Hey everybody. I hope everyone's week is starting off well. I'm still working on the next video in the series, so I don't have a specific release date just yet. Just keep your eyes open. I'm hoping to have this entire series finished soon, but I'm not sure how long it will take me to record/edit the remaining video. I'll do my best to get them out ASAP (this week or next). Have a good one!
Hi, have you seen the release of pandas 1.0?pandas.pydata.org/pandas-docs/version/1.0.0/whatsnew/v1.0.0.html Is this going to affect this series in any way? Also thank your for all of your work! You do an incredible job!
@@alanbarzilay6866 It's still a release candidate, so probably not. However, everything here could at some point become obsolete for sure. The documentation on pandas is mostly pretty nice, so I would just look up how to do some specific thing should the "old way" stop working.
@@waynezor Release candidate means that features are probably set, it just needs more testing before they release the stable version. Agree with the rest, but why not include the new things if they are worth noting from now on?
I'm using pandas for a quite long time and sometimes I found it annoying (yet still very useful and mandatory in data science). Your videos make this library crystal clear. Thank you for this!
How Kind Can Someone Be? He explains each and every detail and also explain things repeatedly so that anyone coming any of the video in the middle of the series will find it easy to follow the video.
Pandas is an enormously helpful tool with good documentation, but for those of us who learn best by example there can be a steep learning curve. These tutorials are the best I've seen for clearly and methodically working through the basics.
Chapters: 00:00 Intro 00:30 Recap of Dataset 01:00 Recap of What's an Index 02:06 How to Set DataFrame (Row) Indexes ('df.set_index('col_to_use')') 02:35 'inplace' Argument 03:40 '.index' Attribute 05:13 How to Reset (Row) Indeces ('df.reset_index()') 06:16 Set (Row) Index on DataFrame Creation () and Practice on Real-World Dataset ('pd.read_csv('file.csv', index_col='col_to_use')' 12:58 Sort Indexes (`df.sort_index(ascending=False)`) 15:02 Outro Copied from @Adam Hendry for future reference
I can`t ensure if you will believe me or not when i tell you that i downloaded 130 tutorial video of your content about python, but the most important thing that i am sure about is, you are awesome, keep going believer
I learned Pandas on my own, by hit and trial, but after watching these videos, finally I am able to connect the dots and make some sense why things are like this. Thanks Corey, this will save my time to google every command :)
Thanks a lot Corey.. you are the best instructor out there.. I can't even imagine learning from anybody else. Can you please consider creating a series on pyspark and machine learning??
Can't believe how awesome you are! Really enjoying this series so far your instructions are so thorough and simple, you've really helped me grow so much in my aspirations. Thank you so much Corey, hope all is well in this tough time.
Wow, these videos are seriously so helpful! I've just been getting started with pandas, feeling frustrated because I just don't understand the syntax super well yet and thus having to google literally everything. This is making it so much easier to understand! I can't thank you enough and I'm looking forward to getting through all the videos! :)
Thanks a lot, Corey! It's evident that you put in a lot of effort into making your videos flawless. Where else could I get such clear and thorough explanations !?!
Thanks Corey for this awesome series... You are making complex things looks simple.. What I like the most about your series is that your Tutorial flow by explaining simple to complex in an understandable manner.. Keep this good work, you are bringing in differences in many Techies lives.
7:20 respondent 0: "I am a sttudent learning to code" stack overflow: "are you a student" respondent 0: "no" stack overflow: "what is your education level" respondent 0: "elementary school" stack overflow: *mike wazowski bruh face
Thanks for this series, @Corey! Very helpful and very well done. I went to Brilliant to check them out to thank them for sponsoring your videos! Thanks Brilliant!
1.To reset index after loading csv ; df.reset_index 2 to set index after reading CSV; df.set_index(" ") 3.To reset index in place and permanently change dataframe ; df.reset_index(inplace= True) 4. To set index while reading the data(csv) ; df = pd.read_csv('data/survey_results_public.csv', index_col =" ") 5. To sort your index alphabetically; df.index_sort 5. To sort your index alphabetically in a descending order; df.index_sort(ascending = False)
Watching one video everyday after work! Thanks for the amazing videos. They're easy to follow. I am looking forward to check the other courses as well.
