sales.pivot_table(index="Gender",aggfunc="sum")
TypeError: datetime64 type does not support sum operations
What to do ?
The only thing, that works for me!
df_sales.groupby("Gender").sum(numeric_only=True)
Love it. Thanks a lot, Frank! 🎉
the the f. t
Great course, broken down like ABC. Thanks Frank
Thanks!
Extraordinary content, crystal clear explanation. Pure gold. We should be able to like the video a couple of times. Thanks a ton for such an wonderful content.
Fantastically explained, thank you so much. Clear, easy to understand and shows some good examples.
GENSHIN PREACH
No words can express how great your work is, thank you so much
Brilliant tutorial! You are a very gifted presenter.
Thanks a lot for that course!! For starting with pandas, numpy dataframes perfect for getting basics to built up on them.
Excellent, very well explained. Very nice use of Jupyter notebooks. Many thanks for uploading.
Amazing content Frank.. How effortlessly you explained everything in the most simplistic way.. Thank you
python data analysis is great! I've also used it to systematically clear up my Inbox
Thanks for basic and effective course and plus English sound is perfect 👍
Thank You Very Much, Much Much More❤️, Love From Indonesia
Thank you for share this! I recommend this video for everyone wants to learn some basics of python, numpy and pandas is awesome.
Excellent...
thanks you mr Frank Andrade
Great course! Thank you so much! Spent a half day finishing the course. Very Helpful!
I don’t remember clicking on this when I fell asleep but congrats I watch the whole thing
good job Frank .. really it's very interesting
highly recommended
THANKS FRANK, YOU MADE ME UNDERSTAND PANDAS
This is a very good course for me, help me a lot. Thank you very much.
I love this content it's well structured with lots of examples to make you understand and master it without any problem. 🇿🇲
Did you happen to run into issues making a line graph? I used the provided code in the tutorial but keep getting errors I need matplotlib.
Wonderful tuto. Very well explained !
Very nice course, you are truly blessed
Great video Frank!! regards from Peru
Frank that was excellent work.
I was going to watch another video. But Frank’s voice was nicer to listen to 😂
Thank you very much, this was very informative and explained in detail!
Very easy to follow and understand. Thank you.
Excellent course, simply put!
Fantastic session 💯
God bless you for this project, I learned a lot from it.
My phone died in the middle of the night and now it’s morning and I don’t know how I got here
Real
Enjoyed every last second of it. Great job!
Thank you. It is a fantastic course. ❤
Very clear and concise instructions! Thank you very much!
Thank you Frank, this is so useful
I fell asleep to this, but it came through in my dreams and now I know two new pandas functions. 😂
Guys take this seriously. I am a computer informations major. This 1 video goes over 2 months of material in college
Thank you very much Frank ❤
Great and simple to mind tutorial
Thank you so much. This is what I was looking for!
got "TypeError: datetime64 type does not support sum operations ", @3.24. how to drop columns contains datetime64 type?
Nicely explained and step by step coverage of "whole" topic. ....Thank you Sir.
I’m so glad I’m not the only one who wakes up this these videos, I have literally no interest in this
Estou muito feliz por ter me inscrito e ter acesso a este conteúdo.
Good learning here! The data should however be available for download to easily practice.
💯Exceptionally awesome video clip
Amazing deep learning. Thankyou
falling asleep listening to this hopefully i’ll learn something new by the time i wake up 🙏
In the section on reading a csv file to create a Dataframe, the syntax used by you, i.e
df_exams = pd.read_csv('file_name.csv')
doesn't execute as the file local directory is gonna be whole different as when tried in different PC local systems.
Instead we can try using
df_exams = pd.read_csv(r"file_name.csv")
This syntax works perfectly.
You're right, i also used the second option.
i tried both the medthod, its not working
Do we need to include the path of that csv file?
@@vignesh28kk I copied the path of the file
could someone advise where to download "StudentsPerformance.csv" file used in the course
The course is really good but has a few caveats:
1. The Dataframe CSV for the short .pivot() method demonstration is not included.
2. The file gdp.csv is in Windows-1252 encoding in the zip file. This cannot be imported into a Dataframe without prior recoding into UTF-8.
3. The .pivot_table() example throws a FutureWarning. I had to list all features in values=['Quantity', 'Rating',...] to make it working. The problem comes from the attempt to sum non-numerical values. So only include columns with numerical values in values=[ ].
Thank you! I had the same problems and I was so lost on trying to figure out what to do with the pivot_table() method's problem till I saw your comment. Helped me a lot!
Amazing course big thanks!
Extremely helpful and easy to follow and understand.
very clear and simple explanations , thank you!
Thx for the efforts
But frankly , excel is much faster and everything you did can be done more efficiently in excel.
Thank you for your guidance 😃
Great introduction for everyday use!
Great ❤️
I didn't understand the use of the lambda function in the ordering section (3:09:40), as you are trying to lower() the values but none of those are becoming lower. Could you explain deeper what failed there?
Really Nice and Really Beautiful "Data Analysis with Python for Excel Users " . Stay Connected!😍😍😍🤗🤗🤗
Love it. Thank you so much!