How to Do Data Exploration (step-by-step tutorial on real-life dataset)

👇Learn how to complete your first real-world data science project
Hands-on Data Science course

In this video we learn how to explore a real-life dataset from NYC using Python and Pandas. We will dive deep into the data and find out potential problems, issues to fix and extract insights from it.

00:00 Welcome
00:34 Some notes on data exploration
01:15 Dataset explanations
05:26 First look into our dataset
06:58 Understanding columns
09:22 Filtering out the unnecessary columns
11:45 Missing value check
12:49 Numerical values check
15:08 Outliers check
19:57 Categorical values check
24:57 Explore distribution of binary columns
26:40 Summary

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[prinjeshshah]

I was searching for a video where someone explains their reasoning in data exploration from last 15 days. This video has now become bookmark for my future data exploration works. Thank you very much.

[AlissaFernelius]

Honestly your the most honest and humble trader on YouTube!!

[Sir_Lancelotz]

I didn't finish the video, and now I really understand why this is important, good job, excellent video!

[lara-rosetadman]

Hi Misra, this video was so helpful! I'm starting my master's in Data Science this September and you've honestly been such a role model for me! Thank you and keep up the great work!

[sergiopellitero]

This is the kind of videos that I am looking for. Let's see if it is interesting.

[stephanielynn]

Found you as I start to work on a project for my MS in analytics! This has definitely helped me make better progress than before.

[arindam_maji]

a definite bookmark video for data analysts

[ExtraKanin]

Hi Misra. I'm 18 minutes into the video and I'm still able to follow. thank you for this! Most of the articles I see on Google just jump straight into data cleaning and I don't even know how they detected the data errors they're trying to clean in the first place.

[djmd]

Just wanted to let you know that your videos breathed new life into my Udacity Nanodegree experience. I have really been stalling on the last two classes, but this video and the cleaning one (along with others) were so much easier to watch and understand than the Udacity instruction provided in the course. Thank you!

[lianyan]

Really like how you have explained the thought process when comes to data understand and exploration. Learnt a lot!

[swadhikarc]

Very useful indeed.. learnt how to think like a data analyst as a beginner

[mmikeves]

I appreciate your explanation even though i was looking for something else,

[ramvenkatachalam]

Wow . Great DataSet . just what i was looking for . I was searching for a video where someone explains all important things on datascience . This video has now become bookmark for my future data exploration works. Thank you very much Misra . ur channel is the best in the world.

[santdayalverma]

Hi Misra, I love your videos. The way you explain topics in a simple manner is really helpful. Thank you so much!

[SFW]

Thank you so much for making this video! I'm just starting out with using python for data analysis and this video is so informative and inspiring. :)

[gunhild]

Great video! Very informative and helpful 😃 I would love if you can upload more videos like this where you go through the steps of exploratory data analysis. I love that you really bring up every little thing of how it could be when doing EDA. Like for example where you talked about the data explanation and how it could be in the real life. Just the thing about documentation of the dataset fields and how it sometimes is not so obvious and that you therefore need to talk to someone responsible etcetera etcetera. This kind of information that you brought up helps me to picture how I could be. Maybe it's silly but a simple thing like helped me big time. Overall, a perfect how-to-do-video. More videos like this would be appreciated! 😄

[Naturebykittu]

you explained so well. Just awesome. Thank you..

[SimaManiyevaDEV]

Thank you so much! I love your explanation.

[Olumasei]

You teach better than my MSc lecturers.
Thank you

[smartlymade]

thank you for this video! i was very overwhelmed by a dataset that i was looking at and didn't know how to start. great video