add readme for shapefiles and CT script (9945d351) · Commits · quantifyinggerrymandering / MapProcessing

scripts/GeneratingJSON_CT.ipynb

+87 −2

Original line number	Diff line number	Diff line
		%% Cell type:code id: tags:

		``` python
		import geopandas as gpd
		import numpy as np
		import pandas as pd
		import os
		import shapely
		import sys
		sys.path.append("../lib")

		from tqdm import tqdm

		############ local libraries #################
		from importlib import reload

		import censusBlockFunctions as cbF
		import countyFunctions as cnF
		import hierarchy
		import reader
		import shapefileToGraph
		import writer
		reload(cbF)
		reload(cnF)
		reload(hierarchy)
		reload(reader)
		reload(shapefileToGraph)
		reload(writer)
		##############################################
		```

		%% Output

		<module 'writer' from '/Users/g/Desktop/mapprocessing/scripts/../lib/writer.py'>
		/Users/jonm/Git/Greg/MapProcessing/.venv/lib/python3.13/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html
		from .autonotebook import tqdm as notebook_tqdm

		<module 'writer' from '/Users/jonm/Git/Greg/MapProcessing/scripts/../lib/writer.py'>

		%% Cell type:code id: tags:

		``` python
		stateAbv = "CT"
		dists = 5

		precinctShapefile = gpd.read_file("../shapefiles/CT/ct_vest_20") # https://redistrictingdatahub.org/data/download-data/
		cblockShapefile = gpd.read_file("../shapefiles/CT/tl_rd22_09_tabblock20") # https://www2.census.gov/geo/tiger/TIGER2024/TABBLOCK20/
		cblockShapefile = gpd.read_file("../shapefiles/CT/tl_2025_09_tabblock20") # https://www2.census.gov/geo/tiger/TIGER2025/TABBLOCK20/tl_2025_09_tabblock20.zip

		reload(cnF)
		cnF.determineCountyIDMaps("data", path="..")
		cblockShapefile["COUNTY"] = cblockShapefile["COUNTYFP20"].apply(lambda g: cnF.countyName(g, stateID="09"))
		precinctShapefile["COUNTY"] = precinctShapefile["COUNTYFP20"].apply(lambda g: cnF.countyName(g, stateID="09"))
		```