Hey Corey, Your way of teaching is really awesome, Anyone who is beginner can also grab it and take it forward easily. Waiting for your upcoming videos on pandas :-) and looking forward to new series in python like numpy etc. which can help us in data analysis. You are doing a great job.
Great video, thank you! 14:000 I know you covered - pd.set_options('display.max_columns',##) but I can't seem to get the schema dataframe to show that even if I do run that... - nevermind, I figured it out. It was just pd.set_options('display.max_rows',##) and I think you did cover that! Anyway, thanks again Corey!
Yet another lovely lesson. Nice flow with a good combination of motivation and technical instruction. Thanks. Just wondering how common the inplace=True argument is across Python generally, or is it specific to Pandas- first time I've seen it.
Great course with clear explanation, great help to me. Thanks a lot.
4 ปีที่แล้ว +2
Hey Corey. Your tutorials are awesome. It would be great if you produce how to use importlib library and dynamic module importing tutorials in future videos. Thank you very much.
Hey Corey A very good series. Learning from these and applying to Python visuals in Power BI. A bit limited in options there. Would it interest you to make a few videos on handling Python in Power BI? Thanks
Hi teacher, I love the videos, Thanks for taking us through, My data set after loading it in pandas its showing the "NaN" columns that are not there when i open the file direct using excel, what could be the issue?
Can't understand why would anyone dislike such a high quality work?!!! Thank you Corey... one simple question, when using methods (df.set_index()) I get an error on Spyder. 'DataFrame' object has no attribute 'set_index'.... it works if pd.set_index is used instead?
1st comment...didn't watch it...first i like corey's video then i watch it...PS: First i disable my adblock....i urge everyone to do the same. Just out of curiosity...how many videos this pandas series consist of?..thank you for amazing videos..you're the best teacher Corey.
I still haven't finished recording the series yet, so I'm not exactly sure how I'll break up the last videos. But I _think_ it's going to end up being around 10 videos or so. Then I'm going to do another series of 5-10 videos specifically on plotting in Pandas.
Sir Can you please make Videos on ML also. You teach like a teacher is teaching to a 1st class student. I am very curious to study ML lectures by you Sir. Thankyou very much sir .😊😊
Overall good stuff. More thought needs to be given when choosing example data. For rows and columns it's natural to speak of the first or last row -- and even the first or last column.. Using 'first' and 'last' for column names is needlessly ambiguous.
@coreyschafer. (or anyone who can help me) @11:40. I'm running this code on Pycharm while following your video and I'm getting a 'KeyError: 'MgrIdiot' message. The code has worked exactly as it should for any other row I've tried to look up ('Hobbyist', 'Age', etc). Any idea why pycharm would specifically show a KeyError just for the 'MgrIdiot' row? I tried running schema_df = schema_df.astype('str) to change all values to strings, but that didn't help. Thanks!
Thank you Corey for the video. I have a small doubt: pd.set_option('display.max_columns',85) pd.set_option('display.max_rows',85) After this command if we print df, shouldn't we see 85 rows of df? Or am I getting this wrong?
Hi Corey, thank you so much for this tutorial but I keep getting something missed up, Iin what context do we use the normal parenthesis (), this {} and the squared bracket [] ????
I followed your example for indexes. df.loc(). It works perfectly. However if I use df.loc[1:10,:], it throws an error. If I use another new dataframe object without having to create any indexes then df.loc[1:10,:], then it works perfectly. Please help me understand what's this confusion.
Hi Corey, at video time 6:33, after df.rest_index(inplace=True) it resets the index but now email column becoming the first column. How we can move the email column to the last column ? Thank you.
Do you have any real world projects with problems and solutions using pandas? Thanks for tutorials but i want to see more real life problems/solutions.
Hey everybody. I hope everyone's week is starting off well. I'm still working on the next video in the series, so I don't have a specific release date just yet. Just keep your eyes open. I'm hoping to have this entire series finished soon, but I'm not sure how long it will take me to record/edit the remaining video. I'll do my best to get them out ASAP (this week or next). Have a good one!
