{ "cells": [ { "cell_type": "markdown", "id": "painted-discipline", "metadata": {}, "source": [ "# Overview of the data product\n", "\n", "The data product of spatial signatures in Great Britain contains the data illustrated by this notebook." ] }, { "cell_type": "code", "execution_count": 1, "id": "intelligent-present", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "/home/jovyan/work/urbangrammar_samba/spatial_signatures/data_product\n" ] } ], "source": [ "cd ../../urbangrammar_samba/spatial_signatures/data_product/" ] }, { "cell_type": "code", "execution_count": 3, "id": "supposed-diameter", "metadata": {}, "outputs": [], "source": [ "import json\n", "import pandas\n", "import geopandas" ] }, { "cell_type": "markdown", "id": "played-heaven", "metadata": {}, "source": [ "## Geometry\n", "\n", "Signature geometry with signature type and polygon ID." ] }, { "cell_type": "code", "execution_count": 3, "id": "alpha-taxation", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/opt/conda/lib/python3.8/site-packages/geopandas/geodataframe.py:577: RuntimeWarning: Sequential read of iterator was interrupted. Resetting iterator. This can negatively impact the performance.\n", " for feature in features_lst:\n" ] }, { "data": { "text/html": [ "
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" ], "text/plain": [ " id code type \\\n", "0 0_COA COA Countryside agriculture \n", "1 1_COA COA Countryside agriculture \n", "2 2_COA COA Countryside agriculture \n", "3 3_COA COA Countryside agriculture \n", "4 4_COA COA Countryside agriculture \n", "5 5_COA COA Countryside agriculture \n", "6 6_COA COA Countryside agriculture \n", "7 7_COA COA Countryside agriculture \n", "8 8_COA COA Countryside agriculture \n", "9 9_COA COA Countryside agriculture \n", "\n", " geometry \n", "0 POLYGON ((62220.000 798500.000, 62110.000 7985... \n", "1 POLYGON ((63507.682 796515.169, 63471.097 7965... \n", "2 POLYGON ((65953.174 802246.172, 65950.620 8022... \n", "3 POLYGON ((67297.740 803435.800, 67220.289 8034... \n", "4 POLYGON ((75760.000 852670.000, 75700.000 8527... \n", "5 POLYGON ((78663.640 819587.579, 78665.420 8195... \n", "6 POLYGON ((79020.596 820041.322, 79022.514 8200... \n", "7 POLYGON ((79088.951 819900.971, 79089.062 8199... \n", "8 POLYGON ((79843.335 818918.964, 79843.296 8189... \n", "9 POLYGON ((88080.000 14970.000, 88078.269 14961... " ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "geopandas.read_file(\"spatial_signatures_GB.gpkg\", rows=10)" ] }, { "cell_type": "markdown", "id": "reflected-retrieval", "metadata": {}, "source": [ "## Geometry description\n", "\n", "Summary of input characters per each geometry." ] }, { "cell_type": "code", "execution_count": 4, "id": "mineral-dealer", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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311_COA190.30894659.0228240.7645430.4945194.5419850.9976730.9673970.59809210.134862...NaN0.000000281.2893698.043478198.2968414.326087NaN0.074.3776824378.879114
414_COA146.47781650.3089640.2297560.5094394.3820900.7694550.9745910.6079798.836870...2296.6579680.023599519.0197177.519174281.73730824.020649NaN0.0199.5443811698.769041
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9670194892_LOUNaNNaNNaNNaNNaNNaNNaNNaNNaN...457.1709905.0000000.000000515.00000038.4700012364.000000401.4110112.0410.0390480.000000
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codetypeform_sdbAreform_sdbPerform_sdbCoAform_ssbCCoform_ssbCorform_ssbSquform_ssbERIform_ssbElo...func_supermarkets_nearestfunc_supermarkets_countsfunc_listed_nearestfunc_listed_countsfunc_fhrs_nearestfunc_fhrs_countsfunc_culture_nearestfunc_culture_countsfunc_water_nearestfunc_retail_centrenearest
0ACSAccessible suburbia176.94913553.9026970.4768380.5348564.2538450.7752720.9877070.642271...828.8222611.890519744.22399411.273578218.460768334.4349915384.6387460.059113542.613661849.447871
1CRNConnected residential neighbourhoods272.52222069.1199671.0698720.4809414.4455151.4664260.9794150.555468...679.9589402.855980596.61365424.279146152.479922692.6640503946.0525170.129197555.964942536.469155
