Exploratory Data Analysis with Pandas Python

In this video about exploratory data analysis with pandas and python, Kaggle grandmaster Rob Mulla will teach you the basics of how to explore data using python and pandas. Exploratory Data Analysis it a necessary tool for any data scientist. Pandas is a MUST for anyone getting into data science with python. Python is the #1 coding language for data science and has been growing over the years as an essential tool, with Pandas being the main data wrangling module. Kaggle Grandmaster Rob goes over it all in this video. In this video we discuss the basics of how to use explore data including...
Timestamps:
00:00 Introduction
01:00 Imports and reading data
03:35 Data Understanding
06:40 Data Preparation
20:57 Feature Understanding
27:35 Feature Relationships
35:30 Asking a Question about the Data
40:00 Final Thoughts
Follow me on twitch for live coding streams: / medallionstallion_
Intro to Pandas video: • A Gentle Introduction ...
Link to kaggle notebook used in the tutorial: www.kaggle.com/robikscube/int...
* KZbin: / @robmulla
* Twitch: / medallionstallion_
* Twitter: / medalliondata
* Kaggle: www.kaggle.com/robikscube
#Python #Coding #DataScience #Kaggle

[@robmulla]

Chapters don't appear to be working for my videos for some reason. Here are the timestamps for the video: 00:00 Introduction 01:00 Imports and reading data 03:35 Data Understanding 06:40 Data Preparation 20:57 Feature Understanding 27:35 Feature Relationships 35:30 Asking a Question about the Data 40:00 Final Thoughts

[@oshogweikekhai5499]

amazing video, please can you make available the dataset used? thank you

[@Pluvo2for1]

Hi Rob. I'm new to notebooks. Could you plese explain why you don't need an explicit print statement to view cell output?

[@cocgamingstar6990]

This was one of the bad video and non industry knowledge

[@ABYHYDROS]

😮

[@saintsaens3517]

As a begginer in data this really opend my eyes as to how things works. Your explanations are very clear and I can feel how passionate you are. Great video

[@robmulla]

Glad it was helpful! I am passionate about it, and excited when I hear people are learning from my videos.

[@arunkumark6351]

So true,, though there are many projects and training videos outside. The way you think, step by step approach and the reason for doing so, is so relatable and feels very natural. Awesome video, Thank you so much

[@saptarshidey7672]

There are a ton of EDA videos on KZbin. This is one of the best I have ever come across. You just nailed it, Rob.

[@robmulla]

Thanks so much!

[@Aarron-io3pm]

Hi Rob, this was super useful to me as a tired Excel veteran and python beginner. You explain and demonstrate everything so clearly, thank you

[@nigelkiernan1321]

This is a great refresher guide! Very nice coding style and I appreciate you using a simple Kaggle dataset to follow along. Great stuff - thanks!

[@silver_soul98]

I have tried plenty of tutorials by now. This is the most precise and to-the-point tutorial so far. Well done.

[@romanrodin5669]

Great channel! Very helpful for beginners and for those who' re digging deeper and moving forward into DS industry as myself! Thanks Rob!

[@jackgarn8392]

This is such an amazing guide! I’m new to data analysis and had limited python exposure and have taught myself most of these things so far by googling or just reading the pandas documentation. Watching someone familiar with the process do it all together was really helpful and gave me a lot of insights as to how I can improve my skills and workflow. Thank you so so much!

[@chrisosomo2856]

I can’t get enough of your videos, especially the very hands-on practical approach to learning. Your explanations are clear and easy to follow along with. Please make more of these types of videos. You are definitely makes a change and contributing to the KZbin knowledge pool. Thank you so much.

[@sa-pt3kf]

By far one of the most clear and concise ways of teaching in a computer science related field I've come across in a while. I'll be binging all your tutorials for sure!

[@robmulla]

Whoa. I love this feedback. I'll try my best to keep them coming.

[@adamvoltemar420]

This is one of the best content related to Data Analysis and Python/Pandas, I am really glad I found it! Thanks!

[@user-et7zv5rs3q]

this is absolutely amazing! Follow your video step by step actually make me more confident of my coding!

[@lindyhopwithliz]

Great video: informative and fun; easy to follow along. Helped me feel motivated to tackle more Python Pandas. Thanks so much!

[@itm1996]

Hands down one of the best tutorial I ever saw. Basic enough to follow as a newbie but demanding enough to be useful. ❤

[@SearchingforScraps]

Wow ! this is such a clean run through. You make it look so easy and easy to learn ! Thank you so much. This is giving me the confidence to finally start something on my own.

[@jcgdt94]

Thank you for sharing this, Rob! This is wonderful content. Keep up the good work. Cheers!