		%% Output

		---------------------------------------------------------------------------
		DataSourceError Traceback (most recent call last)
		Cell In[2], line 5
		2 dists = 5
		4 precinctShapefile = gpd.read_file("../shapefiles/CT/ct_vest_20") # https://redistrictingdatahub.org/data/download-data/
		----> 5 cblockShapefile = gpd.read_file("../shapefiles/CT/tl_rd22_09_tabblock20") # https://www2.census.gov/geo/tiger/TIGER2024/TABBLOCK20/
		7 reload(cnF)
		8 cnF.determineCountyIDMaps("data", path="..")
		File ~/Git/Greg/MapProcessing/.venv/lib/python3.13/site-packages/geopandas/io/file.py:316, in _read_file(filename, bbox, mask, columns, rows, engine, **kwargs)
		313 filename = response.read()
		315 if engine == "pyogrio":
		--> 316 return _read_file_pyogrio(
		317 filename, bbox=bbox, mask=mask, columns=columns, rows=rows, **kwargs
		318 )
		320 elif engine == "fiona":
		321 if pd.api.types.is_file_like(filename):
		File ~/Git/Greg/MapProcessing/.venv/lib/python3.13/site-packages/geopandas/io/file.py:576, in _read_file_pyogrio(path_or_bytes, bbox, mask, rows, **kwargs)
		567 warnings.warn(
		568 "The 'include_fields' and 'ignore_fields' keywords are deprecated, and "
		569 "will be removed in a future release. You can use the 'columns' keyword "
		(...) 572 stacklevel=3,
		573 )
		574 kwargs["columns"] = kwargs.pop("include_fields")
		--> 576 return pyogrio.read_dataframe(path_or_bytes, bbox=bbox, **kwargs)
		File ~/Git/Greg/MapProcessing/.venv/lib/python3.13/site-packages/pyogrio/geopandas.py:275, in read_dataframe(path_or_buffer, layer, encoding, columns, read_geometry, force_2d, skip_features, max_features, where, bbox, mask, fids, sql, sql_dialect, fid_as_index, use_arrow, on_invalid, arrow_to_pandas_kwargs, **kwargs)
		270 if not use_arrow:
		271 # For arrow, datetimes are read as is.
		272 # For numpy IO, datetimes are read as string values to preserve timezone info
		273 # as numpy does not directly support timezones.
		274 kwargs["datetime_as_string"] = True
		--> 275 result = read_func(
		276 path_or_buffer,
		277 layer=layer,
		278 encoding=encoding,
		279 columns=columns,
		280 read_geometry=read_geometry,
		281 force_2d=gdal_force_2d,
		282 skip_features=skip_features,
		283 max_features=max_features,
		284 where=where,
		285 bbox=bbox,
		286 mask=mask,
		287 fids=fids,
		288 sql=sql,
		289 sql_dialect=sql_dialect,
		290 return_fids=fid_as_index,
		291 **kwargs,
		292 )
		294 if use_arrow:
		295 import pyarrow as pa
		File ~/Git/Greg/MapProcessing/.venv/lib/python3.13/site-packages/pyogrio/raw.py:198, in read(path_or_buffer, layer, encoding, columns, read_geometry, force_2d, skip_features, max_features, where, bbox, mask, fids, sql, sql_dialect, return_fids, datetime_as_string, **kwargs)
		59 """Read OGR data source into numpy arrays.
		60
		61 IMPORTANT: non-linear geometry types (e.g., MultiSurface) are converted
		(...) 194
		195 """
		196 dataset_kwargs = _preprocess_options_key_value(kwargs) if kwargs else {}
		--> 198 return ogr_read(
		199 get_vsi_path_or_buffer(path_or_buffer),
		200 layer=layer,
		201 encoding=encoding,
		202 columns=columns,
		203 read_geometry=read_geometry,
		204 force_2d=force_2d,
		205 skip_features=skip_features,
		206 max_features=max_features or 0,
		207 where=where,
		208 bbox=bbox,
		209 mask=_mask_to_wkb(mask),
		210 fids=fids,
		211 sql=sql,
		212 sql_dialect=sql_dialect,
		213 return_fids=return_fids,
		214 dataset_kwargs=dataset_kwargs,
		215 datetime_as_string=datetime_as_string,
		216 )
		File pyogrio/_io.pyx:1313, in pyogrio._io.ogr_read()
		File pyogrio/_io.pyx:227, in pyogrio._io.ogr_open()
		DataSourceError: '../shapefiles/CT/tl_rd22_09_tabblock20' not recognized as being in a supported file format.; It might help to specify the correct driver explicitly by prefixing the file path with '<DRIVER>:', e.g. 'CSV:path'.

		%% Cell type:code id: tags:

		``` python
		cblockShapefile = cblockShapefile.to_crs("ESRI:102656")
		precinctShapefile = precinctShapefile.to_crs("ESRI:102656")
		```

		%% Cell type:markdown id: tags:

		## Assign census blocks to precincts

		%% Cell type:code id: tags:

		``` python
		precinctShapefile.NAME20 += "_" +precinctShapefile.COUNTY
		precinctShapefile["NAME"] = precinctShapefile["NAME20"]
		# precinctShapefile["PCTID"] = precinctShapefile.GEOID20
		precinctShapefile.COUNTY = precinctShapefile.COUNTY.map(lambda c: c.upper())
		```

		%% Cell type:code id: tags:

		``` python
		pctField = "NAME"
		```

		%% Cell type:code id: tags:

		``` python
		reload(hierarchy)
		cblockFile = "cblocksWPct2020_" + stateAbv
		filePath = os.path.join("..", "shapefiles", "derived", cblockFile + ".shp")
		if os.path.exists(filePath):
		cblockShapefile = gpd.read_file(filePath)
		else:
		cblockShapefile = hierarchy.smallUnitsToPartition(cblockShapefile, precinctShapefile,
		pctField, "COUNTY")
		# writer.writeShapefile(cblockShapefile, filePath)
		```

