def down_bos_wards(connection, load, message):
"""
downloads the boston wards shape file
passes message dict to down_extract_zip function from downloading functions.
reads shape filepath and sends shape.
-----------
parameters :
message: {url : , target_exenstion : , local_filename : }
url : a string passed to dlf.down_extract_zip, containing the url. if left empty, automatically passes
default function dataset.
target_extension : desired filetype that needs to be extracted that is contained in the zip folder
(i.e. 'shp')
local_filename : A string. The desired filename you would like the file to be written to your directory as.
"""
down_shape_specs(message)
import geopandas as gpd
import downloading_funcs as dlf
if 'url' not in message:
message['url'] = 'http://bostonopendata-boston.opendata.arcgis.com/datasets/398ee443f4ac49e9a0b7facf80afc20f_8.zip'
shape = dlf.down_extract_zip(message['url'], message['target_extension'], local_filename = message['local_filename'],)
shape = gpd.read_file(shape)
connection.send(shape)
def zoneConcentration(shp_gdf, raw, pntLst, bufr=None):
from downloading_funcs import addr_shape, down_extract_zip
import pandas as pd
import geopandas as gpd
pnt = pntLst[0]
pnt_isCalled = pntLst[1]
for url in pnt:
if url[-3:] == 'zip':
pnt = url
assert isinstance(pnt, str) #Must extract a zipfile from pnt!
#Convenience assignment of projection type
crs = 'EPSG:4326'
#Extract and read points into memory
pnt = down_extract_zip(pnt)
ftr = gpd.read_file(pnt, crs=crs)
#Flag properties within distance "bufr" of featured locations
if not bufr:
bufr = 1 / 250 #Hard to say what a good buffer is.
assert isinstance(bufr, float) #buffer must be float!
#Frame up the buffer shapes
ftr.geometry = ftr.geometry.buffer(bufr)
ftr['flag'] = 1
if 'NAME' in ftr:
ftr.drop(['NAME'], axis=1, inplace=True)
#Frame up the raw address points data
pointy = raw[['NAME', 'Points', 'dummy_counter']]
pointy = gpd.GeoDataFrame(pointy, crs=ftr.crs, geometry=pointy.Points)
pointy = gpd.sjoin(pointy, ftr, how='left', op='intersects')
denom = pointy.groupby('NAME').sum()
denom = denom.dummy_counter
numer = pointy.groupby('NAME').sum()
numer = numer.flag
pct_ftr_coverage = pd.DataFrame(numer / denom)
pct_ftr_coverage.columns = [pnt_isCalled]
pct_ftr_coverage.fillna(0, inplace=True)
pct_ftr_coverage.crs = pointy.crs
shp_gdf = shp_gdf.merge(pct_ftr_coverage,
how="left",
left_on='NAME',
right_index=True)
del pct_ftr_coverage, raw, pointy, denom, numer
return shp_gdf
del shp_gdf
def pointInZone(shp_gdf, raw, zoneLst):
from downloading_funcs import addr_shape, down_extract_zip
import pandas as pd
import geopandas as gpd
zone = zoneLst[0]
zone_isCalled = zoneLst[1]
for url in zone:
if url[-3:] == 'zip':
zone = url
assert isinstance(zone, str) #Must extract a zipfile from pnt!
#Convenience assignment of projection type
crs = 'EPSG:4326'
#Extract and read points into memory
zone = down_extract_zip(zone)
zone = gpd.read_file(zone, crs=crs)
zone['flag'] = 1
if 'NAME' in zone:
zone.drop(['NAME'], axis=1, inplace=True)
#Frame up the raw address points data
pointy = raw[['NAME', 'Points', 'dummy_counter']]
pointy = gpd.GeoDataFrame(pointy, crs=zone.crs, geometry=pointy.Points)
pointy = gpd.sjoin(pointy, zone, how='left', op='intersects')
numer = pointy.groupby('NAME').sum()
numer = numer.flag
inzone = pointy.groupby('NAME').sum()
inzone = inzone.dummy_counter #This was calling denom.dummy_counter which is undeclared
flaginzone = pd.DataFrame(inzone)
flaginzone.columns = [zone_isCalled]
flaginzone.fillna(0, inplace=True)
flaginzone.crs = pointy.crs
shp_gdf = shp_gdf.merge(flaginzone,
how="left",
left_on='NAME',
right_index=True)
del flaginzone, pointy, inzone, numer, raw
return shp_gdf
del shp_gdf
def metro_prox(shp_gdf, raw, bufr=None):
#Flag properties within distance "bufr" of metro stations
from downloading_funcs import addr_shape, down_extract_zip
import pandas as pd
import geopandas as gpd
if not bufr:
bufr = 1 / 250 #Hard to say what a good buffer is.
assert isinstance(bufr, float) #buffer must be float!
