def load_data(self, request, bounds, **args):
resp = self._base_response(bounds)
if "census-tract" in bounds:
tract = bounds["census-tract"][0]
results = Tract.objects.filter(
state=tract['metadata']['STATEFP10'],
county=tract['metadata']['COUNTYFP10'],
tract=tract['metadata']['TRACTCE10'])
if results:
t = results[0]
# median value
if t.B25077_001E:
resp["data"].update({
"owned": {
"median_value": dec2curr(t.B25077_001E, whole=True),
}
})
# rental pct
try:
rental_pct = t.B25003_003E / (t.B25003_002E + t.B25003_003E)
resp["data"].update({
"rentals": {
"median_cost": dec2curr(t.B25058_001E, whole=True),
"pct": dec2pct(rental_pct, whole=True),
"svg": viz.svg_piechart(rental_pct, 50, 50, 35)
}
})
except:
pass
# transportation
trans_total = t.B08301_001E
if trans_total:
resp["data"].update({
"transport": {
"total": dec2num(trans_total, whole=True),
"auto_pct": dec2num((t.B08301_002E / trans_total) * 100, whole=True),
"public_pct": dec2num((t.B08301_010E / trans_total) * 100, whole=True),
"bike_pct": dec2num((t.B08301_018E / trans_total) * 100, whole=True),
"walk_pct": dec2num((t.B08301_019E / trans_total) * 100, whole=True),
}
})
return resp
def test_dec2num(self):
d = Decimal("23.235235")
s = formatting.dec2num(d)
self.assertEqual(s, "23.24")
d = Decimal("23456.308")
s = formatting.dec2num(d)
self.assertEqual(s, "23,456.31")
s = formatting.dec2num(d, whole=True)
self.assertEqual(s, "23,456")
def load_data(self, request, bounds, **args):
resp = self._base_response(bounds)
resp["data"] = {}
if "census-tract" in bounds:
tract = bounds["census-tract"][0]
# nhgis
results = NHGISTract.objects.filter(
state=tract["metadata"]["STATEFP10"],
county=tract["metadata"]["COUNTYFP10"],
tract=tract["metadata"]["TRACTCE10"],
)
if results:
years = {"1970": None, "1980": None, "1990": None, "2000": None, "2010": None}
for res in results:
years[res.year] = res.units
housing_data = {
"current": dec2num(years["2010"], whole=True),
"current_before": ("%i" % (years["2010"] - 1))[-1],
"current_after": ("%i" % (years["2010"] + 1))[-1],
"history": years,
}
if len([v for v in years.values() if v]) > 2:
housing_data["history_svg"] = viz.svg_housinghistory(years)
resp["data"].update({"housing": housing_data})
# census
results = Tract.objects.filter(
state=tract["metadata"]["STATEFP10"],
county=tract["metadata"]["COUNTYFP10"],
tract=tract["metadata"]["TRACTCE10"],
)
if results:
t = results[0]
if t.B25035_001E:
thisyear = datetime.datetime.utcnow().year
resp["data"].update(
{"median_year": "%d" % t.B25035_001E, "median_home_age": "%d" % (thisyear - t.B25035_001E)}
)
return resp
def load_data(self, request, bounds, **args):
resp = self._base_response(bounds)
if "census-tract" in bounds:
tract = bounds["census-tract"][0]
results = Tract.objects.filter(
state=tract["metadata"]["STATEFP10"],
county=tract["metadata"]["COUNTYFP10"],
tract=tract["metadata"]["TRACTCE10"],
)
if results:
t = results[0]
# ethnicity
# top_ancestry = max(
# ((k, getattr(t, k, None)) for k in ("B04003_%03dE" % i for i in range(2, 108))),
# key=lambda x: x[1]
# )
# resp["data"].update({
# "ethnicity": {
# "total": dec2num(top_ancestry[1], whole=True),
# "pct": dec2pct(top_ancestry[1] / t.B04003_001E),
# "name": CENSUS_FIELDS[top_ancestry[0]],
# },
# })
# update avarage age in years, months
(years, months) = utils.age2ym(t.B01002_001E)
if years is not None and months is not None:
resp["data"].update({"average_age": {"years": years, "months": months}})
# relative age distribution
total = t.B01001_001E
males = []
females = []
for i in range(3, 26):
males.append(getattr(t, "B01001_%03dE" % i))
females.append(getattr(t, "B01001_%03dE" % (i + 24)))
total = max([max(males), max(females)])
if total:
males = [dec2pct(m / total, whole=True) for m in males]
females = [dec2pct(f / total, whole=True) for f in females]
resp["data"].update({"age_distribution": {"female": females, "male": males}})
# under five years of age
if t.B11005_001E:
