I'm just upskilling myself in Python for Data Analytics. I am really happy that I found your video on Pandas. A very big thanks for all your efforts. You got yourself a new subscriber today!!!
I appreciate you trying to accelerate the delivery of the information. Preparing the cells, speeding the coding, being to the point... There is way too much time that can be saved in teaching videos out there. Thank you!
The perfect cheat sheet for someone just starting! Saving this video for future reference. Also, video had great speed, good quality! Skipped through 10 or so videos until I finally landed on yours.
I was taking a statistics course online at a university I won't name. We basically had to display all this data as one of our assignments in the first week, and I struggled because I didn't know how to do it. And here you've explained it in 20 minutes! Thank you for making it easy to understand.
Thank you so much for this quick Crash course. I have been doing an online course but the problem is that the videos was too long and I just wanted a quick intro to Pandas. Thank God, I saw video and now I understand Pandas basics. Thanks once again.
I have always done data analysis using Stata and Spss. i need to add Python, Pandas and Numpy to my portfolio. That's why i am here. I like the CRUD initiative. It will make learning easier.
@@NicholasRenotte I am from Mechanical Engineering Branch and to entry into Data Science field doing course on Coursera (ibm) and watching such videos is only investment i can do :)
I just discovered your channel, and I am very impressed with its content. I plan on watching every single video you have. I'm new to ML so well done bro.
i like this kind of teaching! the use of every functions are explained clearly. btw omg you type so fast!!! i just checked whether i turned to 1.5 speed XDD
Nicholas you admire Andrew ng and I'm going for you......The best channel I found in the whole UA-cam......thanks for sharing this valuable content....
I am using pandas to explore connectivity in the brain!! I was wondering what's the most "pandas" way to do the following. Each row of my table is associated with a patient, while each column with a certain connectivity measure (200 of them). For each column n with label tag[n] I compute the average avg[n] =df[tag[n]].mean() and the standard deviation std[n] = sqrt( df[tag[n]].var()). I would like to run the following pseudocode: for row in df: for n in range(number of columns): row[n] = (row[n] - avg[n])/std[n] But it seems like iteration in pandas has its own weird rules to keep performance up. I can't really use apply or transform since my function depends on the column (its average and deviation, in particular). What do you suggest?
Is knowing Python a prerequisite to this? I wound up here because I asked Chat GPT if Excel was adequate for the type of data analysis I wanted to do, and it suggested I look into Python with Pandas. I know nothing about coding. But it seems like some of the things you explained were with the assumption that the viewer already knew/understood why to type it. Thanks
Can you please make a video or tell, what is the best library for handling parquet which has a hive structured data with multiple layers and various data types , fastparquet or pyarrow or pandas or polars.
Oh dude, very nice very clear. Thanks so much. Maybe it is not for beginners, but if you familiar little bit with Pandas it is very helpful. I want to install Jupiter Notebook already. Now I'm using Pycharm :D
Super useful video, great presentation, and explanation of many important functions, however, I am still not convinced of using Pandas. I can do much of this stuff with a Google sheet (or MS Excel) with the same results. Why then should I use Pandas? By the way, I am very new to this field (starting a course on ML) and I am wondering what are the uses of the many tools involved, and why are there many of them! I love Jupytor by the way, I think I'll keep using that one, super fun and easy to use!
It's mainly for inline automation, agreed I still use Excel a ton but Python extends this out massively for example you could build hardcore ML models using a dataset prepared using Pandas. It eliminates the need for manual handling.
Hello Nicholas, Thanks for your great videos. I need your help. I have Binance Btc DataFrame, first column is epoch datetime value. I want to create two new columns from (first column) unix epoch time as date, time seperated. example value of : df['epoch'] = 1641898800000 target values : df['only_date'] = '2021-03-31' df['only_time'] = '23:00' how can i do it without loop, because loop taking long time to apply. Thanks for your help.
you can see mine too. Most of the fundamnetal Python tutorials, present with ppt and coding, and source files can be found in the description of each video.
good video i am working Student_performance_data _.csv from Kaggle i wanted to replace all the gender column with 0 for female and 1 for male can you help
i haven't gone to university, but right now i am working as a data analyst because of UA-cam videos. thank you Nick....
Which company dude
Excellent! 🎉
How did you find jobs and experience when you were learning?
That's cool. The technology evolving we need universities only to protest by losers.
what projects did you do to get hired?
I'm just upskilling myself in Python for Data Analytics. I am really happy that I found your video on Pandas. A very big thanks for all your efforts. You got yourself a new subscriber today!!!
Heyyyy, thanks Deepak!
I appreciate you trying to accelerate the delivery of the information. Preparing the cells, speeding the coding, being to the point... There is way too much time that can be saved in teaching videos out there. Thank you!
