[Project] Where Millennials Spend Money (It's Not Avocados)

[linleysanders]

Pitch

Summary

I'm hoping to create a visually-focused infographic that explores new data (August 2018) released by the Bureau of Labor Statistics on the spending patterns of Millenials and earlier generations. The generation-to-generation changes can showcase societal shifts in demographics and lifestyle preferences. I'd like for this to not echo the dramatic headlines like "How Millennial Spending Habits Could Spark the Next Economic Crisis" or "Why Millennials Can't Afford a House," but just focus on the changes and what small takeaways exist in this data.

Here are a few pieces of inspiration:

Details

Possible headline(s): How Millennials Spend Money Compared to Older Generations

Data set(s): BLS Data: https://www.bls.gov/opub/ted/2018/spending-patterns-of-millenials-and-earlier-generations-in-2016.htm

Code repository:

• Scraping Code for Bureau of Labor Statistics: https://github.com/linleysanders/data-studio/blob/master/Code/07-where-millennials-spend/Scraping%20Bureau%20of%20Labor%20Statistics.ipynb -Code for Analysis: https://github.com/linleysanders/data-studio/blob/master/Code/07-where-millennials-spend/Millennial%20Spending%20Data.ipynb

Possible problems/fears/questions: Making this perspective fresh—I know the analysis of Millennial is a little trite, but I'm excited about this dataset regardless.

Work so far

Webscraping—so fun! I got my dataset and am beginning the initial analysis. I'm planning to zero in on around three topics mentioned in the dataset, like home-ownership, eating out costs, transportation... Stay tuned.

Checklist

This checklist must be completed before you submit your draft.

• [x] I have already spent time with my data set, opening it, exploring it, etc
• [ ] I have created a "DIARY.md" file to save links and list all of the terrible, no good problems I come across
• [x] My issue links to my data set(s)
• [x] My issue links to my code repository
• [x] My issue explains what I'd like to explore in the data set
• [x] My issue includes images - either inspiration or what I've done so far

[linleysanders]

Dropping in some rough and early analysis here. Not adding too much subhead context because I'm going to try to visualize bigger takeaways later:

[sarahslo]

how are these data organized?!! by the way you got the data! remember, you must always have an organizing principle! start by sorting the data to see what most and least is. look for superlatives.

instead of bars can you do a slope chart? you can keep your nice colors then and we'll be able to see faster how each age chooses and compares to each other,

[linleysanders]

That's a really interesting idea—I guess at the face value I'm worried it will be difficult to read, but I'm up for messing around with it. Here is an initial idea. Not sure why the numbers on the bottom are the Index rather than the two categories... Will need to mess around with that tomorrow. It should just be either 11 or 12 (Buy a Used Car vs. Buy a New Car).

[ksliney]

Hey Linley, Is there a way to look at millennials living in expensive regions vs. non expensive ones? So, say, New York City vs. Kansas City? I feel like location is so crucial to how we spend.

[linleysanders]

Hey @ksliney—unfortunately the BLS doesn't release that level of data, but it's definitely an interesting idea.

[jsoma]

I like @sarahslo's slope graph thought - it would be a really easy way to highlight the difference between two different generations. What you'd be looking to do is each line represents one type of cost, and, for example, on the left you'd have boomers and on the right you'd have millenials.

One line would be telephone, one line would be car, etc. So you'd see a dot way down low on the left about rent $$, and then a line would blast upwards at a terrifying angle, to come to rest at "millenials spent infinite amounts of money on rent."

I really thought some of these numbers were going to be really different, but they're really remarkably similar! Which might actually be to your benefit - you can highlight a few same/not same things - like greatest gen and millenials rent a lot, why is that? millenials buy used cars, why is that?

Pairwise comparisons are probably best, unless there are trends over time or a strong outlier where you can graph all of the generations and highlight millenials being Very Diferent.

While we're on the topic, avocados at my formerly cheap avocado place are now $2/each instead of overly ripe ones being 2/$1 like they were a month ago and I'm pretty unhappy about it.

[linleysanders]

@jsoma do you think it's best to compare two generations across all categories as opposed to all of them on one category? I'm trying to sketch out on a piece of paper so I can hopefully get caught up, but I think I'm getting torn between directions.

[sarahslo]

Use color to make meaning! If you made 'the older you are, the darker the color' on the other chart (and lost your gray background) we could see the pattern better. Also will you give us age ranges on those names, or year born.

to answer your question above, i'd look at the data -- see if there is something that stands out. do all generations, by category. then, you'll get the answer for the narrow category. if 2 stand out what you can do is USE COLOR TO MAKE MEANING!

make all the generations that are not important one color, and put the label of the generation by the rule, and then make the two generations you want us to see another bright color. draw our eye to the point.

[linleysanders]

[linleysanders]

^^ Per Sarah's feedback, still working on colors

[linleysanders]

[sarahslo]

i get it. success. except. my only wish here still, is you gave me the age ranges or birth dates for the generations. i have zero idea who some of these generations are. like the greatest? so perhaps i don't 100% get it.

add that for me and you're there.