[@9jorge]

Thanks a lot, you explain concepts like no one, subscribed!

[@grandselenium296]

- import data Data understanding - filter columns by need - convert dtype of certain columns - rename columns - check isna in columns and dropna on row or column accordingly - locate duplicated rows in single or multiple columns - drop duplicated rows from dataset and reset index Data prep -univariate analysis of features - kde, histogram, box plot - use value counts to determine duplicates and unique values in feature - he creates bar plot for top 10 years introduced to highest # of coasters - he creates histogram to bin speeds of roller coaster and view their frequency distribution Feature understanding - scatterplot, pairplot, correlation, groupby - he creates scatterplot for speed and height with year based hue of points - he create pairplot to compare correlation between features, alongside hue from material type - creates a correlation heatmap for selected features Ask question - he uses groupby and query to create bar plot with sorted descending data on mean speed of roller coasters by location.

[@sheshankjoshi]

This is perfect for my interview tomorrow. I just needed a refresher on how to approach the problem, ask right questions and then come up with exploratory options. Thank You so much for this video

[@Eysh2009]

This video makes me feel glad to be alive. Great explanation, amazingly fast and on point. Thank you!

[@alikakavand3165]

It was fantastic. Every step you took was kind of amazing, specially the last bit where you visualized average coaster speed by location. Thanks.

[@user-ei9jd7pw4s]

Thank you for the video. You have combined all my knowledge into one comprehensible picture.

[@MCMMADDOGXCV]

This is GOLD! Thank you

[@iiN1GH7M4R3ii]

Great stuff man, thanks so much for this. Youre great at teaching beginners!!!!

[@wesleyweel8007]

The quality of your content is only surpassed by the ease at which it is to assimilate it, keep up the great content Rob, cheers!

[@robmulla]

Wow. Thanks for the positive feedback!

[@yjgg5882]

​@@robmulla bi L😅

[@yjgg5882]

🎉😊

[@Anarky35]

Great! Thanks a lot for this tuorial, so helpful for me as a beginner!

[@jmmj5018]

thank you so much, you have made my EDA analysis easier and faster. :) also, it's easy to digest as I go along with the data you are working. thanks a lot. you are helping a lot of analysts or people who wants to study in data analytics. Great video, keep them coming.

[@vishwathapa6626]

Pair-plot looked absolutely beautiful!

[@linux2350]

Thank you! that was very informative!

[@kapamagicman]

Awesome! Love the method chaining

[@jsplayground241]

You are the best coach. Thank you, sir!

[@olusolafatoye9691]

Great video. Clear explanation! You just earned a new subscriber

[@Dongnanjie]

Definitely amazing. Thank you so much, Rob!

[@kmvkmv3433]

Great stuff - thank you, Rob!

[@tomparatube6506]

I dabbled in this 4 years ago at EDX. This is a wonderful refresher. Thanks Rob!

[@aydanlopresti2879]

Clear and applicable to any type of analysis. Thank you

[@bradleyfrueh2761]

Thank you so much. I appreciate the work you put into your videos. It shows.

[@robmulla]

I really appreciate the feedback! Please share with anyone you think might also learn from it.

[@wahabamin6946]

Thanks Rob, you’re doing a great job for the data science community. Your videos here and on TikTok is helping me a lot in this journey. Thank you.

[@robmulla]

Love to hear that Wahab! Glad you learned something, and thanks for posting the feedback.

[@Rantalytics]

wow... thank you so much rob. I come from a frontend background but just began a data analytics bachelor at SJSU. I was trying to grasp at a high level what DA might look like as it pertains to conducting an explorative project. This tutorial completely cleared up those questions!

[@fabiolasilva6623]

Amazing, Thank you so much, the best tutorial!! :)

[@ricardorockthem3339]

Very well explained and quite nice difficulty level! Brilliant!

[@chrismagee5845]

This is the best reference guide. I always find myself rewatching this whenever I'm cleaning a dataset.

[@robmulla]

So glad you find it helpful.

[@Dean-nz9ld]

This is a brilliant video, helped alot thankyou!!

[@alexluvlol]

Thanks for making this tutorial! This is amazing

[@guilhermedesanctis]

Thanks for this lesson. It’s much valuable.

[@JHornsby89]

This is the second one of these I have now watched and coded along with! Genuinely awesome content, so precise and simple to follow. You make daunting tasks (for beginners getting into data) really accessible which is a sign of a great teacher!

[@robmulla]

Comments like this make me really happy that I made this video. So happy it helped you in your coding journey. Did you use the Kaggle notebook when you followed along?

[@mario1ua]

Really cool and looks so easy now, thank you Rob

[@anishkumaranjan]

Just completed it along with coding it all!