Hi Corey, can you please do tutorials on pytorch ? That would be so useful.
Hi, have you seen the release of pandas 1.0?pandas.pydata.org/pandas-docs/version/1.0.0/whatsnew/v1.0.0.html
Is this going to affect this series in any way?
Also thank your for all of your work! You do an incredible job!
Sir how many videos are in this series?
@@alanbarzilay6866 It's still a release candidate, so probably not. However, everything here could at some point become obsolete for sure.
The documentation on pandas is mostly pretty nice, so I would just look up how to do some specific thing should the "old way" stop working.
@@waynezor Release candidate means that features are probably set, it just needs more testing before they release the stable version. Agree with the rest, but why not include the new things if they are worth noting from now on?
Even after 4 years, this is the best Pandas video on TH-cam. Thank you Corey , for this.
Talk about beginner friendly?? This is one!!! Hands down the best!!!!!!!
Hands down best python tutorials on youtube. Nobody does so much for free. Thanks Corey
it isn't free
@@im4485 I def subscribed to brilliant.
I'm using pandas for a quite long time and sometimes I found it annoying (yet still very useful and mandatory in data science). Your videos make this library crystal clear. Thank you for this!
Thank you Corey. After this Pandas tutorials, please start the scikit-Learn and then TensorFlow2 tutorials
most likely never going to happen :(, but this would be soo good
Wish that could be possible. ':(
How Kind Can Someone Be?
He explains each and every detail and also explain things repeatedly so that anyone coming any of the video in the middle of the series will find it easy to follow the video.
Corey, I just want to appreciate your work here. I am learning a lot from your videos. Thank you for making them freely available.
Pandas is an enormously helpful tool with good documentation, but for those of us who learn best by example there can be a steep learning curve. These tutorials are the best I've seen for clearly and methodically working through the basics.
Chapters:
00:00 Intro
00:30 Recap of Dataset
01:00 Recap of What's an Index
02:06 How to Set DataFrame (Row) Indexes ('df.set_index('col_to_use')')
02:35 'inplace' Argument
03:40 '.index' Attribute
05:13 How to Reset (Row) Indeces ('df.reset_index()')
06:16 Set (Row) Index on DataFrame Creation () and Practice on Real-World Dataset ('pd.read_csv('file.csv', index_col='col_to_use')'
12:58 Sort Indexes (`df.sort_index(ascending=False)`)
15:02 Outro
Copied from @Adam Hendry for future reference
your tutorials are far better than the paid ones on other platforms
I can`t ensure if you will believe me or not when i tell you that i downloaded 130 tutorial video of your content about python, but the most important thing that i am sure about is, you are awesome, keep going believer
I learned Pandas on my own, by hit and trial, but after watching these videos, finally I am able to connect the dots and make some sense why things are like this. Thanks Corey, this will save my time to google every command :)
how do u learn ..how many works u did on your own
Thank you for this particular video. It's explained indexing in 15 minutes with much greater clarity than anything else I've used so far.
I am using a string index in my current project and this is all very useful. Thanks! This pandas series is gonna be awesome.
You know what Corey, you are the only person I would like to thank once I become a data scientist...
Thanks a lot Corey.. you are the best instructor out there.. I can't even imagine learning from anybody else. Can you please consider creating a series on pyspark and machine learning??
Can't believe how awesome you are! Really enjoying this series so far your instructions are so thorough and simple, you've really helped me grow so much in my aspirations. Thank you so much Corey, hope all is well in this tough time.
Wow, these videos are seriously so helpful! I've just been getting started with pandas, feeling frustrated because I just don't understand the syntax super well yet and thus having to google literally everything. This is making it so much easier to understand! I can't thank you enough and I'm looking forward to getting through all the videos! :)
Awesome, this is best Pandas series so far I have watched on internet...
BEST #PYTHON #channel ever
NO DOUBT...
Thanks a lot, Corey! It's evident that you put in a lot of effort into making your videos flawless. Where else could I get such clear and thorough explanations !?!
