Data Analyst Portfolio Project (Exploratory Data Analysis With Python Pandas)

In this video, we take a look at an Exploratory Data Analysis (EDA) portfolio project within Python Pandas. Everything is coded within Jupyter Notebook and the data is sourced from Kaggle.

Python Libraries needed: Pandas, Seaborn

Interested in discussing a Data or AI project? Feel free to reach out via email or simply complete the contact form on my website.

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WHO AM I?
As a full-time data analyst/scientist at a fintech company specializing in combating fraud within underwriting and risk, I've transitioned from my background in Electrical Engineering to pursue my true passion: data. In this dynamic field, I've discovered a profound interest in leveraging data analytics to address complex challenges in the financial sector.

This YouTube channel serves as both a platform for sharing knowledge and a personal journey of continuous learning. With a commitment to growth, I aim to expand my skill set by publishing 2 to 3 new videos each week, delving into various aspects of data analytics/science and Artificial Intelligence. Join me on this exciting journey as we explore the endless possibilities of data together.

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[WarbossPepe]

You're a good man Ryan. Hope the run went well

[jkzhakom]

Fantastic video, Ryan. Thanks for sharing your knowledge with us.

[kokowin]

This is an easier way to remove USA from the event name = df2["Event name"] = df2["Event name"].str.replace("(USA)", " ")

[shailendra_kunwar]

Awesome work Ryan 🔥🔥🔥🔥
I have just watched it and I appreciate the effort that you put in for the video. I will be using this as my portfolio project.

[arun_jakhmola]

Hey Ryan, Greetings from India
I shadowed you for 3 days and completed the project in bits but glad I finished the whole video.
Loved the project and the way you taught it.

(Just a suggestion - Please go by the agenda for the project, so that we can have an outline in our minds of the key things that we as data analysts need to extract from the data.)

[yankoshuan]

great great content ! i am subscribing only on the condition you upload more and more in depth analysis using Python. Keep it up

[everywoman]

subscribed! great video. Thank you for this

[alexrosen]

Really useful project for learning especially since the datasample is included. Thanks a lot 🙏

[akshatalanjewar]

Its simply amazing ....i lke the way u teach and informative video

[michaelshepherdmunemo]

Great work. Thank you i was following hands on. # Subscribed_and_Liked

[Nighthunterm]

Was just doing some python learning to get some more knowledge and and I just found your channel. I heard you say you ran your marathon around UCF. I'm a fellow alumni as well from there haha. Go knights!

[emastehr]

Great Project. Could you develop a full project? Something that includes sql, python and then a visualization tool. That would be amazing

[charlieadleydog]

Hey Ryan, great video. Just wanted to ask how much RAM you suggest for these projects to be able to run quickly?

[dominiktokarski]

Liked, subscribed and commented for stats. Keep going :)

[Al-Ahdal]

In event_len column there are many row items with km, mi, how can we check all these to get the correct count, and how to extract numbers only. Should we be using REGEX for that?

[MiguelGracia-gd]

Hi, had a quick question!

at 17:27 would there be any downside to me using something like df[df['Event name'].str.contains('USA')] instead?

Thanks!

[athayaazaria]

hi, can I get the full syntax at minute 49.07, I can't see the continuation. I need it for my current school assignment, and this will help me a lot😊😊😊

[nlnl]

Thanks for the video! really helpful.
Do you think you can do a Data Scientist Portfolio Project(s) series? I'm sure you'll find a lot of people interested in that (including me haha)!

[rahulpal_dsml]

Not subscribing you would be a sin, after going through this beautiful and informative video!. keep going!

[chalamohamed]

Hello Ryan,

Thanks for sharing your skills.

I would like to understand why you have dropped Athlethe Club and Country ?
I thinks it would be better if you had dropped rows whose have an empty value than you can modify the type of column.