The perfect cheat sheet for someone just starting! Saving this video for future reference. Also, video had great speed, good quality! Skipped through 10 or so videos until I finally landed on yours.
The intro is so cute. Literally makes anyone come to see pandas and learn about them too!
😂 both cute and practical!
I was taking a statistics course online at a university I won't name. We basically had to display all this data as one of our assignments in the first week, and I struggled because I didn't know how to do it. And here you've explained it in 20 minutes! Thank you for making it easy to understand.
Most underrated tech channel on UA-cam. Bravo!
Thank you so much for this quick Crash course. I have been doing an online course but the problem is that the videos was too long and I just wanted a quick intro to Pandas. Thank God, I saw video and now I understand Pandas basics. Thanks once again.
I seriously needed this course for my project (took a lot of time o write notes converting 20min to 2hrs). Just perfect. Thank you very much
I have always done data analysis using Stata and Spss. i need to add Python, Pandas and Numpy to my portfolio. That's why i am here. I like the CRUD initiative. It will make learning easier.
Just started my internship for data science and this video helped me solidify my knowledge on pandas!
Amazing just what I needed before an interview did me a solid ! Thanks !
Nice taster, mate. Learning Python and was curious about Pandas. This did the job.
I'm a beginner and you crush the pandas library and data science for me. thanks a lot
This Helped a lot as a revision before my lab exam. Really Thanks Nicholas. great work
YESS! Awesome!
Amazing. I got to know you from a webinar and it landed me to your linkedin and then finally here.
Awesome! I remember talking to you, it was one of the global webinars!
@@NicholasRenotte I am from Mechanical Engineering Branch and to entry into Data Science field doing course on Coursera (ibm) and watching such videos is only investment i can do :)
best pandas crash course out there! great practical demonstration with no nonsense!! Thank you Nicholas!!!
Awersome. Thank you very much! I tried to undarstand how to use pandas for 3 hours. But your video have solved my questions! Like.
YESSSS, glad you enjoyed it @Роман Васильев
I like this format. Clear and concise.
Beautiful tutorial man, going straight to the point with the key fundamentals. I appreciate it.
Best Explanation ever...... Thank you Mr. Nick
I just discovered your channel, and I am very impressed with its content. I plan on watching every single video you have. I'm new to ML so well done bro.
Best panda programming video brief and easy to assimilate😇😌
i like this kind of teaching!
the use of every functions are explained clearly.
btw omg you type so fast!!!
i just checked whether i turned to 1.5 speed XDD
Thanks sooo much @kotori!! 🤣 it's sped up, i wish I typed that fast!
The best Pandas tutorial I've found, cheers.
Thanks so much!! Plenty more to come!
I wish I would have come across your videos when I was learning pandas. Best summary.
Pls keep doing your job; I don't know how to thank you enough. As always, you are my superhero.
this was crisp and to the point pandas video.. thanks a lot !!
This is Brillant, so many theory videos on pandas, but to teach in such a clear manner... you are amazing. Thank you, this is a game changer.
Nicholas you admire Andrew ng and I'm going for you......The best channel I found in the whole UA-cam......thanks for sharing this valuable content....
Thank you very much! just grabbed a used gigabyte rx580 egpu to run 3x monitors off a 2014 mac mini.
Thanks bro! I'm starting in data science and your youtube channel is a gold mine! Thanks for share your knowledge, tips and tricks!
Super productive introduction to Pandas. Thanks Nicholas!
This is some pretty solid info! Really helped me understand what’s going on
Awesome work @FreshMilkHD, glad you enjoyed it!
You are a point fisher. Straight to the moon. Thanks Nick.
Amazing session keep dropping such short and crisp videos ❤❤ love from India
Thanks Nicholas, great refresher . I am not a professional developer but wanted a quick refresher for some stats I am researching
this is the best pandas video on youtube
Ohhhhh thanks so much @Rishit!
This is exactly what I was looking for. Short and sweet!
You're a legend! I'm gonna learn from your body of work everyday!
I am using pandas to explore connectivity in the brain!! I was wondering what's the most "pandas" way to do the following.
Each row of my table is associated with a patient, while each column with a certain connectivity measure (200 of them). For each column n with label tag[n] I compute the average avg[n] =df[tag[n]].mean() and the standard deviation std[n] = sqrt( df[tag[n]].var()).
I would like to run the following pseudocode:
for row in df:
for n in range(number of columns):
row[n] = (row[n] - avg[n])/std[n]
But it seems like iteration in pandas has its own weird rules to keep performance up. I can't really use apply or transform since my function depends on the column (its average and deviation, in particular).
What do you suggest?
I want you to know, YOU'RE THE MAN!!
Thanks homie 🙏, means a ton Moises!!