I am an amateur coder, I also have never posted a TH-cam comment, but thank you.... these videos are incredible
Thanks Corey for this awesome series... You are making complex things looks simple.. What I like the most about your series is that your Tutorial flow by explaining simple to complex in an understandable manner.. Keep this good work, you are bringing in differences in many Techies lives.
7:20
respondent 0: "I am a sttudent learning to code"
stack overflow: "are you a student"
respondent 0: "no"
stack overflow: "what is your education level"
respondent 0: "elementary school"
stack overflow: *mike wazowski bruh face
i dont need sleep i need answers
Thanks for this series, @Corey! Very helpful and very well done. I went to Brilliant to check them out to thank them for sponsoring your videos! Thanks Brilliant!
I enjoyed this video so much, thank you so much, I'm recommending your channel to all my friends. Watching your videos is a must!
Thank you so much!!
1.To reset index after loading csv ; df.reset_index
2 to set index after reading CSV; df.set_index(" ")
3.To reset index in place and permanently change dataframe ; df.reset_index(inplace= True)
4. To set index while reading the data(csv) ; df = pd.read_csv('data/survey_results_public.csv', index_col =" ")
5. To sort your index alphabetically; df.index_sort
5. To sort your index alphabetically in a descending order; df.index_sort(ascending = False)
I don't know how to thank you enough for this free gift. I wish I could subscribe more than once to this channel. you turn my life around. thank you
Watching one video everyday after work! Thanks for the amazing videos. They're easy to follow. I am looking forward to check the other courses as well.
Very nice video.. will recommend anyone who is in the world of data engineering. will look forward for the next video! Thank you Corey 👍
Hey Corey, Your way of teaching is really awesome, Anyone who is beginner can also grab it and take it forward easily. Waiting for your upcoming videos on pandas :-) and looking forward to new series in python like numpy etc. which can help us in data analysis. You are doing a great job.
This series is an instructional masterpiece!
Hey Corey, you did justice to this lecture! All for free! Be blessed!
The index tips are so useful to work with dataframe. Thank you for such a great work.
watched 1 and 2 . the best tutorial. And am watching the third. thanks a lot. you are the best.
I am finally getting into Pandas and these videos have been great!!!
I keep refering back to these pandas tutorial videos whenever I needed. Great job @coreyms.
I a so glad I found you video. Finally I found the answer I was looking for for 2 hours!. Thank you.
Really great videos Part 1, 2 and now 3. It was so hard to find a good Pandas tutorial but yours is Ivy School level explanation. 🎉
Talk about timing, I just started this series this morning
You are extremely a nice teacher. Good and detailed explanations in all your videos i have watched. Keep it up rolling for us beginners
This is top quality stuff again. As always from Corey.
Thanks Mr Corey, you are such a great teacher.
Manager Idiot is the best
they removed that question in 2020 survey xD
About time. Great timing! Thank you sir! Respect to you!
i can't believe I'm getting this for free
thank you sir
wow excellent tutorial, really well explained with awesome clarity. Keep up the good work!
Great video, thank you! 14:000 I know you covered - pd.set_options('display.max_columns',##) but I can't seem to get the schema dataframe to show that even if I do run that... - nevermind, I figured it out. It was just pd.set_options('display.max_rows',##) and I think you did cover that! Anyway, thanks again Corey!
Thanks, Corey! This playlist is really insightful
Best possible explanations ever...
Thank you for the video. I am grateful for your time and contribution. Kind regards, Akira.
So nice! I will like and coment in every video of this set! You deserve the best! thanks!
Yet another lovely lesson. Nice flow with a good combination of motivation and technical instruction. Thanks.
Just wondering how common the inplace=True argument is across Python generally, or is it specific to Pandas- first time I've seen it.
Great tutorial video as always. Thanks!
Thank you!! Very important and nice video series
Great course with clear explanation, great help to me. Thanks a lot.
Hey Corey. Your tutorials are awesome. It would be great if you produce how to use importlib library and dynamic module importing tutorials in future videos. Thank you very much.
Thank you so much for this wonderful pandas series🙏
Great lesson thank you!
