Learning Pandas for Data Analysis? Start Here.

A high paced overview of many of the pandas core functionality. As one of the most popular libraries in all of programming, Pandas is an essential tool for learning data wrangling. Watch this video to get a good foundational understanding of what is possible.
Intro to Jupyter: • Jupyter Notebook Compl...
Kaggle notebook made by a viewer! www.kaggle.com/code/lizhechen...
Download the dataset here: www.kaggle.com/datasets/robik...
Timeline:
00:00 Intro
00:57 Importing Pandas
01:26 Data I/O
01:51 Reading From Files
03:03 Writing to Files
03:36 DataFrame Basics
04:57 DataFrame Summary
06:12 Subsetting Columns
07:19 Select dtypes
07:34 Select as Series vs DataFrame
07:58 .loc and .iloc
09:37 .loc Filter Expressions
10:50 .query
11:31 Summary Statistics
12:10 .agg
12:53 Sumarizing Categoricals
13:43 rank, shift, cumsum
14:44 Rolling methods
15:21 Clip
15:41 Groupby
16:44 New Columns
17:33 Sorting
18:30 Missing Data
19:33 Combining Data
19:55 concat
21:01 Merge DataFrames
21:52 Merge Suffixes
22:34 Bonus
Check out my other videos:
Data Pipelines: Polars vs PySpark vs Pandas: • The BEST library for b...
Polars for Data Science: • Polars: The Next Big P...
Speed up Pandas Dataframes: • This INCREDIBLE trick ...
Avoid These Pandas Mistakes: • 25 Nooby Pandas Coding...
Links to my stuff:
* KZbin: youtube.com/@robmulla?sub_con...
* Discord: / discord
* Twitch: / medallionstallion_
* Twitter: / rob_mulla
* Kaggle: www.kaggle.com/robikscube

[@robmulla]

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!

[@spacephenix9849]

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.

[@pranjalpandey147]

+1

[@ramboram2685]

+1

[@mujibai]

+1

[@chauhanknight07]

This 20 min video is equivalent to 2hrs of other youtube videos...masterpiece

[@robmulla]

Thanks! Tell your friends.

[@avonzo]

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!

[@SmadeX2]

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!

[@elu1]

This is truly incredible! It's the finest pandas tutorial available on the internet, offering a remarkable balance of breadth and depth.

[@paveluhliar]

Thanks for this video. Packed with info, but still easy to follow, no small talk… Really appreciate your effort!

[@irfanshaikh262]

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

[@samanvithajanga]

Wonderful channel for beginner data analysts & learned a lot of concepts from you…. Great work man

[@thomaskwesimwaba9151]

Thank you for the videos Rob, your hard work is highly appreciated.

[@sojourner5294]

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 !

[@robmulla]

Glad it helped you!

[@IsraRM]

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.

[@PaulMcKillop]

Thanks, Rob. That's a great summary of the features. Really useful!

[@franciseigbe2796]

I can tell even before watching this video that's its great!!! You're such a great tutor.

[@kiara4345]

This is great work!! Thank you very much for putting it out here!!

[@okok-sc2cx]

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 ❤

[@syedhaider0916]

Not enough half way through and I can tell this video is gold.

[@_RahulDewangan]

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

[@robmulla]

Love that! Share it with a friend or two.

[@Goutham-exists]

@@robmulla ok check ur bed tommorow jk

[@mikep4981]

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]

Really appreciate the feedback. Glad you found it easy to follow. I was a little worried it might be too fast.

[@mikep4981]

@@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.

[@kamranzamanni6826]

Very easy to follow along, thank you!

[@nusratsayyed8560]

Thanks Rob for sharing the knowledge and experience to data community 😊

[@robmulla]

🙌

[@Arctect]

Very cool ninja panda style!!! So useful and like a real pro awesome!!!

[@alfonsourquidi9778]

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? 🙏

[@user235fhrdiib]

It is solid tutorial for Data Geeks. Thank you)

[@whatisagoodusernamehere]

we are waiting for the next part! I personally wanna see sth on visualization!

[@robmulla]

Thanks for the feedback. I’ll keep that in mind for the next video.

[@DavidPonzio-up8ln]

Good Intro! Thanks!

[@lucasoliveirapaes]

Thanks for the content, Rob! it's really excellent! Can you do another video like this but with numpy?