resp["data"].update(
{
"under_five": {
"total": dec2num(t.B01001_003E + t.B01001_027E, whole=True),
"per_household": dec2num((t.B01001_003E + t.B01001_027E) / t.B11005_001E),
"households": dec2num(t.B11005_001E, whole=True),
}
}
)
# gender
if t.B01001_001E:
resp["data"].update(
{
"gender": {
"male_pct": dec2pct(t.B01001_002E / t.B01001_001E),
"female_pct": dec2pct(t.B01001_026E / t.B01001_001E),
}
}
)
# update rest of the stuff
if t.B19001_001E:
resp["data"].update(
{
"average_household_income": {
"total": dec2curr(t.B19013_001E),
"pct_gt_100k": dec2pct(
(t.B19001_014E + t.B19001_015E + t.B19001_016E + t.B19001_017E) / t.B19001_001E
),
"pct_60k_100k": dec2pct((t.B19001_012E + t.B19001_013E) / t.B19001_001E),
"pct_30k_60k": dec2pct(
(t.B19001_007E + t.B19001_008E + t.B19001_009E + t.B19001_010E + t.B19001_011E)
/ t.B19001_001E
),
"pct_10k_30k": dec2pct(
(t.B19001_003E + t.B19001_004E + t.B19001_005E + t.B19001_006E) / t.B19001_001E
),
"pct_lt_10k": dec2pct((t.B19001_002E) / t.B19001_001E),
}
}
)
if "census-zcta" in bounds:
zcta = bounds["census-zcta"][0]
try:
c = Contribution.objects.get(zipcode=zcta["metadata"]["ZCTA5CE10"])
total = c.democrats + c.republicans
resp["data"].update(
{
"contributions": {
"r": dec2curr(c.republicans, whole=True),
"r_pct": dec2pct(c.republicans / total),
"r_raw": int(c.republicans),
"d": dec2curr(c.democrats, whole=True),
"d_pct": dec2pct(c.democrats / total),
"d_raw": int(c.democrats),
}
}
)
except:
pass # eh, don't really care
return resp
def load_data(self, request, bounds, **args):
resp = self._base_response(bounds)
resp['data'] = {}
if "census-tract" in bounds:
tract = bounds["census-tract"][0]
# nhgis
results = NHGISTract.objects.filter(
state=tract['metadata']['STATEFP10'],
county=tract['metadata']['COUNTYFP10'],
tract=tract['metadata']['TRACTCE10'])
if results:
years = {
'1970': None,
'1980': None,
'1990': None,
'2000': None,
'2010': None,
}
for res in results:
years[res.year] = res.units
housing_data = {
'current': dec2num(years['2010'], whole=True),
'current_before': ("%i" % (years['2010'] - 1))[-1],
'current_after': ("%i" % (years['2010'] + 1))[-1],
'history': years,
}
if len([v for v in years.values() if v]) > 2:
housing_data['history_svg'] = viz.svg_housinghistory(years)
resp['data'].update({
'housing': housing_data,
})
# census
results = Tract.objects.filter(
state=tract['metadata']['STATEFP10'],
county=tract['metadata']['COUNTYFP10'],
tract=tract['metadata']['TRACTCE10'])
if results:
t = results[0]
if t.B25035_001E:
thisyear = datetime.datetime.utcnow().year
resp['data'].update({
'median_year':
"%d" % t.B25035_001E,
'median_home_age':
"%d" % (thisyear - t.B25035_001E),
})
return resp
def load_data(self, request, bounds, **args):
resp = self._base_response(bounds)
if "census-tract" in bounds:
tract = bounds["census-tract"][0]
results = Tract.objects.filter(
state=tract['metadata']['STATEFP10'],
county=tract['metadata']['COUNTYFP10'],
tract=tract['metadata']['TRACTCE10'])
if results:
t = results[0]
# median value
if t.B25077_001E:
resp["data"].update({
"owned": {
"median_value": dec2curr(t.B25077_001E,
whole=True),
}
})
# rental pct
try:
rental_pct = t.B25003_003E / (t.B25003_002E +
t.B25003_003E)
resp["data"].update({
"rentals": {
"median_cost": dec2curr(t.B25058_001E, whole=True),
"pct": dec2pct(rental_pct, whole=True),
"svg": viz.svg_piechart(rental_pct, 50, 50, 35)
}
})
except:
pass
# transportation
trans_total = t.B08301_001E
if trans_total:
resp["data"].update({
"transport": {
"total":
dec2num(trans_total, whole=True),
"auto_pct":
dec2num((t.B08301_002E / trans_total) * 100,
whole=True),
"public_pct":
dec2num((t.B08301_010E / trans_total) * 100,
whole=True),
"bike_pct":
dec2num((t.B08301_018E / trans_total) * 100,
whole=True),
"walk_pct":
dec2num((t.B08301_019E / trans_total) * 100,
whole=True),
}
})
return resp
def load_data(self, request, bounds, **args):
resp = self._base_response(bounds)