		%% Output

		100%\|██████████\| 8/8 [00:41<00:00, 5.19s/it]

		%% Cell type:markdown id: tags:

		## Clean precinct noise/small discontinuities

		%% Cell type:code id: tags:

		``` python
		cblockShapefile = hierarchy.cleanSmallPartitionDiscontinuity(cblockShapefile,
		["COUNTY", pctField],
		"POP20")
		```

		%% Output

		100%\|██████████\| 43/43 [00:00<00:00, 53.85it/s]

		%% Cell type:code id: tags:

		``` python
		# cblockFile = "cblocksDenoise_" + stateAbv
		# filePath = os.path.join("..", "shapefiles", "derived", cblockFile + ".shp")
		# if os.path.exists(filePath):
		# cblockShapefile = gpd.read_file(filePath)
		# else:
		# writer.writeShapefile(cblockShapefile, filePath)
		```

		%% Cell type:markdown id: tags:

		## Merge or split multipolyginol precincts

		%% Cell type:code id: tags:

		``` python
		# cblockShapefile.NAME = cblockShapefile.NAME.map(lambda n: n if "_Split" not in n
		# else "_".join(n.split("_")[:-1]))
		```

		%% Cell type:code id: tags:

		``` python
		reload(hierarchy)
		# To split discontinuous precincts
		# cblockShapefile = hierarchy.splitSignificantPartitionDiscontinuity(cblockShapefile, ["COUNTY", "NAME"],
		# "POP20")

		# To merge discontinous precincts with neighbors
		# reload(hierarchy)
		cblockShapefile = hierarchy.mergeSignificantPartitionDiscontinuity(cblockShapefile,
		["COUNTY", pctField],
		"POP20")
		```

		%% Output

		100%\|██████████\| 739/739 [00:03<00:00, 195.45it/s]
		100%\|██████████\| 42/42 [00:00<00:00, 54.89it/s]

		%% Cell type:code id: tags:

		``` python
		pctSF = cblockShapefile.dissolve(by=["COUNTY", pctField], aggfunc='sum')
		pctSF = pctSF.reset_index()
		split_regions = pctSF[pctSF.geometry.map(lambda g: isinstance(g,
		shapely.geometry.multipolygon.MultiPolygon))]
		assert len(split_regions) == 0
		# cntySF = pctSF.dissolve(by = "COUNTY", aggfunc = "sum")
		# cntySF = cntySF.reset_index()
		# split_regions = cntySF[cntySF.geometry.map(lambda g: isinstance(g,
		# shapely.geometry.multipolygon.MultiPolygon))]
		# assert len(split_regions) == 0
		```

		%% Cell type:code id: tags:

		``` python
		len(pctSF[pctSF["NAME"].str.contains(",")])
		```

		%% Output

		32

		%% Cell type:code id: tags:

		``` python
		len(pctSF), len(precinctShapefile)
		```

		%% Output

		(696, 741)

		%% Cell type:code id: tags:

		``` python
		max(list(pctSF.POP20)), sum(pctSF.POP20)/dists, len(pctSF)
		```

		%% Output

		(26970, 721188.8, 696)

		%% Cell type:code id: tags:

		``` python
		cblockFile = "cblocksMergeMultiPcts_" + stateAbv
		filePath = os.path.join("..", "shapefiles", "derived", cblockFile + ".shp")
		if os.path.exists(filePath):
		cblockShapefile = gpd.read_file(filePath)
		else:
		writer.writeShapefile(cblockShapefile, filePath)
		```

		%% Cell type:markdown id: tags:

		## Find biconnected components and merge

		%% Cell type:code id: tags:

		``` python
		import pyximport; pyximport.install(reload_support=True, language_level=3)
		import biconnectedComponents
		```

		%% Output

		ld: warning: duplicate -rpath '/Users/g/anaconda3/envs/gis/lib' ignored

		%% Cell type:code id: tags:

		``` python
		import pyximport; pyximport.install(reload_support=True, language_level=3)
		import biconnectedComponents

		adjacency = shapefileToGraph.findAdjacency(pctSF)
		adjacency_nobdr = [e for e in adjacency if -1 not in e]
		nbrList = shapefileToGraph.neighborList(pctSF, adjacency_nobdr)
		articulationPoints = biconnectedComponents.getArticulationPoints_cdef(nbrList)
		```