[@phamtienthinh1795]

It took me 2 hours and 30 minutes to revise pandas, but it's worth it

[@oukiebotha2227]

Brilliant tutorial. Absolutely the best. Thank you, thank you,🏆🏆🙏🙏

[@ronbzalen]

Great tip on renaming the multi index columns!!

[@robmulla]

Glad it was helpful!

[@chriskeo392]

One of my favorite teachers

[@Blahcub]

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.

[@akshaynitinvaidya]

Very very helpful! thank you so much for this upload

[@level10peon]

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).

[@mark-dy9zo]

Can you give an example of a rolling method application? I'm curious

[@andrewmk8514]

​@@mark-dy9zomoving averages

[@gamerfisch5117]

Nice Video Rob. This helped me a lot :)

[@AnastasiyaKaliutchyk]

Just brilliant! Thank you so much!

[@robmulla]

You're very welcome!

[@TATAWAKO]

Magic Rob! hopefully be like you one day

[@ruanstg]

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?

[@dailinchibasgoico6508]

Thanks for sharing your knowledge

[@andrewmk8514]

Hi. I wish I watched this before my last project. Hope you will do an advanced series.

[@teddybear7949]

Great video as always ! Would be Nice to have the same one with polars

[@mathiaz943]

Great stuff!

[@tmb8807]

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).

[@bassamsaleh8034]

thanks for the video, one request though, can we have the same dataset so we can follow along.

[@Dongnanjie]

Thank you Rob!!!

[@alirezashahinmehr]

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.

[@enricomendiola9952]

Thank you Rob 😊

[@sandie_jr]

Thanks Rob!

[@bisiadeyemo3082]

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

[@ryanzhan1513]

Hi Rob,how to read the details of function in jupyter lab just like 2:22

[@SuperSumittanwar]

Hey Rob! Any resouce to download and handson with parquest file

[@Christianboy2231]

Can u tell me where u execute ur code/ How do I get to the same terminal

[@jahunmoayedzadeh9194]

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

[@Arkantosi]

Great as always! Now get to work and make tutorials for seaborn and matplotlib :)

[@CaribouDataScience]

Are you streaming this evening?

[@bisiadeyemo3082]

@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

[@ravishmahajan9314]

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.

[@am0x01]

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.

[@vinsensilitonga9148]

Great lesson

[@robmulla]

Glad you liked it!

[@txreal2]

Do you have a panda functions cheat sheet (df functions) available? Thanks. Follower 👍

[@rubenagurcia906]

amazing!!

[@enricomendiola9952]

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’.

[@robmulla]

Thanks. With Jupyter you just do shift-tab

[@s.joseph4838]

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

[@Shahidma58]

Hi Rob, Please start some series on Tableau. Regards.

[@therickestpicklerick]

Perfect!

[@sunnykumar-iz7bq]

1:52 min. how to get that dropdown option

[@prashlovessamosa]

Thanks Rob 😁.

[@therealrucleshe7662]

this vid is a gem

[@robmulla]

Thanks! Glad you liked it.

[@swannschilling474]

Awesome ❤

[@ProfitPioneers69]

Thanks bro

[@obayram4615]

WERY NİCE .. THANKS FOR YOUR EFFORTSS :))

[@vmartme]

Thanks!

[@kancharlasrimannarayana7068]

cover EDA for time series data

[@pabloarizono8398]

hi! What plugin do you use to see the details of each function?

[@robmulla]

Great question! Shift-tab in jupyterlab.

[@thecaptain2000]

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

[@robmulla]

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

[@twink276]

This is great

[@aldocastillo1194]

how to get the data of this video

[@MaxTheKing289]

Masterpiece thanks thief!

[@AyahuascaDataScientist]

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 :-(

[@prashlovessamosa]

Thanks Rob 15 min done still 7 to go.

[@robmulla]

Nice! 🙌

[@chrisw1462]

Nice dictionary.

[@prashlovessamosa]

Hello Rob.

[@Artyom_E]

🤗

[@datawithtess]

Its time for you to show us hiw to build a dashboard

[@fakhreddinemilouchi6013]

Great refresher, but too fast for tutorial. I suggest breaking it in chuncks.

[@fisherh9111]

is this guy AI generated? His jawline is too perfect.

[@robmulla]

No AI. I’m a real person.

[@user-fk8wl4uk7b]

only jesus can save me

[@user-fk8wl4uk7b]

jesus christ bless you

[@user-xn8wg6yw7g]

Helpful overview. Good content. But way too fast. Not everyone has an IQ of 150, Mr Mulla. Slow down..