This is a fantastic mini-course. Thank you, man
Is knowing Python a prerequisite to this? I wound up here because I asked Chat GPT if Excel was adequate for the type of data analysis I wanted to do, and it suggested I look into Python with Pandas. I know nothing about coding. But it seems like some of the things you explained were with the assumption that the viewer already knew/understood why to type it. Thanks
Thank you Nick. Such a great video.
Can you please make a video or tell, what is the best library for handling parquet which has a hive structured data with multiple layers and various data types , fastparquet or pyarrow or pandas or polars.
Tell us all what secrets you use, we will all benefit from it. Hope to make a video on how we can take a sure shot in the next video.
Thanks Nick. Well organized and presented. A nugget- of-time well spent as viewer and novice coder.
Great video learned a lot in a short time. Thanks
I don't really use panda for anything, but I have some data science project that i'v done in panda and jupyternotebook
Thank you so much Nick👏
clear and precise tutorial. Thank you.
This is such a informative video and I'm not even done yet, thank you so much!
thanks a lot for your video. really helped me to learn how to preprocess my data.
awesome! concise and crisp presentation. Appreciate your efforts for this @Nicholas
Thanks!
Oh dude, very nice very clear. Thanks so much. Maybe it is not for beginners, but if you familiar little bit with Pandas it is very helpful. I want to install Jupiter Notebook already. Now I'm using Pycharm :D
Nice! Go getem!
Very good job and very well explained
Subscribed
Hello. this command did not bring any result
df = pd.read_csv('survey_results.csv') . Would you be able to help?
Thank you
Very useful video Nicholas, Thanks , Love your channel, I am Fahad from Linkedin :)
Awesome video, thank you Nicholas!
Clear and concise
Thanks so much @Immanuel!
Great job. Short, sweet, to the point, helpful!
Hi Nick I indeed like your explanation techniques, currently I have a project and would like some clarification so how do I reach you directly?
Great tutorial, very helpful. Thank you!!!
very good and clear explanation. Thanks!
Thanks a bunch @shirvas1!
Nice !! Thank you Brother for this great Job you are a King !! This help me a lot.
Oh, thank you so much! Glad you found it useful!!
Short but very informative great video
Very helpful video. Short and informative!
Thanks so much @SnowryCocoon!
Short & Crisp.. 👌👌
Speedrunning for an interview
This was so useful THANK YOU
Extremely helpful. Thank you!
Awesome video, thank so much!!, Nicholas you rock!!
Took sometime to set up best video to crack in for pandas
neat content Nicholas Renotte. I shattered that thumbs up on your video. Always keep up the awesome work.
Super useful video, great presentation, and explanation of many important functions, however, I am still not convinced of using Pandas. I can do much of this stuff with a Google sheet (or MS Excel) with the same results. Why then should I use Pandas?
By the way, I am very new to this field (starting a course on ML) and I am wondering what are the uses of the many tools involved, and why are there many of them!
I love Jupytor by the way, I think I'll keep using that one, super fun and easy to use!
It's mainly for inline automation, agreed I still use Excel a ton but Python extends this out massively for example you could build hardcore ML models using a dataset prepared using Pandas. It eliminates the need for manual handling.
@@NicholasRenotte Thanks for taking time to answer my question!
Thank you!
Very specific and clear.
Thank you, This was super helpful.
Hello Nicholas,
Thanks for your great videos. I need your help.
I have Binance Btc DataFrame, first column is epoch datetime value.
I want to create two new columns from (first column) unix epoch time as date, time seperated.
example value of : df['epoch'] = 1641898800000
target values :
df['only_date'] = '2021-03-31'
df['only_time'] = '23:00'
how can i do it without loop, because loop taking long time to apply.
Thanks for your help.
This is golden, thank you
Thanks a bunch @Thiago!
Great Explanation Nich, Thank you so much :")
If my csv data frame has no column headings and data is not organized how I can create a column headings using pandas
Very helpful video..
Thanks
Thank you so much bro ! this is so helpful for me 😍
Thanks that was very helpful.
loved it.. thanks a tin! complete time saviour for beginners like me.
Thanks for this!
COULD YOU ABLE TO DO THIS KIND OF ANALSYS ON STOCK MARKET DATA ? IF SO PLEASE DO IT
Please could you make a Seaborn in 20 minutes?
Thank you so much it is so helpful.
you can see mine too. Most of the fundamnetal Python tutorials, present with ppt and coding, and source files can be found in the description of each video.
@@easydatascience2508 Ok thank you. Best of luck
This is amazing tutorial
what does 130 means in import pandas as pd. sorry i am absolute noob
Excellent video!
Great video , thanks 👍👌🙌🙏
Great video, thank you
Awesome video cheers
Thank you so much pal 🍻
Anytime! Glad you enjoyed it!
good video i am working Student_performance_data _.csv from Kaggle i wanted to replace all the gender column with 0 for female and 1 for male can you help
thanks man