2COACountryside agriculture204.10040056.0489840.5058310.5062754.3711560.8090870.9777890.600065...4751.2264290.089042557.93627611.223066725.69064344.46552913156.2037650.003804304.4881814943.972107
3DRNDense residential neighbourhoods375.59829080.5584732.1273400.4725544.6947141.8636200.9699120.557054...661.7655943.127412506.61471537.474705144.021617860.9271023497.5111810.259194483.124139421.093530
4DUNDense urban neighbourhoods588.359559107.3628495.0340840.4357145.2082423.2784190.9504310.519821...587.2768104.436632350.89033962.783422106.0843581568.4435972287.4321990.476118528.850109224.326713
5DISDisconnected suburbia212.71395861.6316620.5193720.4915884.3479001.0192930.9817790.573786...761.8583732.067315729.60851724.181257217.945624342.0817225831.5234330.077958523.050240725.573382
6DIUConcentrated urbanity3713.379427376.300388159.0876080.42518612.48466718.5894820.7769500.594314...229.90309622.51056331.732228685.15633816.2190506297.607746702.75088010.392254565.24820329.803442
7GRQGridded residential quarters283.89260769.6672450.7490260.4917544.5066851.6631510.9768420.584548...577.6839743.409903516.19737631.771826129.2442041081.3765104094.9152530.240503522.087434445.518972
8HDUHyper concentrated urbanity3358.099586330.81857690.8195440.4462929.27343822.5139540.8028920.617669...324.41631218.79104569.7492361142.56716414.1012699213.145522351.32511034.197761759.60420832.544669
9LOULocal urbanity823.354285135.54391912.6667290.4093106.0142395.0718480.9190850.506415...483.0178626.848327216.858599140.03107382.4689612167.9099911273.2268971.129622507.706457161.854989
10MEUMetropolitan urbanity2413.938716283.935149118.9469490.3958629.71750412.4068940.8201420.527758...299.93049617.27195851.874364456.52963040.0639824490.949206644.5312594.446825467.71363166.318054
11OPSOpen sprawl226.71509859.6397800.9004780.5185314.3719390.9857290.9824520.622301...948.0259141.469023760.25725418.171441267.238602253.8752266309.7533410.061560378.3561871002.663064
12REURegional urbanity1480.260902195.97866043.1909980.3930357.7768638.8448050.8695140.512959...331.06778112.531123115.004786324.50075256.8652403163.829678850.2544872.233070461.41585990.874497
13URBUrban buffer209.42185855.9417020.7433950.5236324.3405400.8599730.9829040.630125...1752.8734790.654018673.93139916.138833379.169823132.6618468939.6471360.024052345.7907472102.455609
14WALWarehouse/Park land393.21609775.6802703.2630390.4694664.5648901.3525360.9761020.542256...1043.8354091.427596934.00115210.570084256.220805271.0925375121.4691500.058667417.431851898.174463
15WICWild countryside209.85538257.1220520.2235420.5019394.3812720.7061300.9765220.589908...9854.1239370.0289751324.0250444.2127201699.16964933.07329320695.2906650.001680236.73032411041.324478
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16 rows × 118 columns

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" ], "text/plain": [ " code type form_sdbAre form_sdbPer \\\n", "0 ACS Accessible suburbia 176.949135 53.902697 \n", "1 CRN Connected residential neighbourhoods 272.522220 69.119967 \n", "2 COA Countryside agriculture 204.100400 56.048984 \n", "3 DRN Dense residential neighbourhoods 375.598290 80.558473 \n", "4 DUN Dense urban neighbourhoods 588.359559 107.362849 \n", "5 DIS Disconnected suburbia 212.713958 61.631662 \n", "6 DIU Concentrated urbanity 3713.379427 376.300388 \n", "7 GRQ Gridded residential quarters 283.892607 69.667245 \n", "8 HDU Hyper concentrated urbanity 3358.099586 330.818576 \n", "9 LOU Local urbanity 823.354285 135.543919 \n", "10 MEU Metropolitan urbanity 2413.938716 283.935149 \n", "11 OPS Open sprawl 226.715098 59.639780 \n", "12 REU Regional urbanity 1480.260902 195.978660 \n", "13 URB Urban buffer 209.421858 55.941702 \n", "14 WAL Warehouse/Park land 393.216097 75.680270 \n", "15 WIC Wild countryside 209.855382 57.122052 \n", "\n", " form_sdbCoA form_ssbCCo form_ssbCor form_ssbSqu form_ssbERI \\\n", "0 0.476838 0.534856 4.253845 0.775272 0.987707 \n", "1 