#Frame up the metro buffer shapes
metro = down_extract_zip(
'https://opendata.arcgis.com/datasets/54018b7f06b943f2af278bbe415df1de_52.zip'
)
metro = gpd.read_file(metro, crs=shp_gdf.crs)
metro.geometry = metro.geometry.buffer(bufr)
metro['bymet'] = 1
metro.drop(['NAME'], axis=1, inplace=True)
#Frame up the raw address points data
pointy = raw[['NAME', 'Points', 'dummy_counter']]
pointy = gpd.GeoDataFrame(pointy, crs=metro.crs, geometry=pointy.Points)
pointy = gpd.sjoin(pointy, metro, how='left', op='intersects')
denom = pointy.groupby('NAME').sum()
denom = denom.dummy_counter
numer = pointy.groupby('NAME').sum()
numer = numer.bymet
pct_metro_coverage = pd.DataFrame(numer / denom)
pct_metro_coverage.columns = ['pct_metro_coverage']
pct_metro_coverage.fillna(0, inplace=True)
pct_metro_coverage.crs = pointy.crs
shp_gdf = shp_gdf.merge(pct_metro_coverage,
how="left",
left_on='NAME',
right_index=True)
return shp_gdf
def down_la_census_council(
connection, load,
message): #city council districts joined with census tracts 2010
"""
downloads the la city council and census polygons shape file
passes message dict to down_extract_zip function from downloading functions.
reads shape filepath and sends shape.
-----------
parameters :
message: {url : , target_exenstion : , local_filename : }
url : a string passed to dlf.down_extract_zip, containing the url. if left empty, automatically passes
default function dataset.
target_extension : desired filetype that needs to be extracted that is contained in the zip folder
(i.e. 'shp')
local_filename : A string. The desired filename you would like the file to be written to your directory as.
"""
down_shape_specs(message)
import geopandas as gpd
import downloading_funcs as dlf
if 'url' not in message:
message[
'url'] = 'http://geohub.lacity.org/datasets/3d41239eaa564ca699b17dbefd5d2981_0.zip'
shape = dlf.down_extract_zip(
message['url'],
message['target_extension'],
local_filename=message['local_filename'],
)
shape = gpd.read_file(shape)
connection.send(shape)
def down_dc_anc(connection, load, message):
"""
downloads the dc anc shape file
passes message dict to down_extract_zip function from downloading functions.
reads shape filepath and sends shape.
-----------
parameters :
message: {url : , target_exenstion : , local_filename : }
url : a string passed to dlf.down_extract_zip, containing the url. if left empty, automatically passes
default function dataset.
target_extension : desired filetype that needs to be extracted that is contained in the zip folder
(i.e. 'shp')
local_filename : A string. The desired filename you would like the file to be written to your directory as.
"""
down_shape_specs(message)
import geopandas as gpd
import downloading_funcs as dlf
if 'url' not in message:
message[
'url'] = 'https://opendata.arcgis.com/datasets/fcfbf29074e549d8aff9b9c708179291_1.zip'
shape = dlf.down_extract_zip(
message['url'],
message['target_extension'],
local_filename=message['local_filename'],
)
shape = gpd.read_file(shape)
connection.send(shape)
def down_la_congress(connection, load, message): #congressional districts
"""
downloads the la congressional districts shape file
passes message dict to down_extract_zip function from downloading functions.
reads shape filepath and sends shape.
-----------
parameters :
message: {url : , target_exenstion : , local_filename : }
url : a string passed to dlf.down_extract_zip, containing the url. if left empty, automatically passes
default function dataset.
target_extension : desired filetype that needs to be extracted that is contained in the zip folder
(i.e. 'shp')
local_filename : A string. The desired filename you would like the file to be written to your directory as.
"""
down_shape_specs(message)
import geopandas as gpd
import downloading_funcs as dlf
if 'url' not in message:
message[
'url'] = 'http://geohub.lacity.org/datasets/ab63122b097641d28d70ef434ebdf852_10'
shape = dlf.down_extract_zip(
message['url'],
message['target_extension'],
local_filename=message['local_filename'],
)
shape = gpd.read_file(shape)
connection.send(shape)
def down_sf_zipcodes(connection, load, message):
"""
downloads the sf zipcodes shape file
passes message dict to down_extract_zip function from downloading functions.
reads shape filepath and sends shape.
-----------
parameters :
message: {url : , target_exenstion : , local_filename : }
url : a string passed to dlf.down_extract_zip, containing the url. if left empty, automatically passes
default function dataset.
target_extension : desired filetype that needs to be extracted that is contained in the zip folder
(i.e. 'shp')
local_filename : A string. The desired filename you would like the file to be written to your directory as.
"""
down_shape_specs(message)
import geopandas as gpd
import downloading_funcs as dlf
if 'url' not in message:
message[
'url'] = 'https://data.sfgov.org/api/geospatial/u5j3-svi6?method=export&format=Shapefile'
shape = dlf.down_extract_zip(
message['url'],
message['target_extension'],
local_filename=message['local_filename'],
)
shape = gpd.read_file(shape)
connection.send(shape)