Want to follow along with the same dataset and python environment? Big thanks to someone who made a kaggle notebook with this entire tutorial: www.kaggle.com/code/lizhecheng/pandas-2-0-1-tutorial/notebook Just fork the notebook and explore the data with pandas!
This is a masterpiece Rob. A condensed pandas course. Wow. Even regular Data Scientist can refresh their mind or discover tips and tricks they are not used to use such as the query methods. And what I like the most, it all fits within 23 minutes. I would love to have such videos for some of the other commons libs.
@@robmulla he did, and i love it too. If ive mastered these pandas functions you showed am i ready to move on do you think? maybe just practice with exercise's until i incorporate it in projects?
This is the best video on pandas I’ve seen so far (and I’ve seen dozens). Thank you so much for keeping your explanations short and up to the point!!! Gonna use the video as my top 1 reference resource when I feel stuck!
By far the best Pandas tutorial I've come across! Your clear explanations and engaging style make complex concepts so much easier to grasp. It would be fantastic to see more videos covering other common libraries as well! Your content is truly inspiring and has motivated me to consider a career change into data science. Thank you for sharing your knowledge!
Thank You so much for putting this together Rob, you make it look so easy and it's well explained and very clear. I really appreciate you for sharing this with everyone !
This video came many times in my home page recommendation but i was ignoring cause it's just a 22 min video.....but boom 🤯 ! Omg not even a 2 hours video of others cover all these.❤ thanks
same, i kept thinking i need to know more and ive realised i know even more than this tutuorial, so im gonna just set practice time so i dont forget anything and move on. Maybe he should say, 2 hrs of pandas in 23 mins lol
I've been learning Pandas for a couple of years on and off now, and have even used it a little at work, and yet there were still a few things in here I didn't know about. The rolling method in particular is a game changer, I've been manually creating functions to do that and now I can just do it in one line of code (and likely faster than my hacked together functions).
This video is fantastic. informative, concise and a strong foundation for pandas. Most importantly, it is easy to understand and follow along. Thanks for the video, I'm subscribing!
@@robmulla I typically take notes when watching videos like this so I am accustomed to pausing. In my opinion it's better when there isn't much filler in between so that it's easy to get to the next point or move back to where you want.
I'm wanting to ask a bit more of a meta question. How much time do you spend outside of work on your skills? How much passion or drive do you have and what are your routines? I work in medical ML and came across your EDA video and wanted to get a successful person's view on how to improve and grow.
Great video Rob, I would love to see you explaining Machine Learning and Deep Learning models, from theory to practice using scikit-learn, Keras or Pytorch. You really made things look easy. Can't wait to see another of your awesome videos.
It was really helpful, but I think you missed a section for converting data types in dataframes, specially for date types. thank you very much for this summary.
Thank you so much ❣️ I have watched your previous pandas video, but this had everything ❤ it was awesome ❤ I understood everything except for to write csv, Thank you so much for this amazing video ❤
Thanks for the great Video! How did you manipulate that folder with bunch of.csv files to put fit all together in the df? And how to deal with irregular datas in a typical case like this? Have you already done some tutorial explaining and detailing these kind of tasks?
Thanks for this. Straight to the point. Great! Do you think Polars is going to be especially disruptive? I’ve been using it a bit and I can’t believe how much faster it is at a lot of things. But pandas is very entrenched (and probably has slightly more friendly syntax).
Hello Rob great video! I have a question, how do you enable the description of the methods that you use. They are showing on the right when you type in the ‘dot’.
nice, if would be useful if you could put a link for downloading your dataset so we could play around with your data while you explain, it would be appreciated, for example I would need to see by myself what the difference reindexing does when combining datasets, it is not immediately obvious to me and would require some test and comparisons
The datset is on kaggle. Check out this notebook where someone linked the dataset and included the tutorial code: www.kaggle.com/code/lizhecheng/pandas-2-0-1-tutorial/notebook
@robmulla do you know a website or where I can find data cleaning exercises or challenges? I want to practice cleaning different kinds of data, any suggestions will be helpful
Hi, i have one silly question. How do you get intellisense i.e. functions menu for each object and for each function, the whole list of available parameters. Which IDE you are using ? It really helps to focus on use case rather than mugging up the function names and their syntax.
I’m sorry I know this will sound dumb to you guys but how is it listing all option after writing a part of if. Like read_ ( then a whole bunch of different commands like read_csv and so on)? I’m using jupyter lab everyday and haven’t seen that ! Cool
Hi, does anybody know a website or where I can find data cleaning exercises or challenges? I want to practice cleaning different kinds of data, any suggestions will be helpful
Hi @robmulla In Handling Missing Data chapter, would be nice, if you could provide your insight as the best approach and what is normally recommended to do, if it is fillna or dropna, I know that it could be subjective to the task at hand, but having insight as expert would be nice.