1.069872 0.480941 4.445515 1.466426 0.979415 \n", "2 0.505831 0.506275 4.371156 0.809087 0.977789 \n", "3 2.127340 0.472554 4.694714 1.863620 0.969912 \n", "4 5.034084 0.435714 5.208242 3.278419 0.950431 \n", "5 0.519372 0.491588 4.347900 1.019293 0.981779 \n", "6 159.087608 0.425186 12.484667 18.589482 0.776950 \n", "7 0.749026 0.491754 4.506685 1.663151 0.976842 \n", "8 90.819544 0.446292 9.273438 22.513954 0.802892 \n", "9 12.666729 0.409310 6.014239 5.071848 0.919085 \n", "10 118.946949 0.395862 9.717504 12.406894 0.820142 \n", "11 0.900478 0.518531 4.371939 0.985729 0.982452 \n", "12 43.190998 0.393035 7.776863 8.844805 0.869514 \n", "13 0.743395 0.523632 4.340540 0.859973 0.982904 \n", "14 3.263039 0.469466 4.564890 1.352536 0.976102 \n", "15 0.223542 0.501939 4.381272 0.706130 0.976522 \n", "\n", " form_ssbElo ... func_supermarkets_nearest func_supermarkets_counts \\\n", "0 0.642271 ... 828.822261 1.890519 \n", "1 0.555468 ... 679.958940 2.855980 \n", "2 0.600065 ... 4751.226429 0.089042 \n", "3 0.557054 ... 661.765594 3.127412 \n", "4 0.519821 ... 587.276810 4.436632 \n", "5 0.573786 ... 761.858373 2.067315 \n", "6 0.594314 ... 229.903096 22.510563 \n", "7 0.584548 ... 577.683974 3.409903 \n", "8 0.617669 ... 324.416312 18.791045 \n", "9 0.506415 ... 483.017862 6.848327 \n", "10 0.527758 ... 299.930496 17.271958 \n", "11 0.622301 ... 948.025914 1.469023 \n", "12 0.512959 ... 331.067781 12.531123 \n", "13 0.630125 ... 1752.873479 0.654018 \n", "14 0.542256 ... 1043.835409 1.427596 \n", "15 0.589908 ... 9854.123937 0.028975 \n", "\n", " func_listed_nearest func_listed_counts func_fhrs_nearest \\\n", "0 744.223994 11.273578 218.460768 \n", "1 596.613654 24.279146 152.479922 \n", "2 557.936276 11.223066 725.690643 \n", "3 506.614715 37.474705 144.021617 \n", "4 350.890339 62.783422 106.084358 \n", "5 729.608517 24.181257 217.945624 \n", "6 31.732228 685.156338 16.219050 \n", "7 516.197376 31.771826 129.244204 \n", "8 69.749236 1142.567164 14.101269 \n", "9 216.858599 140.031073 82.468961 \n", "10 51.874364 456.529630 40.063982 \n", "11 760.257254 18.171441 267.238602 \n", "12 115.004786 324.500752 56.865240 \n", "13 673.931399 16.138833 379.169823 \n", "14 934.001152 10.570084 256.220805 \n", "15 1324.025044 4.212720 1699.169649 \n", "\n", " func_fhrs_counts func_culture_nearest func_culture_counts \\\n", "0 334.434991 5384.638746 0.059113 \n", "1 692.664050 3946.052517 0.129197 \n", "2 44.465529 13156.203765 0.003804 \n", "3 860.927102 3497.511181 0.259194 \n", "4 1568.443597 2287.432199 0.476118 \n", "5 342.081722 5831.523433 0.077958 \n", "6 6297.607746 702.750880 10.392254 \n", "7 1081.376510 4094.915253 0.240503 \n", "8 9213.145522 351.325110 34.197761 \n", "9 2167.909991 1273.226897 1.129622 \n", "10 4490.949206 644.531259 4.446825 \n", "11 253.875226 6309.753341 0.061560 \n", "12 3163.829678 850.254487 2.233070 \n", "13 132.661846 8939.647136 0.024052 \n", "14 271.092537 5121.469150 0.058667 \n", "15 33.073293 20695.290665 0.001680 \n", "\n", " func_water_nearest func_retail_centrenearest \n", "0 542.613661 849.447871 \n", "1 555.964942 536.469155 \n", "2 304.488181 4943.972107 \n", "3 483.124139 421.093530 \n", "4 528.850109 224.326713 \n", "5 523.050240 725.573382 \n", "6 565.248203 29.803442 \n", "7 522.087434 445.518972 \n", "8 759.604208 32.544669 \n", "9 507.706457 161.854989 \n", "10 467.713631 66.318054 \n", "11 378.356187 1002.663064 \n", "12 461.415859 90.874497 \n", "13 345.790747 2102.455609 \n", "14 417.431851 898.174463 \n", "15 236.730324 11041.324478 \n", "\n", "[16 rows x 118 columns]" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pandas.read_csv(\"per_type.csv\")" ] }, { "cell_type": "markdown", "id": "yellow-rover", "metadata": {}, "source": [ "## Keys\n", "\n", "Key to codes denoting measured characters. " ] }, { "cell_type": "code", "execution_count": 6, "id": "defensive-costa", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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Unnamed: 00
0func_populationPopulation