[@deneskalnoky7939]

This is a really good tutorial. I am new to Python and data analysis, and was completely lost. It was so hard to find a good, reliable source about it. This source just clarifies the basics for beginners so that I can start off with my own project.

[@siddhant0701]

This was a really nice tutorial, Rob. Had fun coding along, thanks for doing it :)

[@robmulla]

Thanks for watching and providing feedback. Feel free to share with anyone else you think might also learn from it.

[@sergiopellitero4136]

This video is.... PERFECT! Thanks ^^

[@muhammadfadliaktsar7172]

Thank you Rob for your explanation, before this it was hard for me to study and my mind just start pressured me of how to do EDA with Python language. And this video just open my mind to study it!

[@rr2b]

Very nice explanations , thank you so much!

[@aayaanhasnain5143]

Hey Rob, really admired the way you explained complicated topics with ease!! Looking forward to learning from you more :)

[@robmulla]

Thanks so much for that feedback. I really apprecaite it.

[@chess6802]

Perfect stuff what I love about this video is the simplicity and the clearness of the way you talk

[@robmulla]

I appreciate that! Thats how I learn best so it's also how I try to explain things.

[@chess6802]

@@robmulla your response reflect your both knowldge and wisdom please keep on 💞

[@ThePablo505]

amazing video, appreciate it a lot!

[@mschuer100]

Awesome video! Thanks for putting the time into this. Very helpful

[@robmulla]

Glad it was helpful! Share with a friend!

[@mschuer100]

@@robmulla I certainly will. Thanks

[@hardikacharya2664]

Great video. Look forward to your twitch streams!!

[@robmulla]

Thanks so much. Hope to see you during one of the twitch streams soon.

[@rdatta]

Excellent work and introduction. Very well done!

[@pdrcouto]

It has been great to refresh some topics and learn new ones. Thanks a lot :)

[@robmulla]

Thanks Pedro. So glad you’ve found these as a good refresher.

[@Jack-bs2mx]

you are the best teacher ever, I'm not good at English but I try to write down this sentence to show my appreciate to you. Im still waiting for new lesson using pandas for Data Analyst

[@walterpark8824]

well organized, concise, very helpful to get grounded in Pandas. my explorations will continue. Thanks!

[@robmulla]

Glad it helped! Thanks for watching. Share with anyone else you think might also learn from it.

[@panneerselvamposangu9929]

This is very helpful. Thank you, Rob!

[@adityagavali3158]

An absolute legend, thank you

[@thaanathaana4522]

Clear explanation for beginners.. will follow you more for tutorials

[@user-ki9vt2jc2t]

this is a wonderful video!

[@anuragarunedlabadkar8889]

Excellent explanation Rob. Learned a lot from this video. Keep it up.

[@walterpark8824]

Terrific introductory survey that answered so many of my questions, moving from SQL. Looks extremely efficient. Now, to plug into my data! Thanks.

[@robmulla]

Glad you liked it. Sql still has a place but when working with the data for EDA pandas can’t be beat.

[@shihaosun6861]

Thank you very much Rob for this wonderful walkthrough and explanation! Really Appreciate it!!!!

[@robmulla]

Thanks for the feedback! Glad to hear you learned something from it.

[@nunolopes3910]

This type of videos are amazing to follow, i am starting to use python for data analysis and i could not happier! Your channel is helping me alot, thank you!

[@robmulla]

So happy to hear this. Let me know what you would like to see in future videos.

[@nunolopes3910]

​@@robmulla One question i have is about the safety of using jupyter while working with company data. I am just starting to use jupyter and that is a big question that i'm sure other begginers would like to know to! Can you give your opinion on it? Thanks in advance

[@zhaozheng7704]

Excellent tutorial and immediately useful. Thank you!

[@robmulla]

Glad it was helpful! Thanks for watching Zhao.

[@terencelim9889]

Cheers bro~! M grateful for your tutorial =)

[@rrestituti]

#1 Data science youtuber!!! You made easy to understand the basic commands e sintaxes. Thank you a lot, Rob. 😉

[@robmulla]

Tell all your friends. 😆

[@lashlarue7924]

Agreed, this is the best Python content on the entire internet, hands down. I'm going to be carefully watching these videos over and over for a long time.

[@MrEdinaldolaroque]

Thank you for the tutorial, Rob!

[@robmulla]

Thanks for watching and commenting. Share it around if you want to.

[@soumyadrip]

Wow so many things are covered, its a great tutorial for getting started with EDA.

[@robmulla]

Thanks @somuSan. Glad you liked the tutorial. It took me waaaaay longer to film than I expected but I'm happy with the result. I hope more people in the future find it helpful.

