ksliney commented 6 years ago

Please complete all of the following sections, or the ghost of Joseph Pulitzer will spookily dance around your issue! A completed version of this template can be found at https://github.com/jsoma/data-studio-projects/issues/1

Pitch

Summary

Critics argue Obama relied too heavily on the National Security Council for operational control of foreign policy at the expense of State and Department of Defense participation. Others argue this isn't a critique of the Obama administration so much as it is a response shared by multiple administrations to a need for flexibility to respond to a complex global security environment.

So, if the NSC is growing in both size and influence, who staffs the NSC? What is their background and expertise? What are some of the ways that these people get selected for these jobs?

For more context: https://www.defenseone.com/ideas/2016/04/whats-wrong-obamas-national-security-council/127802/ https://www.washingtonpost.com/world/national-security/how-the-obama-white-house-runs-foreign-policy/2015/08/04/2befb960-2fd7-11e5-8353-1215475949f4_story.html

Details

Possible headline(s): I reverse engineered Obama's national security team. Here's what the data shows.

Data set(s): *I've compiled gender and education data on 417 officials using Linkedin. Using a Selenium-based scraper, I will continue to dig for details on their path to the NSC.

Code repository: https://github.com/ksliney/data-studio/tree/master/code/02-Obama_NSC

Possible problems/fears/questions: -TIME

Work so far

I realize this is still ugly, but...here's a basic graph:

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

jsoma commented 6 years ago

You should post some legit matplotlib graphics with your pitch, even if they're terrible or useless, just so you can confirm that your data is actually manageable and solid (I know your collected it yourself, but it's good practice!)

ksliney commented 6 years ago

UPDATE: UGLY charts to prove this topic is semi-possible (ignore design and colors at this point)

Any changes in direction or topic?

Not yet.

Problems/Questions

Ideal scenario: (1) building a scraper for Linkedin Recruiter (2) figuring out who came up as a lawyer, vs. military, vs. PMF. (3) Figure out length of time served. (4)Figuring out when served (many came on during lame duck period) Problems: Verifying the total number of staffers that served on Obama's NSC (can't find an official source to compare against who I've found on LinkedIn)

[X] I have included my visuals
[X ] I have filled out the sections above
[ ] I have been updating my DIARY.md with details about my process
[X ] I have uploaded/updated any Jupyter Notebooks or other datasets into my code repository

playfairbot commented 6 years ago

Hi! I'm a little robot, checking in on your project.

You need some feedback, let me summon @zle2105, @cfelke, @collleenwang for you

It looks like we need to fix up your your update a little bit! Edit it by clicking the pencil in the top right-hand corner. It requires:

New, updated content for your project
The checklist (be sure you're using the template!)

Maybe you just didn't use the template? If not, edit your comment, cut and paste the template in, and then fill it out.

cfelke commented 6 years ago

I like your choice of topic; looking at your previous works I really love that you're addressing the female angle/representation in various fields. You go, woman!

Regarding your first graph, it would be more helpful, if you display the bars in descending order, so I a as a reader can see for myself what's going on at first glance. Moreover, I'd move the title further to the center and show some x grid lines in the background for orientation, since you're displaying a couple of bars/values.

Regarding your second graph, I'd ditch the grid lines and display the values in or next to the end of your bars, you only have two. And I know everyone associates women with pink and men with blue, but people can adapt and certainly be challenged. I personally would prefer a change of colour. Speaking of, I'd suggest a play with colours overall, white and grey are plain/boring, especially when you're doing such a cool project.

jsoma commented 6 years ago

I recommend fixing up your update with the template so we don't make the robot work so hard.

I agree with @cfelke about the colors - pink hasn't always been for women, and even though it's easy for people to recognize what you're talking about if you use that, I think socially it's really fallen out of favor.
If you did go with the grid line, you'd probably want to make it lighter and push it behind the data with ax.set_axisbelow(True)
If you don't want to change up the titles of the schools later, using something like df.school.replace("The Johns Hopkins University blah blah long title", "Johns Hopkins", inplace=True to make things fit a bit nicer. Even if there's a technical name for something, the common name is probably better to make things fit more nicely!
Oddly, left-aligning label names on a horizontal bar graph can make things look cleaner. I think Sarah kind of talked about this with "jagged edges?"

If you still had long long school names, you could also align the titles on top of the bars (not sure how to do this in matplotlib offhand, you'd probably want to do this manually in illustrator by moving all of the labels at the same time).

collleenwang commented 6 years ago

I like your topic, though it's simple but clear. I think the most important thing for displaying charts is to show people insights or findings.

zle2105 commented 6 years ago

For the second graph, I would add the values into the bar graph since you have the space.

For the first graph, you might be able to save space by putting the names of the schools in the bars, instead of on the X-Axis. The graph might also look much more streamlined.

troboukis commented 6 years ago

also you can use \n to break the university into two lines. Is this project finished? Would be interesting to see the final graphs.

jsoma / data-studio-projects

Still curious about the make up of Obama's NSC? Yeah, me too. #189