1func_night_lightsNight lights
2func_workplace_abdeWorkplace population [Agriculture, energy and ...
3func_workplace_cWorkplace population [Manufacturing]
4func_workplace_fWorkplace population [Construction]
.........
111form_lseERIequivalent rectangular index of enclosure
112form_lseCWAcompactness-weighted axis of enclosure
113form_lteOriorientation of enclosure
114form_lteWNBperimeter-weighted neighbours of enclosure
115form_lieWCearea-weighted ETCs of enclosure
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116 rows × 2 columns

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" ], "text/plain": [ " Unnamed: 0 0\n", "0 func_population Population\n", "1 func_night_lights Night lights\n", "2 func_workplace_abde Workplace population [Agriculture, energy and ...\n", "3 func_workplace_c Workplace population [Manufacturing]\n", "4 func_workplace_f Workplace population [Construction]\n", ".. ... ...\n", "111 form_lseERI equivalent rectangular index of enclosure\n", "112 form_lseCWA compactness-weighted axis of enclosure\n", "113 form_lteOri orientation of enclosure\n", "114 form_lteWNB perimeter-weighted neighbours of enclosure\n", "115 form_lieWCe area-weighted ETCs of enclosure\n", "\n", "[116 rows x 2 columns]" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pandas.read_csv(\"key.csv\")" ] }, { "cell_type": "markdown", "id": "recognized-destruction", "metadata": {}, "source": [ "Key linking signature type and type code." ] }, { "cell_type": "code", "execution_count": 7, "id": "pressing-violation", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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type_nametype_code
0Countryside agricultureCOA
1Accessible suburbiaACS
2Open sprawlOPS
3Wild countrysideWIC
4Warehouse/Park landWAL
5Gridded residential quartersGRQ
6Urban bufferURB
7Disconnected suburbiaDIS
8Dense residential neighbourhoodsDRN
9Connected residential neighbourhoodsCRN
10Dense urban neighbourhoodsDUN
11Local urbanityLOU
12Concentrated urbanityDIU
13Regional urbanityREU
14Metropolitan urbanityMEU
15Hyper concentrated urbanityHDU
16outlierOUT
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" ], "text/plain": [ " type_name type_code\n", "0 Countryside agriculture COA\n", "1 Accessible suburbia ACS\n", "2 Open sprawl OPS\n", "3 Wild countryside WIC\n", "4 Warehouse/Park land WAL\n", "5 Gridded residential quarters GRQ\n", "6 Urban buffer URB\n", "7 Disconnected suburbia DIS\n", "8 Dense residential neighbourhoods DRN\n", "9 Connected residential neighbourhoods CRN\n", "10 Dense urban neighbourhoods DUN\n", "11 Local urbanity LOU\n", "12 Concentrated urbanity DIU\n", "13 Regional urbanity REU\n", "14 Metropolitan urbanity MEU\n", "15 Hyper concentrated urbanity HDU\n", "16 outlier OUT" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pandas.read_csv(\"type_code.csv\")" ] }, { "cell_type": "markdown", "id": "automatic-cruise", "metadata": {}, "source": [ "## LSOA interpolation\n", "\n", "Interpolation of signature types to LSOA geometry." ] }, { "cell_type": "code", "execution_count": 8, "id": "arranged-ordering", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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LSOA11CDprimary_codeprimary_typeCOAACSOPSWICWALGRQURBDISDRNCRNDUNLOUDIUREUOUTMEUHDU
0E01000007DUNDense urban neighbourhoods0.00.0000000.0000000.00.0000000.0000000.00.0000000.0000000.0000000.8227030.1772970.00.00.00.00.0
1E01000015DRNDense residential neighbourhoods0.00.0000000.0011170.00.0000000.0000000.00.0228150.7076350.1367940.1302510.0000000.00.00.00.00.0
2E01000030DRNDense residential neighbourhoods0.00.0000000.0000000.00.4277420.0000000.00.0000000.5722580.0000000.0000000.0000000.00.00.00.00.0
3E01000085DUNDense urban neighbourhoods0.00.0000000.0000000.00.0000000.0000000.00.0000000.1718080.1265670.7016260.0000000.00.00.00.00.0
4E01000118CRNConnected residential neighbourhoods0.00.3397140.0362300.00.0000000.1320120.00.0000000.0042800.4877640.0000000.0000000.00.00.00.00.0