		%% Output

		100%\|██████████\| 696/696 [00:03<00:00, 192.79it/s]

		%% Cell type:code id: tags:

		``` python
		articulationPoints
		```

		%% Output

		{77}

		%% Cell type:code id: tags:

		``` python
		reload(hierarchy)
		pctSF = hierarchy.mergeArticulationDict(pctSF, adjacency, articulationPoints,
		["COUNTY", pctField],
		"POP20")
		```

		%% Output

		100%\|██████████\| 1/1 [00:00<00:00, 376.68it/s]

		%% Cell type:code id: tags:

		``` python
		pctSF = pctSF.dissolve(by = ["COUNTY", pctField], aggfunc='sum')
		pctSF = pctSF.reset_index()
		len(pctSF)
		```

		%% Output

		695

		%% Cell type:code id: tags:

		``` python
		adjacency_check = [e for e in shapefileToGraph.findAdjacency(pctSF)
		if -1 not in e]
		nbrList_check = shapefileToGraph.neighborList(pctSF, adjacency_check)
		articulationPoints = biconnectedComponents.getArticulationPoints_cdef(nbrList_check)
		assert len(articulationPoints) == 0
		```

		%% Output

		100%\|██████████\| 695/695 [00:03<00:00, 181.33it/s]

		%% Cell type:markdown id: tags:

		## Add votes

		%% Cell type:code id: tags:

		``` python
		precinctShapefile.columns
		```

		%% Output

		Index(['STATEFP20', 'COUNTYFP20', 'NAME20', 'G20PREDBID', 'G20PRERTRU',
		'G20PRELJOR', 'G20PREGHAW', 'G20PREOWRI', 'geometry', 'COUNTY', 'NAME'],
		dtype='object')

		%% Cell type:code id: tags:

		``` python
		dr = dict(zip(precinctShapefile[pctField], precinctShapefile.G20PRERTRU))
		dd = dict(zip(precinctShapefile[pctField], precinctShapefile.G20PREDBID))

		def getv(name, votedict):
		split_name = name.split(",")
		return sum([votedict[n] for n in split_name])


		pctSF["G20PREDEM"] = pctSF[pctField].map(lambda n: getv(n, dd))
		pctSF["G20PREREP"] = pctSF[pctField].map(lambda n: getv(n, dr))
		```

		%% Cell type:code id: tags:

		``` python
		pctSF.columns
		```

		%% Output

		Index(['COUNTY', 'NAME', 'geometry', 'STATEFP20', 'COUNTYFP20', 'TRACTCE20',
		'BLOCKCE20', 'GEOID20', 'NAME20', 'MTFCC20', 'UR20', 'UACE20',
		'UATYPE20', 'FUNCSTAT20', 'ALAND20', 'AWATER20', 'INTPTLAT20',
		'INTPTLON20', 'HOUSING20', 'POP20', 'G20PREDEM', 'G20PREREP'],
		dtype='object')

		%% Cell type:code id: tags:

		``` python
		pctSF.drop(["ALAND20", "AWATER20", "HOUSING20"], axis=1, inplace=True)
		```

		%% Cell type:code id: tags:

		``` python
		# pctSF.to_file("../shapefiles/derived/pctSF_"+ stateAbv)
		```

		%% Cell type:markdown id: tags:

		## Extract precinct graphs in various formats

		%% Cell type:code id: tags:

		``` python
		reload(writer)
		outPath = os.path.join("..", "graph", stateAbv+"_pct20.json")
		pctSF["area"] = pctSF.geometry.area
		writer.saveGerrychainJSON(pctSF, outPath, stateAbv)
		```

		%% Output

		100%\|██████████\| 695/695 [00:03<00:00, 189.34it/s]

		%% Cell type:code id: tags:

		``` python
		import networkx as nx
		G = nx.Graph()
		for e in adjacency_check:
		if -1 in list(e):
		continue
		n1, n2 = list(e)
		G.add_edge(n1, n2)
		assert nx.is_connected(G)
		```