I'm new to Data Science. Type every information on my jupyter lab. And im getting error and not dine. I don't understand this, smh what I'm im doing wrong
Want to follow along with the same dataset and python environment? Big thanks to someone who made a kaggle notebook with this entire tutorial: www.kaggle.com/code/lizhecheng/pandas-2-0-1-tutorial/notebook
Just fork the notebook and explore the data with pandas!
This is a masterpiece Rob. A condensed pandas course. Wow. Even regular Data Scientist can refresh their mind or discover tips and tricks they are not used to use such as the query methods. And what I like the most, it all fits within 23 minutes. I would love to have such videos for some of the other commons libs.
+1
+1
+1
+1
This 20 min video is equivalent to 2hrs of other youtube videos...masterpiece
Thanks! Tell your friends.
@@robmulla he did, and i love it too. If ive mastered these pandas functions you showed am i ready to move on do you think? maybe just practice with exercise's until i incorporate it in projects?
This is truly incredible! It's the finest pandas tutorial available on the internet, offering a remarkable balance of breadth and depth.
It took me 2 hours and 30 minutes to revise pandas, but it's worth it
Not enough half way through and I can tell this video is gold.
This is the best video on pandas I’ve seen so far (and I’ve seen dozens). Thank you so much for keeping your explanations short and up to the point!!! Gonna use the video as my top 1 reference resource when I feel stuck!
By far the best Pandas tutorial I've come across! Your clear explanations and engaging style make complex concepts so much easier to grasp. It would be fantastic to see more videos covering other common libraries as well! Your content is truly inspiring and has motivated me to consider a career change into data science. Thank you for sharing your knowledge!
Thank You so much for putting this together Rob, you make it look so easy and it's well explained and very clear. I really appreciate you for sharing this with everyone !
Glad it helped you!
Awesome. This is a zipped version of the tutorial.. Would need to rewind many times to understand completely. Good Job
Would love to see a "level 2" which has more tips and tricks for experienced users!
Absolutely a masterpiece of a tutorial this one is! Hope you do more of this kind! Thank you for helping me to get kick started with Pandas!
Thank u very much.
I can now officially announce and recommend this video to my friends as one stop pandas tutorial and solution.
Thanks Rob
we are waiting for the next part! I personally wanna see sth on visualization!
Thanks for the feedback. I’ll keep that in mind for the next video.
This video came many times in my home page recommendation but i was ignoring cause it's just a 22 min video.....but boom 🤯 ! Omg not even a 2 hours video of others cover all these.❤ thanks
Love that! Share it with a friend or two.
@@robmulla ok
check ur bed tommorow
jk
same, i kept thinking i need to know more and ive realised i know even more than this tutuorial, so im gonna just set practice time so i dont forget anything and move on. Maybe he should say, 2 hrs of pandas in 23 mins lol
@@Goutham-exists oh no your not LGBT smh
I've been learning Pandas for a couple of years on and off now, and have even used it a little at work, and yet there were still a few things in here I didn't know about. The rolling method in particular is a game changer, I've been manually creating functions to do that and now I can just do it in one line of code (and likely faster than my hacked together functions).
Can you give an example of a rolling method application? I'm curious
@@mark-dy9zomoving averages
Thanks for this video. Packed with info, but still easy to follow, no small talk… Really appreciate your effort!
This video is fantastic. informative, concise and a strong foundation for pandas. Most importantly, it is easy to understand and follow along. Thanks for the video, I'm subscribing!
Really appreciate the feedback. Glad you found it easy to follow. I was a little worried it might be too fast.
@@robmulla I typically take notes when watching videos like this so I am accustomed to pausing. In my opinion it's better when there isn't much filler in between so that it's easy to get to the next point or move back to where you want.
I can tell even before watching this video that's its great!!! You're such a great tutor.
Wonderful channel for beginner data analysts & learned a lot of concepts from you…. Great work man
I'm wanting to ask a bit more of a meta question. How much time do you spend outside of work on your skills? How much passion or drive do you have and what are your routines? I work in medical ML and came across your EDA video and wanted to get a successful person's view on how to improve and grow.
Thank you for this lesson and all your work. As always, I learn so much from you! Any chance you'd do a video lesson on data cleaning? 🙏
Great work….thank you for posting the kaggle file!
Great video Rob, I would love to see you explaining Machine Learning and Deep Learning models, from theory to practice using scikit-learn, Keras or Pytorch. You really made things look easy. Can't wait to see another of your awesome videos.
Great tip on renaming the multi index columns!!
Glad it was helpful!
Thank you for the videos Rob, your hard work is highly appreciated.
Hi. I wish I watched this before my last project. Hope you will do an advanced series.
Thanks Rob for sharing the knowledge and experience to data community 😊
🙌
One of my favorite teachers
Thanks, Rob. That's a great summary of the features. Really useful!
It was really helpful, but I think you missed a section for converting data types in dataframes, specially for date types. thank you very much for this summary.
Gratitude 🙏 bravo 👏 Maestro 👏
How is your data analysis going on nowadays?
Fair introduction on pandas library
Thank you for the info
Are you streaming this evening?