5E01000125CRNConnected residential neighbourhoods0.00.0000000.0000000.00.0000000.0000000.00.0000000.0000000.8674040.1325960.0000000.00.00.00.00.0
6E01000136WALWarehouse/Park land0.00.0000000.0514770.00.4430330.0000000.00.0123100.4270060.0292300.0369440.0000000.00.00.00.00.0
7E01000145CRNConnected residential neighbourhoods0.00.0000000.0000000.00.0000000.0000000.00.0000000.0000001.0000000.0000000.0000000.00.00.00.00.0
8E01000146CRNConnected residential neighbourhoods0.00.0000000.0000000.00.0000000.0000000.00.0000000.0834650.9165350.0000000.0000000.00.00.00.00.0
9E01000166OPSOpen sprawl0.00.0000000.8930810.00.0919060.0000000.00.0150130.0000000.0000000.0000000.0000000.00.00.00.00.0
\n", "
" ], "text/plain": [ " LSOA11CD primary_code primary_type COA \\\n", "0 E01000007 DUN Dense urban neighbourhoods 0.0 \n", "1 E01000015 DRN Dense residential neighbourhoods 0.0 \n", "2 E01000030 DRN Dense residential neighbourhoods 0.0 \n", "3 E01000085 DUN Dense urban neighbourhoods 0.0 \n", "4 E01000118 CRN Connected residential neighbourhoods 0.0 \n", "5 E01000125 CRN Connected residential neighbourhoods 0.0 \n", "6 E01000136 WAL Warehouse/Park land 0.0 \n", "7 E01000145 CRN Connected residential neighbourhoods 0.0 \n", "8 E01000146 CRN Connected residential neighbourhoods 0.0 \n", "9 E01000166 OPS Open sprawl 0.0 \n", "\n", " ACS OPS WIC WAL GRQ URB DIS DRN \\\n", "0 0.000000 0.000000 0.0 0.000000 0.000000 0.0 0.000000 0.000000 \n", "1 0.000000 0.001117 0.0 0.000000 0.000000 0.0 0.022815 0.707635 \n", "2 0.000000 0.000000 0.0 0.427742 0.000000 0.0 0.000000 0.572258 \n", "3 0.000000 0.000000 0.0 0.000000 0.000000 0.0 0.000000 0.171808 \n", "4 0.339714 0.036230 0.0 0.000000 0.132012 0.0 0.000000 0.004280 \n", "5 0.000000 0.000000 0.0 0.000000 0.000000 0.0 0.000000 0.000000 \n", "6 0.000000 0.051477 0.0 0.443033 0.000000 0.0 0.012310 0.427006 \n", "7 0.000000 0.000000 0.0 0.000000 0.000000 0.0 0.000000 0.000000 \n", "8 0.000000 0.000000 0.0 0.000000 0.000000 0.0 0.000000 0.083465 \n", "9 0.000000 0.893081 0.0 0.091906 0.000000 0.0 0.015013 0.000000 \n", "\n", " CRN DUN LOU DIU REU OUT MEU HDU \n", "0 0.000000 0.822703 0.177297 0.0 0.0 0.0 0.0 0.0 \n", "1 0.136794 0.130251 0.000000 0.0 0.0 0.0 0.0 0.0 \n", "2 0.000000 0.000000 0.000000 0.0 0.0 0.0 0.0 0.0 \n", "3 0.126567 0.701626 0.000000 0.0 0.0 0.0 0.0 0.0 \n", "4 0.487764 0.000000 0.000000 0.0 0.0 0.0 0.0 0.0 \n", "5 0.867404 0.132596 0.000000 0.0 0.0 0.0 0.0 0.0 \n", "6 0.029230 0.036944 0.000000 0.0 0.0 0.0 0.0 0.0 \n", "7 1.000000 0.000000 0.000000 0.0 0.0 0.0 0.0 0.0 \n", "8 0.916535 0.000000 0.000000 0.0 0.0 0.0 0.0 0.0 \n", "9 0.000000 0.000000 0.000000 0.0 0.0 0.0 0.0 0.0 " ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pandas.read_csv(\"lsoa_estimates.csv\", nrows=10)" ] }, { "cell_type": "markdown", "id": "difficult-bailey", "metadata": {}, "source": [ "## OA interpolation\n", "Interpolation of signature types to OA geometry." ] }, { "cell_type": "code", "execution_count": 9, "id": "surface-pontiac", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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OA11CDprimary_codeprimary_typeCOAACSOPSWICWALGRQURBDISDRNCRNDUNLOUDIUREUOUTMEUHDU
0E00000001DIUConcentrated urbanity0.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.0
1E00000003DIUConcentrated urbanity0.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.0
2E00000005DIUConcentrated urbanity0.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.0
3E00000007DIUConcentrated urbanity0.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.0
4E00000010DIUConcentrated urbanity0.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.0
5E00000012DIUConcentrated urbanity0.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.0
6E00000013DIUConcentrated urbanity0.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.0
7E00000014DIUConcentrated urbanity0.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.0
8E00000016DIUConcentrated urbanity0.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.0
9E00000017DIUConcentrated urbanity0.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.0