[@adarshtiwari7395]

I have been grinding through your videos lately in preperation for my data science job and you have been an absolute blessing! Thanks a bunch!!

[@robmulla]

Wonderful! Glad I could help.

[@hmx21]

Hey Adarsh! Other than this what else are you learning that will help you in the data science job, I'm also preparing for the same but kinda new to data science so any guidance would be appreciated. Cheers!

[@adarshtiwari7395]

@@hmx21 Hi Hemang. I'm a fresher in data science as well. I started with Python and statistics. Then moved on to EDA followed by Machine Learning algorithms. I then made a few projects on ML. Also tools like SQL, Power BI, Excel are preferred

[@hmx21]

@@adarshtiwari7395 Hey Adarsh! Thnaks for the reply, I'm done with EDA and made a dashboard using Power BI, and don't know how much machine learning or SQL is required for the role as I've studied SQL in college and know how to work with joins,etc. Any tips or resources you'd like to share would be a great help. Also from where did you learn stats for ds, whenver I try to learn stats online I get overwhelmed with the magnitude of tutorials.

[@adarshtiwari7395]

@@hmx21 depends on what you're going for. If you are interested in a data analyst position, EDA through Power BI is great but if you want to go done the data scientist or machine learning route you need to be hands on with Python. EDA using python is much more nuanced as compared to visualisation tools like Power BI. SQL is essential in all contexts so it's a must. But whether you should study machine learning depends on your career goal.

[@AbdullahKhan-dl9lm]

Very crisp and concise explanation. Sometimes youtube videos can be better than paid courses.

[@user-tc9lk6iy2h]

Thank you!!! I learned a lot from your course.

[@robmulla]

Glad you found it helpful!!

[@jikarun]

Great Job Rob. I got vast knowledge about pandas from this video

[@edusheffer]

I'm impressed! your videos are excellent. Thanks, Rob

[@282OJK]

This is a great video. So helpful and informative. Thank you.

[@robmulla]

Glad it was helpful! Thanks for watching and tell your friends!

[@ilmankhairusidqi9146]

Your explanation is easy to understand and also show how the things work, ThankYou please make more videos about EDA in python Rob!!

[@swannschilling474]

Great content!! Thanks a lot!

[@alisonhenley2551]

Wow, what an informative fun tutorial. Thanks Rob!

[@robmulla]

Glad you learned from it and I appreciate the comment.

[@ishitasrivastava5923]

This EDA on Roller coaster data was literally a roller coaster for mind

[@NeerajKumardeaf]

Thank you so much. I am happy for your teaching about EDA with data analysis for pandas. I am clearly explaining to you. I can continue my hands-on experience for EDA

[@Davlet]

your content is pure gold! thank you

[@robmulla]

Glad you enjoy it! This comment is gold. 😎

[@bingolio]

Excellent and succint. THANKS!

[@robmulla]

Glad it was helpful! If you can, share it somewhere you think others might also learn from it too!

[@haydercorleoni6128]

excelent job i learned a lot from this video thnk you

[@alasdairmunro1953]

Really great video. Clear and well presented. Thank you.

[@robmulla]

Glad you enjoyed it!

[@user-ld8lc4ex4m]

Thank you so much

[@nyadokuamponsah04]

This is the best video I have watched so far. Thanksss!

[@robmulla]

Thanks so much!

[@ranahuzaifa147]

I was smiling at 39:23 . How easily you answered the question. Thanks for this amazing video tutorial.

[@robmulla]

My pleasure 😊 Glad you liked seeing it all come together at the end.

[@captaincal6447]

Thank you, Jim Halpert

[@zulucharlie5244]

Fantastic video, extremely informative, and very useful. Thank you.

[@robmulla]

So thankful that you found this helpful. Share with anyone else you think might also learn from it!

[@shoaibahmed5616]

I completed my certification in data science but could not figure out where to start. Thanks for such a detailed and easy to understand instructions with very useful commands. It helps a lot. Keep it up

[@hotbit7327]

Some of your other videos I found too fast paced, like about pandas mistakes, this one here has great content and also fantastic presentation. Thank you.

[@robmulla]

Thanks for the feedback. I’ve been experimenting with different editing styles so it’s nice to hear you prefer slower paced like this video. I’ll keep that in mind in the future.

[@generationgap416]

I already know Pandas pretty well, but I still learn from this dude.

[@leonrobinson2053]

Late to the party but this is really really good. Helps you dig in to the detail (rather than you thinking, how do I do what I'm thinking I need to do). This should be a template to use as it general enough for you to pick it up but specific enough with examples to be used elsewhere

[@naturfagstoff]

Way to go, Rob! Excellent!

[@robmulla]

Thanks for watching!