Data Skills Class

The states with the most DUI arrests per 100,000 residents are, more often than not, sparsely populated.  Wyoming, Alaska, and North Dakota are not much of a surprise, but Wisconsin's penchant for drinking and driving is something I've heard of while never seeing empirical evidence.  

We want to gather historic Census data, from 1850 to this day, from  8-10 different migrant populations, and try to answer some things:

- Why did they come to NYC? (War, diseases, economic opportunity)

- Where did they settle in the city and why (it would be interesting to show, for instance, when Little Italy became an Italian neighborhood)

- Did they move after? And why?

The big driver of the story would be something like an animated GIF of a NYC map that would show shapes of migrant populations, color-coded for the country of origin. To accompany that, a timeline showing some milestones of migration movements. And, lastly, some simpler line graphs with the different waves for different groups (tentatively: Italians, Irish, Russians, Chinese, Mexicans, Germans, Dominican Repubic, Jamaica).

Besides making a visually interesting (and shareable) GIF, the story will be interesting to show and verify what neighborhoods are being gentrified.

DATA SETS:

http://www.city-data.com/states/New-York-Migration.html

(City Data on waves of migration to NYC)

http://www.gothamgazette.com/index.php/city/2738-immigrant-city

The 2014 State New Economy Index is comprehensive report on the American economy and in one section examines the energy production/consumption of each state: The Clean Energy Economy.

One of my goals with my community, African-Americans suffering from depression, is to not only build a safe forum for discussing mental health, but to also provide resources for seeking treatment. After a couple of hours (and yes, I do mean hours) I finally found some useful, relevant, mappable data.

While on the Substance Abuse & Mental Health Services Administration’s  (SAMHSA’s) website, probing for a useful dataset file, I discovered a treatment facility locator. The locator is updated weekly and lists, with several exceptions, most public, private for-profit, and non-profit State-licensed or nationally accredited mental health facilities around the nation. Another plus? The locator allows you to download a real-time .csv file of the records. And even better, you’re able to filter the facility locator data, which is perfect when searching for specific types of facilities (e.g. a Public/government sponsored facility that accepts Medicaid) or services for a specific demographic (e.g. treatment for adolescents or LGBTQ patients). A useful resource for my community? You bet.

I will use the data to generate a map of shapes and will then merge it with the US State shapefile in CardoBD, listing facilities per state. I'll most likely be using the common field “state.” If time permits, I'd like to also try generating a NY-based map using a NYS zip code shapefile.

Using the excel data set from the 2014 State New Economy Index I'm mapping the clean energy economy in the U.S., which is calculated as a state's clean energy consumption as an overall proportion of energy consumption. 

My project is focusing on how Black trans, LGB and women fit into the Black Twitter activism and millennial community. And although I'm compiling data on these social issues, I'm also compiling on the Black Lives Movement (sparked by Twitter activism) and the issues it's currently focusing on: Ferguson, racial profiling, police brutality and endangerment of Black male lives.

The data I'm mapping will show the location in major Missouri cities/counties where Black folks were stopped by police compared to white folks. I'm going to use a Missouri-shaped map to represent the geographical location. Also, I'm going to use data shaping with the colors of blue (Black folks) and red (White folks) to show the percentage of Black folks stopped compared their White counterparts. 

Another option will be to show it through a radiant of color -- comparing the Black population percentage simply to the number of Black folks stopped.

Or is there a way to map both together -- Black versus White stops by police and the population of Black and White folks in major Missouri counties?

Hmm...

Actually, I realized it was impossibly hard to map racial profiling as I needed location to prevalent in the data. 

After a tiresome search, I decided to map general data about Internet usage across the United States. The data shows the amount of Internet usage anywhere within each state. Internet Usage was most prevalent in California and Texas.

Brazilian government is blaming climate change and the severe drought for the current water shortage that people from all over the country – particularly in the rich Sao Paulo state – are experiencing. But some environmentalists have pointed out that we know that we needed a better water infrastructure for years. And some parts of the state needed those fixes more badly than others. 

Luckily, Brazilian Federal Water Agency (ANA) released a study in 2009 showing their assessment in each municipality. In Sao Paulo state, most of them were marked as "satisfactory water supply", but big cities like the capital, Sao Paulo, received a "requires extension of the current system" mark, and some even "requires a new water source".

My idea is to plot in a map this information, color-coding where, in 2009, we knew that the situation was going to get bad. I could insert more data-points later (like how was the situation 5 years after, or how much money was invested), but this single map would be sufficient to point that we could have acted way sooner to prevent the calamity.

For my mapping project, I decided to not only work with the Irish community that is part of my greater project, but gain a scope of all the ancestries that comprises the states of the Mid-Atlantic.  I'd be using shapes for this undertaking.  Additionally my data comes from the ACS 2013 estimates, and I'll look at specific ethnicity groups in specific states by using Refine.  Additionally, I'd like to use this to figure out what percentages of groups from other countries make up the largest percentages of state populations.