\n", "
" ], "text/plain": [ " OA11CD primary_code primary_type COA ACS OPS WIC WAL \\\n", "0 E00000001 DIU Concentrated urbanity 0.0 0.0 0.0 0.0 0.0 \n", "1 E00000003 DIU Concentrated urbanity 0.0 0.0 0.0 0.0 0.0 \n", "2 E00000005 DIU Concentrated urbanity 0.0 0.0 0.0 0.0 0.0 \n", "3 E00000007 DIU Concentrated urbanity 0.0 0.0 0.0 0.0 0.0 \n", "4 E00000010 DIU Concentrated urbanity 0.0 0.0 0.0 0.0 0.0 \n", "5 E00000012 DIU Concentrated urbanity 0.0 0.0 0.0 0.0 0.0 \n", "6 E00000013 DIU Concentrated urbanity 0.0 0.0 0.0 0.0 0.0 \n", "7 E00000014 DIU Concentrated urbanity 0.0 0.0 0.0 0.0 0.0 \n", "8 E00000016 DIU Concentrated urbanity 0.0 0.0 0.0 0.0 0.0 \n", "9 E00000017 DIU Concentrated urbanity 0.0 0.0 0.0 0.0 0.0 \n", "\n", " GRQ URB DIS DRN CRN DUN LOU DIU REU OUT MEU HDU \n", "0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 \n", "1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 \n", "2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 \n", "3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 \n", "4 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 \n", "5 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 \n", "6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 \n", "7 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 \n", "8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 \n", "9 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 " ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pandas.read_csv(\"output_area_estimates.csv\", nrows=10)" ] }, { "cell_type": "markdown", "id": "faced-arizona", "metadata": {}, "source": [ "## Pen portraits\n", "\n", "Short description of each signature type." ] }, { "cell_type": "code", "execution_count": 4, "id": "divine-replication", "metadata": {}, "outputs": [], "source": [ "with open(\"pen_portraits.json\", \"r\") as f:\n", " portraits = json.load(f)" ] }, { "cell_type": "code", "execution_count": 5, "id": "solid-parent", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'Wild countryside': 'In “Wild countryside”, human influence is the least intensive. This signature covers large open spaces in the countryside where no urbanisation happens apart from occasional roads, cottages, and pastures. You can find it across the Scottish Highlands, numerous national parks such as Lake District, or in the majority of Wales.',\n", " 'Countryside agriculture': '“Countryside agriculture” features much of the English countryside and displays a high degree of agriculture including both fields and pastures. There are a few buildings scattered across the area but, for the most part, it is green space.',\n", " 'Urban buffer': '“Urban buffer” can be characterised as a green belt around cities. This signature includes mostly agricultural land in the immediate adjacency of towns and cities, often including edge development. It still feels more like countryside than urban, but these signatures are much smaller compared to other countryside types.',\n", " 'Open sprawl': '“Open sprawl” represents the transition between countryside and urbanised land. It is located in the outskirts of cities or around smaller towns and is typically made up of large open space areas intertwined with different kinds of human development, from highways to smaller neighbourhoods.',\n", " 'Disconnected suburbia': '“Disconnected suburbia” includes residential developments in the outskirts of cities or even towns and villages with convoluted, disconnected street networks, low built-up and population densities, and lack of jobs and services. This signature type is entirely car-dependent.',\n", " 'Accessible suburbia': '“Accessible suburbia” covers residential development on the urban periphery with a relatively legible and connected street network, albeit less so than other more urban signature types. Areas in this signature feature low density, both in terms of population and built-up area, lack of jobs and services. For these reasons, “accessible suburbia” largely acts as