Thank you very much for this clear and informative video! 😄
Hey Corey
A very good series. Learning from these and applying to Python visuals in Power BI. A bit limited in options there.
Would it interest you to make a few videos on handling Python in Power BI?
Thanks
Corey Schafer, you 're amazing. Thank you.
Thanks a lot Corey, your videos are very helpful :)
Thank you, Sir! 🧡🤍💚
As usual great video, thanks again!
Great lesson! Thank you!
print("BEST PYTHON LESSON ON UNIVERSE")
Thank you bro ;) Couldn't wait to make data visualization.
Very helpful videos indeed.
Very nice tutorial. Thank you.
Please Corey.. We need docker and microservices
Thanks man this very useful !!
Thank you for the great videos .
Hi teacher, I love the videos, Thanks for taking us through,
My data set after loading it in pandas its showing the "NaN" columns that are not there when i open the file direct using excel, what could be the issue?
Thanks!! very insightful, good video
Can't understand why would anyone dislike such a high quality work?!!! Thank you Corey...
one simple question, when using methods (df.set_index()) I get an error on Spyder.
'DataFrame' object has no attribute 'set_index'.... it works if pd.set_index is used instead?
1st comment...didn't watch it...first i like corey's video then i watch it...PS: First i disable my adblock....i urge everyone to do the same. Just out of curiosity...how many videos this pandas series consist of?..thank you for amazing videos..you're the best teacher Corey.
I still haven't finished recording the series yet, so I'm not exactly sure how I'll break up the last videos. But I _think_ it's going to end up being around 10 videos or so. Then I'm going to do another series of 5-10 videos specifically on plotting in Pandas.
Sir Can you please make Videos on ML also. You teach like a teacher is teaching to a 1st class student. I am very curious to study ML lectures by you Sir. Thankyou very much sir .😊😊
Overall good stuff. More thought needs to be given when choosing example data. For rows and columns it's natural to speak of the first or last row -- and even the first or last column.. Using 'first' and 'last' for column names is needlessly ambiguous.
Thank you, Corey!
Good job!
You deserve ⭐️⭐️⭐️⭐️⭐️
So well explained....
@coreyschafer. (or anyone who can help me) @11:40. I'm running this code on Pycharm while following your video and I'm getting a 'KeyError: 'MgrIdiot' message. The code has worked exactly as it should for any other row I've tried to look up ('Hobbyist', 'Age', etc).
Any idea why pycharm would specifically show a KeyError just for the 'MgrIdiot' row? I tried running schema_df = schema_df.astype('str) to change all values to strings, but that didn't help.
Thanks!
Love your videos
3 down, 8 to go.. Dated 5/25/2023
Thank you Corey for the video.
I have a small doubt:
pd.set_option('display.max_columns',85)
pd.set_option('display.max_rows',85)
After this command if we print df, shouldn't we see 85 rows of df?
Or am I getting this wrong?
Corey, I have same question as this
Thanks bro you're so amazing
Am from Iran
I love u😍
hey corey, please create some videos on numpy!
Hi Corey, thank you so much for this tutorial but I keep getting something missed up, Iin what context do we use the normal parenthesis (), this {} and the squared bracket [] ????
Thankyou Sir
I followed your example for indexes. df.loc(). It works perfectly. However if I use df.loc[1:10,:], it throws an error. If I use another new dataframe object without having to create any indexes then df.loc[1:10,:], then it works perfectly. Please help me understand what's this confusion.
I think it's cause u can't run loc after u do inplace=true
Thanks a lot. My question is how let index start from 1 instead of 0? Also, how to show ordinal number instead of ordinary numbers?
Hi Corey, at video time 6:33, after df.rest_index(inplace=True) it resets the index but now email column becoming the first column. How we can move the email column to the last column ? Thank you.
thankyou 🙂
Can you please also make machine learning tutorials .
And please provide time stamp for this video.
@Corey Schafer Thanks for the tutorial it's really very good but how you can access the questions from another excel?
Do you have any real world projects with problems and solutions using pandas? Thanks for tutorials but i want to see more real life problems/solutions.
Remercie for your work!