		%% Cell type:code id: tags:

		``` python
		pctSF
		```

		%% Output

		COUNTY NAME \
		0 FAIRFIELD COUNTY Bethel 001-00_FAIRFIELD COUNTY
		1 FAIRFIELD COUNTY Bethel 002-00_FAIRFIELD COUNTY,Bethel 005-00_F...
		2 FAIRFIELD COUNTY Bethel 003-00_FAIRFIELD COUNTY
		3 FAIRFIELD COUNTY Bethel 004-00_FAIRFIELD COUNTY
		4 FAIRFIELD COUNTY Bridgeport 124-01_FAIRFIELD COUNTY
		.. ... ...
		690 WINDHAM COUNTY Windham 005-00_WINDHAM COUNTY
		691 WINDHAM COUNTY Windham 006-00_WINDHAM COUNTY
		692 WINDHAM COUNTY Windham 007-00_WINDHAM COUNTY
		693 WINDHAM COUNTY Windham 008-00_WINDHAM COUNTY
		694 WINDHAM COUNTY Woodstock 001-00_WINDHAM COUNTY

		geometry \
		0 POLYGON ((818410.486 696684.981, 818364.897 69...
		1 POLYGON ((821641.904 703498.760, 821691.266 70...
		2 POLYGON ((821515.450 691432.947, 821385.981 69...
		3 POLYGON ((813155.775 691075.367, 812865.915 69...
		4 POLYGON ((881253.707 633360.851, 881224.418 63...
		.. ...
		690 POLYGON ((1144857.467 820824.848, 1144709.740 ...
		691 POLYGON ((1146143.052 819308.868, 1146145.577 ...
		692 POLYGON ((1161096.102 801575.944, 1160371.613 ...
		693 POLYGON ((1140236.769 820508.328, 1140009.976 ...
		694 POLYGON ((1177534.849 898932.087, 1177512.613 ...

		STATEFP20 \
		0 0909090909090909090909090909090909090909
		1 0909090909090909090909090909090909090909090909...
		2 0909090909090909090909090909090909090909090909...
		3 0909090909090909090909090909090909090909090909...
		4 09090909090909090909090909
		.. ...
		690 0909090909090909090909090909090909090909090909...
		691 0909090909090909090909090909090909090909090909...
		692 0909090909090909090909090909090909090909090909...
		693 09090909090909090909090909090909090909090909
		694 0909090909090909090909090909090909090909090909...

		COUNTYFP20 \
		0 0010010010010010010010010010010010010010010010...
		1 0010010010010010010010010010010010010010010010...
		2 0010010010010010010010010010010010010010010010...
		3 0010010010010010010010010010010010010010010010...
		4 001001001001001001001001001001001001001
		.. ...
		690 0150150150150150150150150150150150150150150150...
		691 0150150150150150150150150150150150150150150150...
		692 0150150150150150150150150150150150150150150150...
		693 0150150150150150150150150150150150150150150150...
		694 0150150150150150150150150150150150150150150150...

		TRACTCE20 \
		0 2003012002002002002002002002002002002002002003...
		1 2003012003012003012003012003012003012003012003...
		2 2003022003022003022002002003022003022003022003...
		3 2003022001002001002001002002002001002002002001...
		4 0734000734000734000735000734000734000734000734...
		.. ...
		690 8006008003008003008007008007008007008003008003...
		691 8007008004008006008004008007008004008007008004...
		692 8005028005028005028005028005028005018005028005...
		693 8003008004008004008003008003008003008003008003...
		694 9011019011029011029011029011029011029011019011...

		BLOCKCE20 \
		0 2019100710001010100510124001201340031006100310...
		1 2018300210253008101110212005102830142020100010...
		2 1007400240043005100210034006101210083006101340...
		3 2000100920151005400410034000200010101002100710...
		4 2007200120001002200320022005200810001001200620...
		.. ...
		690 3008200620031007200230063004300330091011302110...
		691 3013100620113006101910071016100410053003101230...
		692 3016200120033025101910042007100110002002302120...
		693 1008300430011018202220141005100610073016300720...
		694 1030104530121016103130041017202030091039105610...