Thank you so much ❣️ I have watched your previous pandas video, but this had everything ❤ it was awesome ❤
I understood everything except for to write csv,
Thank you so much for this amazing video ❤
Thanks for the content, Rob! it's really excellent! Can you do another video like this but with numpy?
Thanks for the great Video!
How did you manipulate that folder with bunch of.csv files to put fit all together in the df? And how to deal with irregular datas in a typical case like this?
Have you already done some tutorial explaining and detailing these kind of tasks?
Thanks for such a beautiful video!
Very cool ninja panda style!!! So useful and like a real pro awesome!!!
It is solid tutorial for Data Geeks. Thank you)
This is great work!! Thank you very much for putting it out here!!
Thanks Rob 15 min done still 7 to go.
Nice! 🙌
thanks for the video, one request though, can we have the same dataset so we can follow along.
Brilliant tutorial. Absolutely the best. Thank you, thank you,🏆🏆🙏🙏
Very easy to follow along, thank you!
Thanks for this. Straight to the point. Great!
Do you think Polars is going to be especially disruptive? I’ve been using it a bit and I can’t believe how much faster it is at a lot of things. But pandas is very entrenched (and probably has slightly more friendly syntax).
Magic Rob! hopefully be like you one day
Good Intro! Thanks!
Very very helpful! thank you so much for this upload
Nice Video Rob. This helped me a lot :)
Thanks bro
Hello Rob great video! I have a question, how do you enable the description of the methods that you use. They are showing on the right when you type in the ‘dot’.
Thanks. With Jupyter you just do shift-tab
nice, if would be useful if you could put a link for downloading your dataset so we could play around with your data while you explain, it would be appreciated, for example I would need to see by myself what the difference reindexing does when combining datasets, it is not immediately obvious to me and would require some test and comparisons
The datset is on kaggle. Check out this notebook where someone linked the dataset and included the tutorial code: www.kaggle.com/code/lizhecheng/pandas-2-0-1-tutorial/notebook
Great video as always ! Would be Nice to have the same one with polars
Great as always! Now get to work and make tutorials for seaborn and matplotlib :)
Just brilliant! Thank you so much!
You're very welcome!
Thanks Rob!
Thanks for sharing your knowledge
Great lesson
Glad you liked it!
Do you have a panda functions cheat sheet (df functions) available? Thanks. Follower 👍
Hi Rob, Please start some series on Tableau. Regards.
Hi Rob,how to read the details of function in jupyter lab just like 2:22
Thank you Rob 😊
this vid is a gem
Thanks! Glad you liked it.
QQ: what is the perfect time span to collect sales data (one and only store), to create a data-set for it’s future analysis… 1 year, 2 years?
Thanks!!
Thank you Rob!!!
hi! What plugin do you use to see the details of each function?
Great question! Shift-tab in jupyterlab.
Awesome! Thanks!
Great stuff!
@robmulla do you know a website or where I can find data cleaning exercises or challenges? I want to practice cleaning different kinds of data, any suggestions will be helpful
Hi, i have one silly question. How do you get intellisense i.e. functions menu for each object and for each function, the whole list of available parameters. Which IDE you are using ?
It really helps to focus on use case rather than mugging up the function names and their syntax.
cover EDA for time series data
Hey Rob! Any resouce to download and handson with parquest file
Thanks Rob 😁.
Can u tell me where u execute ur code/ How do I get to the same terminal
Thanks!
kagle desnt seem to have any datasets in parquet format, moreover it cant seem to preview those files
I’m sorry I know this will sound dumb to you guys but how is it listing all option after writing a part of if. Like read_ ( then a whole bunch of different commands like read_csv and so on)? I’m using jupyter lab everyday and haven’t seen that ! Cool
Hi, does anybody know a website or where I can find data cleaning exercises or challenges? I want to practice cleaning different kinds of data, any suggestions will be helpful
How did you make your Jupiter look like that
Awesome ❤
Hello Rob.
How to handle JSONArray in dataset?
WERY NİCE .. THANKS FOR YOUR EFFORTSS :))
Perfect!
amazing!!
Please add speech to audio method
Nice dictionary.
Hi @robmulla
In Handling Missing Data chapter, would be nice, if you could provide your insight as the best approach and what is normally recommended to do, if it is fillna or dropna, I know that it could be subjective to the task at hand, but having insight as expert would be nice.
I'm new to Data Science. Type every information on my jupyter lab. And im getting error and not dine. I don't understand this, smh what I'm im doing wrong
Doesn’t appear as tho you really used the power of pandas 2.0 with the backend pyarrow default param and checking for nulls/data types :-(
1:52 min. how to get that dropdown option
Masterpiece thanks thief!
only jesus can save me
Its time for you to show us hiw to build a dashboard
how to get the data of this video
🤗
Great refresher, but too fast for tutorial. I suggest breaking it in chuncks.
is this guy AI generated? His jawline is too perfect.
No AI. I’m a real person.
Audio writing methods