Economic Data Analysis Project with Python Pandas - Data scraping, cleaning and exploration!

In this video kaggle grandmaster Rob Mulla takes you through an economic data analysis project with python pandas. We walk through the process of pulling down the data for different economic indicators, cleaning and joining the data. Using the Fred api you can pull up to date data and compare, analyze and explore.

Timeline:
00:00 Intro
01:05 API Setup
06:26 Search Economic Indicators
10:35 Pull Economic Data
13:37 Joining Indicators
25:59 Plotting with Plotly
27:27 Bar Chart of Unemployment
36:50 Unemployment vs Participation

My other videos:

#python #pandas #datascience

[gustavojuantorena]

Great conten! I didn't know the "twinx" method. It would be nice if you can make tutorials about advanced data visualization in Python.

[SmithHayward]

I've done basic data analysis manually in Excel for a long time, but these tools are insane. Your way of explaining things step by step is going to help me get some of these more modern tools into my toolkit and supercharge my productivity and marketability as I look for my next job.

[BKSDA]

Rob you are a legend! This is content worth while ! Thank you for everything you do. I am learning Python for Data Analytics and your tutorials are great! They also apply for beginner level and cover different aspects and ways of using pandas and other libraries. Thank you !

[walterpark]

An inspiring tour de force with a very satisfying outcome. A hundred years ago the data didn’t exist; 25 years ago the data wasn’t in electronic form in one place; 15 years ago it would have taken a team weeks if not months to pull this all together and then format graphs; yesterday I had no idea it could now all be accomplished in much less than an hour. Now I’ll spend the next month or two going through but by bit, learning how to do this with my data. Thanks!

[shivamzala]

The way you explain the entire walkthrough is just brilliant. You have the skill that many posses but your way is really unique like a statistical anomaly!

[jonbig]

I've watched A LOT of data science tutorials and these are extremely well done. Thanks for the great content!

[dodgerboi]

I just want to thank you for what you do. Some people are special in the way they convey information and teach and you just have it. You are going to help me succeed in this field! Keep it up man.

[olubunmiadeniji]

Wow! This is awesome. I am contemplating doing PhD in Economics and this a great introduction to what I should expect. Thanks for your efforts.

[wilsonsantosmarrola]

It's great to see how others ppl work. There's always something to learn. In in my case I'm learning everything that you showed in this video. Thank you so much for doing it

[Charlay_Charlay]

Thank you Rob. This was definitely an interesting walkthrough utilizing Fredapi for data exploration. I took this course to get an idea of what i can do with pandas for data exploration and you definitely delivered. Once again thanks.

[gisleberge]

Great content and pace you did it...particularly like what you did from "plot with plotly" and beyond, the data wrangling. Thanks for sharing.

[dogden]

This is great! Seems like I learn some new pandas tricks in every one of your videos. Thanks dude!

[sjrigatti]

Wow. Great video. Awesome to see the iterative process you use (and hard to take notes on it, so thanks for the links).

[louisvuittondonvg]

Dude you're so clean at this. Unbelievable

[priyadoesdatascience]

Thank you. I do use a lot of financial data at my work. This is going to help a lot. The visualization techniques are great to adopt!

[sadgasm]

only with making a dataframe with the entire unemployment of the US by State, would have taken me at least 5hrs or even more, this is huge help for me and my future projects... you are awesome, please keep up the good content. greetings form Colombia.

[tyroneogarrojr.]

Great content and incredibly insightful and transparent

[iiNGHMRii]

Fascinating stuff man, thank you for this!

[philipomelo]

Thanks @Rob Mulla, this video is very informative and motivating.

[badguyvon]

Great Video! I learned a lot of tips and tricks from this analysis!