		GEOID20 \
		0 0900120030120190900120020010070900120020010000...
		1 0900120030120180900120030130020900120030110250...
		2 0900120030210070900120030240020900120030240040...
		3 0900120030220000900120010010090900120010020150...
		4 0900107340020070900107340020010900107340020000...
		.. ...
		690 0901580060030080901580030020060901580030020030...
		691 0901580070030130901580040010060901580060020110...
		692 0901580050230160901580050220010901580050220030...
		693 0901580030010080901580040030040901580040030010...
		694 0901590110110300901590110210450901590110230120...

		NAME20 \
		0 Block 2019Block 1007Block 1000Block 1010Block ...
		1 Block 2018Block 3002Block 1025Block 3008Block ...
		2 Block 1007Block 4002Block 4004Block 3005Block ...
		3 Block 2000Block 1009Block 2015Block 1005Block ...
		4 Block 2007Block 2001Block 2000Block 1002Block ...
		.. ...
		690 Block 3008Block 2006Block 2003Block 1007Block ...
		691 Block 3013Block 1006Block 2011Block 3006Block ...
		692 Block 3016Block 2001Block 2003Block 3025Block ...
		693 Block 1008Block 3004Block 3001Block 1018Block ...
		694 Block 1030Block 1045Block 3012Block 1016Block ...

		MTFCC20 \
		0 G5040G5040G5040G5040G5040G5040G5040G5040G5040G...
		1 G5040G5040G5040G5040G5040G5040G5040G5040G5040G...
		2 G5040G5040G5040G5040G5040G5040G5040G5040G5040G...
		3 G5040G5040G5040G5040G5040G5040G5040G5040G5040G...
		4 G5040G5040G5040G5040G5040G5040G5040G5040G5040G...
		.. ...
		690 G5040G5040G5040G5040G5040G5040G5040G5040G5040G...
		691 G5040G5040G5040G5040G5040G5040G5040G5040G5040G...
		692 G5040G5040G5040G5040G5040G5040G5040G5040G5040G...
		693 G5040G5040G5040G5040G5040G5040G5040G5040G5040G...
		694 G5040G5040G5040G5040G5040G5040G5040G5040G5040G...

		UR20 \
		0 UUUUUUUUUUUUUUUUUUUU
		1 UUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUU...
		2 URRUUURRUURRUUUUUUUUUUUUUUUUURUUUUURUURUUUUUUU...
		3 UURUUUUUUUUUUUUUUUUUUUUUUUURURUUUUUUUUUUUUUUUU...
		4 UUUUUUUUUUUUU
		.. ...
		690 UUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUU...
		691 UUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUU...
		692 RRURUUURUURUURRRUURRRURRUUURRURRRRRURRRRRURURR...
		693 UUUUURURRRUUUUUUURRRRU
		694 RRURRRRRRRRRRRRRRRRRRRURRRRRRRRRRRRRRRRRRRRURR...

		UACE20 \
		0 2209622096220962209622096220962209622096220962...
		1 2209622096220962209622096220962209622096220962...
		2 2209622096220962209622096220962209622096220962...
		3 2209622096220962209622096220962209622096220962...
		4 1016210162101621016210162101621016210162101621...
		.. ...
		690 9559095590955909559095590955909559095590955909...
		691 9559095590955909559095590955909559095590955909...
		692 9559095590955909559095590955909559095590955909...
		693 9559095590955909559095590955909559095590955909...
		694 7286872868728687286872868728687286872868728687...

		UATYPE20 \
		0 UUUUUUUUUUUUUUUUUUUU
		1 UUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUU...
		2 UUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUU
		3 UUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUU...
		4 UUUUUUUUUUUUU
		.. ...
		690 UUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUU...
		691 UUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUU...
		692 UUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUU
		693 UUUUUUUUUUUUUU
		694 UUUUUUUUUUUUUUU

		FUNCSTAT20 \
		0 SSSSSSSSSSSSSSSSSSSS
		1 SSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSS...
		2 SSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSS...
		3 SSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSS...
		4 SSSSSSSSSSSSS
		.. ...
		690 SSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSS...
		691 SSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSS...
		692 SSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSS...
		693 SSSSSSSSSSSSSSSSSSSSSS
		694 SSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSS...

