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 UA-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.
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
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. 🎮
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 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 ❤
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.
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.
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.
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.
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.
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!
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.
cheat sheet is no longer available through the link :( any chance you have an alternative download link for that? It looked very helpful! Fantastic video by the way. The pace was perfect for me!
50% are people complimenting the guy for this great useful python video
50% have no idea how they end up here
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....
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 UA-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.
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
i just woke up
Same bruh
Me too
Same lol
Same
same
Every single morning i wake up to this.. no matter what i watch or do😭
Every time i open UA-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.
Good morning everyone
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😅
Why didn’t wake up in the middle of the night with this on
Lol same
as a junior data analyst i found this video very useful keep going my friend!!!
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
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. 🎮
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
A very good begginer's course; it covers the basics of Python with Juipter Notebook IDE in a simple and understable way.
Don't know where you watching this from my brother but I wished you all the best in life ❤️❤️
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!
The presentation is engaging and makes it easy to follow the instructions.
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 ❤
Frank went all out with this course. perfect beginner course. hope we all make you proud
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 !!
I already know Frank for writing exceptional technical articles! Good to see you here too 😁😁
Nice meeting you on UA-cam too! :)
Just finished this video. It is my first introduction to python and you did an excellent job. I appreciate this thanks
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🙏
Guys take this seriously. I am a computer informations major. This 1 video goes over 2 months of material in college
one of the best if not the best tutorial this channel has ever presented. Excellent job!
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 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
@@gorkemoncul6565 he will never finish it, he is watching TV now lol
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👏👏👏
I been listening this video for 3rd time and just started practicing by myself.Feelings smart and creative ❤
I have just finished this. Love it. So easy to follow and Frank was amazing. best video so far.
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!!
I fell asleep to this, but it came through in my dreams and now I know two new pandas functions. 😂
Frank Andrade, thank you for the best, and most helpful tutorial of
this type and this subject that I have ever seen.
From Kenya much Appreciated - Asante Sana-
Thanks for this tutorial! It would have also been nice to show how to concatenate or merge multiples data frames (inner, left, right join).
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.
This was a refresher course for me but notwithstanding, I learnt a whole lot.. Well done
You are an excellent teacher but your UA-cam channel has very little content. Can you upload more videos?
@@nriezedichisom1676 Sure! More videos coming soon on my channel
Amazing content Frank.. How effortlessly you explained everything in the most simplistic way
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
I don’t remember clicking on this when I fell asleep but congrats I watch the whole thing
Fantastically explained, thank you so much. Clear, easy to understand and shows some good examples.
GENSHIN PREACH
Love it. Thanks a lot, Frank! 🎉
the the f. t
Amazing content Frank.. How effortlessly you explained everything in the most simplistic way.. Thank you
Watched it during Chrismas Holiday. Enjoyed it and learned something new. Thank you!
Great course, broken down like ABC. Thanks Frank
Excellent, very well explained. Very nice use of Jupyter notebooks. Many thanks for uploading.
I was going to watch another video. But Frank’s voice was nicer to listen to 😂
Thanks!
No words can express how great your work is, thank you so much
Just woke up did I learn python in my sleep?
Great course! Thank you so much! Spent a half day finishing the course. Very Helpful!
Brilliant tutorial! You are a very gifted presenter.
My phone died in the middle of the night and now it’s morning and I don’t know how I got here
Real
good job Frank .. really it's very interesting
highly recommended
Thanks a lot for that course!! For starting with pandas, numpy dataframes perfect for getting basics to built up on them.
Thank you for share this! I recommend this video for everyone wants to learn some basics of python, numpy and pandas is awesome.
Thanks for basic and effective course and plus English sound is perfect 👍
falling asleep listening to this hopefully i’ll learn something new by the time i wake up 🙏
Thank You Very Much, Much Much More❤️, Love From Indonesia
How do i managed to wake up to this THRICE???
Enjoyed every last second of it. Great job!
Thank you very much, this was very informative and explained in detail!
This is a very good course for me, help me a lot. Thank you very much.
Great video Frank!! regards from Peru
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.
Very clear and concise instructions! Thank you very much!
THANKS FRANK, YOU MADE ME UNDERSTAND PANDAS
Very nice course, you are truly blessed
Thank you so much. This is what I was looking for!
Excellent...
thanks you mr Frank Andrade
I just woke up to this
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!
Frank that was excellent work.
Very easy to follow and understand. Thank you.
Really Nice and Really Beautiful "Data Analysis with Python for Excel Users " . Stay Connected!😍😍😍🤗🤗🤗
Nicely explained and step by step coverage of "whole" topic. ....Thank you Sir.
God bless you for this project, I learned a lot from it.
Excellent course, simply put!
Yo you are god to me. Landed just to help me. Thanks
Thank you Frank, this is so useful
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. It is a fantastic course. ❤
Wonderful tuto. Very well explained !
Your voice makes me want to save America.
Excellent course! Help me to come through. :)
Amazing deep learning. Thankyou
Amazing course big thanks!
💯Exceptionally awesome video clip
Fantastic session 💯
Estou muito feliz por ter me inscrito e ter acesso a este conteúdo.
Thank you very much Frank ❤
Great and simple to mind tutorial
Great introduction for everyday use!
Love it. Thank you so much!
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
Thanks. I am trying to learn at 55😊
cheat sheet is no longer available through the link :( any chance you have an alternative download link for that? It looked very helpful! Fantastic video by the way. The pace was perfect for me!
Extremely helpful and easy to follow and understand.