if "census-tract" in bounds:
tract = bounds["census-tract"][0]
results = Tract.objects.filter(
state=tract['metadata']['STATEFP10'],
county=tract['metadata']['COUNTYFP10'],
tract=tract['metadata']['TRACTCE10'])
if results:
t = results[0]
# ethnicity
# top_ancestry = max(
# ((k, getattr(t, k, None)) for k in ("B04003_%03dE" % i for i in range(2, 108))),
# key=lambda x: x[1]
# )
# resp["data"].update({
# "ethnicity": {
# "total": dec2num(top_ancestry[1], whole=True),
# "pct": dec2pct(top_ancestry[1] / t.B04003_001E),
# "name": CENSUS_FIELDS[top_ancestry[0]],
# },
# })
# update avarage age in years, months
(years, months) = utils.age2ym(t.B01002_001E)
if years is not None and months is not None:
resp["data"].update(
{"average_age": {
"years": years,
"months": months,
}})
# relative age distribution
total = t.B01001_001E
males = []
females = []
for i in range(3, 26):
males.append(getattr(t, "B01001_%03dE" % i))
females.append(getattr(t, "B01001_%03dE" % (i + 24)))
total = max([max(males), max(females)])
if total:
males = [dec2pct(m / total, whole=True) for m in males]
females = [dec2pct(f / total, whole=True) for f in females]
resp["data"].update({
"age_distribution": {
"female": females,
"male": males,
}
})
# under five years of age
if t.B11005_001E:
resp["data"].update({
"under_five": {
"total":
dec2num(t.B01001_003E + t.B01001_027E, whole=True),
"per_household":
dec2num((t.B01001_003E + t.B01001_027E) /
t.B11005_001E),
"households":
dec2num(t.B11005_001E, whole=True),
}
})
# gender
if t.B01001_001E:
resp["data"].update({
"gender": {
"male_pct": dec2pct(t.B01001_002E / t.B01001_001E),
"female_pct":
dec2pct(t.B01001_026E / t.B01001_001E),
},
})
# update rest of the stuff
if t.B19001_001E:
resp["data"].update({
"average_household_income": {
"total":
dec2curr(t.B19013_001E),
"pct_gt_100k":
dec2pct((t.B19001_014E + t.B19001_015E +
t.B19001_016E + t.B19001_017E) /
t.B19001_001E),
"pct_60k_100k":
dec2pct((t.B19001_012E + t.B19001_013E) /
t.B19001_001E),
"pct_30k_60k":
dec2pct(
(t.B19001_007E + t.B19001_008E + t.B19001_009E
+ t.B19001_010E + t.B19001_011E) /
t.B19001_001E),
"pct_10k_30k":
dec2pct((t.B19001_003E + t.B19001_004E +
t.B19001_005E + t.B19001_006E) /
t.B19001_001E),
"pct_lt_10k":
dec2pct((t.B19001_002E) / t.B19001_001E),
},
})
if "census-zcta" in bounds:
zcta = bounds["census-zcta"][0]
try:
c = Contribution.objects.get(
zipcode=zcta['metadata']['ZCTA5CE10'])
total = c.democrats + c.republicans
resp['data'].update({
"contributions": {
"r": dec2curr(c.republicans, whole=True),
"r_pct": dec2pct(c.republicans / total),
"r_raw": int(c.republicans),
"d": dec2curr(c.democrats, whole=True),
"d_pct": dec2pct(c.democrats / total),
"d_raw": int(c.democrats),
},
})
except:
pass # eh, don't really care
return resp
def load_data(self, request, bounds, **args):
resp = self._base_response(bounds)
resp['data'] = {}
if "census-tract" in bounds:
tract = bounds["census-tract"][0]
# nhgis
results = NHGISTract.objects.filter(
state=tract['metadata']['STATEFP10'],
county=tract['metadata']['COUNTYFP10'],
tract=tract['metadata']['TRACTCE10'])
if results:
years = {
'1970': None,
'1980': None,
'1990': None,
'2000': None,
'2010': None,
}
for res in results:
years[res.year] = res.units
housing_data = {
'current': dec2num(years['2010'], whole=True),
'current_before': ("%i" % (years['2010'] - 1))[-1],
'current_after': ("%i" % (years['2010'] + 1))[-1],
'history': years,
}
if len([v for v in years.values() if v]) > 2:
housing_data['history_svg'] = viz.svg_housinghistory(years)
resp['data'].update({
'housing': housing_data,
})
# census
results = Tract.objects.filter(
state=tract['metadata']['STATEFP10'],
county=tract['metadata']['COUNTYFP10'],
tract=tract['metadata']['TRACTCE10'])
if results:
t = results[0]
if t.B25035_001E:
thisyear = datetime.datetime.utcnow().year
resp['data'].update({
'median_year': "%d" % t.B25035_001E,
'median_home_age': "%d" % (thisyear - t.B25035_001E),
})
return resp