dormitories.',\n", " 'Warehouse/Park land': '“Warehouse/Park land” covers predominantly industrial areas and other work-related developments made of box-like buildings with large footprints. It contains many jobs of manual nature such as manufacturing or construction, and very little population live here compared to the rest of urban areas. Occasionally this type also covers areas of parks with large scale green open areas.',\n", " 'Gridded residential quarters': '“Gridded residential quarters” are areas with street networks forming a well-connected grid-like (high density of 4-way intersections) pattern, resulting in places with smaller blocks and higher granularity. This signature is mostly residential but includes some services and jobs, and it tends to be located away from city centres.',\n", " 'Connected residential neighbourhoods': '“Connected residential neighbourhoods” are relatively dense urban areas, both in terms of population and built-up area, that tend to be formed around well-connected street networks. They have access to services and some jobs but may be further away from city centres leading to higher dependency on cars and public transport for their residents.',\n", " 'Dense residential neighbourhoods': 'A “dense residential neighbourhood” is an abundant signature often covering large parts of cities outside of their centres. It has primarily residential purpose and high population density, varied street network patterns, and some services and jobs but not in high intensity.',\n", " 'Dense urban neighbourhoods': '“Dense urban neighbourhoods” are areas of inner-city with high population and built-up density of a predominantly residential nature but with direct access to jobs and services. This signature type tends to be relatively walkable and, in the case of some towns, may even form their centres.',\n", " 'Local urbanity': '“Local urbanity” reflects town centres, outer parts of city centres or even district centres. In all cases, this signature is very much urban in essence, combining high population and built-up density, access to amenities and jobs. Yet, it is on the lower end of the hierarchy of signature types denoting urban centres with only a local significance.',\n", " 'Regional urbanity': '“Regional urbanity” captures centres of mid-size cities with regional importance such as Liverpool, Plymouth or Newcastle upon Tyne. It is often encircled by “Local urbanity” signatures and can form outer rings of city centres in large cities. It features high population density, as well as a high number of jobs and amenities within walkable distance.',\n", " 'Metropolitan urbanity': 'Signature type “Metropolitan urbanity” captures the centre of the largest cities in Great Britain such as Glasgow, Birmingham or Manchester. It is characterised by a very high number of jobs in the area, high built-up density and often high population density. This type serves as the core centre of the entire metropolitan areas.',\n", " 'Concentrated urbanity': 'Concentrated urbanity” is a signature type found in the city centre of London and nowhere else in Great Britain. It reflects the uniqueness of London in the British context with an extremely high number of jobs and amenities located nearby, as well as high built-up and population densities. Buildings in this signature are large and tightly packed, forming complex shapes with courtyards and little green space.',\n", " 'Hyper concentrated urbanity': 'The epitome of urbanity in the British context. “Hyper concentrated urbanity” is a signature type present only in the centre of London, around the Soho district, and covering Oxford and Regent streets. This signature is the result of centuries of urban primacy, with a multitude of historical layers interwoven, very high built-up and population density, and extreme abundance of amenities, services and jobs.'}" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "portraits" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.8.8" } }, "nbformat": 4, "nbformat_minor": 5 }