		INTPTLAT20 \
		0 +41.3908647+41.3878371+41.3932749+41.3838596+4...
		1 +41.3910143+41.4154880+41.4179660+41.4057285+4...
		2 +41.3608019+41.3607929+41.3606207+41.3724732+4...
		3 +41.3602695+41.3770989+41.3581148+41.3791469+4...
		4 +41.2002753+41.2022561+41.2056116+41.1984986+4...
		.. ...
		690 +41.7155620+41.7164764+41.7159123+41.7274243+4...
		691 +41.7164456+41.7081731+41.7107981+41.7089858+4...
		692 +41.6886249+41.7401999+41.7519934+41.6663504+4...
		693 +41.7251206+41.7087923+41.7109068+41.7200344+4...
		694 +41.9455386+41.9565782+41.9260304+41.9784916+4...

		INTPTLON20 POP20 G20PREDEM \
		0 -073.4038721-073.4159745-073.4090007-073.41683... 3077 920
		1 -073.3948466-073.3929670-073.3993009-073.39730... 5221 1613
		2 -073.3834793-073.3636509-073.3785212-073.40645... 6293 2064
		3 -073.4139666-073.4314266-073.4293577-073.42678... 5767 1673
		4 -073.1826051-073.1801577-073.1814102-073.18216... 1580 332
		.. ... ... ...
		690 -072.2140220-072.2223063-072.2284299-072.20770... 8519 1456
		691 -072.2108746-072.2021979-072.2083136-072.21785... 7165 1692
		692 -072.1481711-072.1374199-072.1507972-072.13319... 3950 1243
		693 -072.2459741-072.2295604-072.2251597-072.24319... 1282 339
		694 -072.0754769-071.9953641-071.9306718-072.05957... 8221 2548

		G20PREREP area
		0 520 3.626240e+07
		1 1425 1.003939e+08
		2 1656 2.185647e+08
		3 1133 1.191771e+08
		4 87 3.534818e+06
		.. ... ...
		690 563 4.096040e+07
		691 745 4.738276e+07
		692 1025 4.988012e+08
		693 130 3.733801e+07
		694 2520 1.724802e+09

		[695 rows x 20 columns]

		%% Cell type:code id: tags:

		``` python
		```

shapefiles/CT/ct_vest_20/README.md

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Original line number	Diff line number	Diff line
		# Download and Unzip Shapefile

		You can download the shapefile `ct_vest_20.zip` from the following URL:
		[https://redistrictingdatahub.org/data/download-data/](https://redistrictingdatahub.org/data/download-data/)
		[ct_vest_20.zip](https://redistrictingdatahub.org/dataset/vest-2020-connecticut-precinct-and-election-results/)


		Unzip the archive and place its contents in this directory. The contains should contain following files:

shapefiles/CT/tl_2025_09_tabblock20/README.md

0 → 100644

+11 −0

Original line number	Diff line number	Diff line
		# Download and Unzip Shapefile

		Download the shapefile `tl_2025_09_tabblock20.zip` from the following URL:
		[tl_2025_09_tabblock20.zip](https://www2.census.gov/geo/tiger/TIGER2025/TABBLOCK20/tl_2025_09_tabblock20.zip)


		Unzip the archive `tl_2025_09_tabblock20.zip)` and place its contents in this directory. The contains should contain following files:

		```{.sh}

		```
		No newline at end of file

shapefiles/TX/tx_vest_20/README.md

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		# Download and Unzip Shapefile

		You can download the shapefile `tx_vest_20.zip` from the following URL:
		[https://www2.census.gov/geo/tiger/TIGER2024/TABBLOCK20/](https://www2.census.gov/geo/tiger/TIGER2024/TABBLOCK20/)
		[tx_vest_20.zip](https://redistrictingdatahub.org/dataset/vest-2020-texas-precinct-boundaries-and-election-results/)


		Unzip the archive and place its contents in this directory. The contains should contain following files: