open-austin / austin-park-equity

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https://www.open-austin.org/austin-park-equity/
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Replace existing Demographic Need layer with new data #43

Open mateoclarke opened 9 years ago

mateoclarke commented 9 years ago

This page needs work

mateoclarke commented 9 years ago

Then, step 2 is figuring out how to include the data from this layer onto the landing page map

kyoder commented 9 years ago

Incorporating our park data into a format similar to that of the Accessibility Score website we saw in the Census demo would be one way to include the demographic data to our landing page.

http://website-mnhomefinder.rhcloud.com/accessibilityscore/evaluation/explore.action

mateoclarke commented 9 years ago

Yeah, I really liked those radar (or spider) charts too. Digging into the source of their project, it looks like they used Chart.js. Looks like a pretty easy library to plug in, or we could try with d3 if we need something more custom. (Here's a d3 radar chart example)

mateoclarke commented 9 years ago

@kyoder, I've started digging into the census tract data you uploaded. Thanks for merging all this Census Data into the tract objects.

Can you share which of these properties are most important and what their names mean? And in what units they are measured?

And it looks like you already did some calculations to come up with some scores for density, poverty, parks, youth, seniors, and health. What did you do to arrive at these numbers and how should we interpret them? Is it a ranking of by all 202 census tracts?

Finally, if we want to follow the Accessibility Score app model, we would need to get our scores on a 0-100 scale.

Below is a sample of data from one Census Tract...

properties values
OBJECTID 175
STATEFP 48
COUNTYFP 453
TRACTCE 002212
GEOID 48453002212
NAME 22.12
totalCivil 563
uninsuredN 90
totalHousi 161
occupiedHo 161
percentOcc 100
vacantHous 0
percentVac 0
ownerOccup 144
percentOwn 89.4
renterOccu 17
percentRen 10.6
totalHouse 161
totalFamil 145
medIncHous 50313
medIncFam 55703
moe_total 157
est__inHou 181
est_under3 30
est_3_4 10
est_5 31
est_6_8 3
est_9_11 38
est_12_14 21
est_15_17 48
estgroup 0
Shape_Leng 0.21945908268
Shape_Area 0.0028237841
popTotal 563
popDensity 48.4335228399
tractArea 7439.47536388
uninsuredP 16
poverty 0
ageTotal 563
age65total 28
over65 0.04973357016
un18Total 181
under18 0.3214920071
densitySCR 0
healthSCR 4
povertySCR 0
seniorSCR 3
youthSCR 9
parkSCR 16
kyoder commented 9 years ago

We probably need to revisit the logic. I'm sorry the field names are so messy.

Important fields:

STATEFP = state FIP code COUNTYFP = county FIP code TRACTCE = census tract id GEOID = unique census tract id that is a combination of STATEFP, COUNTYFP, and TRACTCE NAME = name of census Tract

popTotal = population total popDensity = population density (calculated from popTotal/tractArea) used for score tractArea = area of the census tract calculated in square miles uninsuredP = percent uninsured used for score poverty = percent below poverty used for score ageTotal = total from the census table, Sex and Age age65total = number from the census table, Sex and Age, that are over 65 over65 = percent over 65 (calculated age65total/ageTotal) used for score un18Total = total number under 18 from census table, Population under 18 under18 = percent under 18 (calculated un18Total/popTotal) *used for score densitySCR = population density score healthSCR = health insurance coverage score povertySCR = below poverty score seniorSCR = population over 65 score youthSCR = population under 18 score parkSCR = SUM of all other score fields

See this Park Score breakdown for more details on the classifications and source data https://docs.google.com/spreadsheets/d/1YzCqHEBSD9saystcNoUkGIMcaqOKt2oZsJSVtIVS_Y8/edit?usp=sharing

kyoder commented 9 years ago

Discussed tonight at open austin wtih @wilsaj and john