Diseases percentage for every SA2

SA2_by_DISEASES.csv

+SA2_MAINCODE_2011,arthritis,asthma,circulatory_system_diseases,copd,diabetes_t2,high_cholestral,hypertension,respiratory_system_diseases
+203021037,14.376249392911900,11.863531296319700,17.114506693711900,1.990333522577840,3.621095638401750,34.793751130116900,9.417185587778180,29.753269909522500
+203021038,17.850005714571100,12.424971667568600,17.965641246159600,2.486118670115010,8.424310004142390,32.695682671664200,11.141735794677000,29.849253139366300
+203021039,14.376249392911900,11.863531296319700,17.114506693711900,1.990333522577840,3.621095638401750,34.793751130116900,9.417185587778180,29.753269909522500
+203021040,15.028217152628700,11.949927678527700,18.077309975269100,2.106186764005320,3.774885527578830,33.319508602319800,10.592554875264200,30.053010288722600
+203021041,14.014443636654900,12.190387602835900,17.299746363249900,1.912487818572950,3.560774909601300,33.916075557681400,10.104466404033500,31.514887915895600
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+203021044,14.332261177539000,14.051666669796700,17.099565570455100,1.927442074984310,3.543657342285330,33.188829834364000,10.037590428433400,30.655580487610000
+203021045,17.191095391626800,11.879944186774500,17.178226078097300,2.333891702885220,4.608792750831970,32.630190163140100,9.864856060915300,31.048807128769000
+203021046,13.516038105989700,11.701240254232900,14.920308613104400,1.862033512745440,3.369331266826620,33.490201863957600,9.857636995138950,29.741695361315600
+203021047,15.675617956451900,10.291516382732900,16.665330272057200,1.793627693401410,6.544821311966120,32.756211100741400,9.427819006125570,28.318053655321400
+203031048,14.539261614377700,14.286567951702700,17.287016600565000,2.023675728523240,3.502428190863480,32.938410273072800,9.793956173292150,30.766962265104700
+203031050,13.919878265919700,14.582845932213000,15.251895944219600,1.880614055353090,3.212177226916100,33.945876246168200,9.819857047991850,31.004171721514100
+203031051,17.476708286944700,14.329079078803900,17.583716768913700,2.126711656660280,4.077092790558270,32.894743329299200,10.013222617315200,31.602591337793800
+203031052,13.919878265919700,14.582845932213000,15.251895944219600,1.880614055353090,3.212177226916100,33.945876246168200,9.819857047991850,31.004171721514100
+204011061,14.562402917968500,13.009023398393000,17.257903181334700,2.066774672039220,3.559479970440660,34.250436192464600,9.691076275002090,30.592328768164300
+205011077,13.961741714841700,13.000410748005900,15.519580167890000,2.045831548430360,3.423188358372440,36.486009988042100,8.669851083532080,29.237963559934400
+205011078,13.961741714841700,13.000410748005900,15.519580167890000,2.045831548430360,3.423188358372440,36.486009988042100,8.669851083532080,29.237963559934400
+205031090,14.669407452505900,12.650047557496700,17.616275815349700,1.945568635978660,3.452643989035400,35.416314460207900,9.920466053404970,29.656181032288900
+205041094,16.682022399212400,12.645427576464300,17.320198512981300,2.045786500940900,3.810987050407160,36.839470656997900,10.269349362976900,30.443263938008500
+205041095,17.222016383865600,14.339052731221700,17.554654165797100,2.427476771510730,5.026729566722340,32.924335773216100,9.888302165199760,31.166319518772700
+205041096,17.222016383865600,14.339052731221700,17.554654165797100,2.427476771510730,5.026729566722340,32.924335773216100,9.888302165199760,31.166319518772700
+205041097,14.338234925664700,13.550501258690400,16.527028443767700,2.103926248917370,3.777632178013030,32.419654204450600,9.898534890515710,29.167012947707700
+205041098,14.338234925664700,13.550501258690400,16.527028443767700,2.103926248917370,3.777632178013030,32.419654204450600,9.898534890515710,29.167012947707700
+206021110,13.017653951837600,9.378824398851850,16.540156936760000,1.729575003245990,5.831483831560920,32.280882646267900,9.729080930968820,33.066435129472000
+206021111,13.017653951837600,9.378824398851850,16.540156936760000,1.729575003245990,5.831483831560920,32.280882646267900,9.729080930968820,33.066435129472000
+206021112,13.607202026564800,10.624098967719800,17.372378119418100,1.762388123900880,6.301701900777690,32.164560344186500,10.181261577838600,30.772339634014400
+206071139,11.887086591773100,10.636318207561400,16.235096476715300,1.698303407451640,4.908314289323410,32.130385932897000,9.738800428616580,28.513069573123100
+206071140,13.076741759486200,9.939637425157130,16.818179029188600,1.759218116906240,5.173174885408390,32.217763743197500,9.744160533569750,29.680528099834300
+206071141,12.622448327288900,9.006184498939790,18.366365705982200,2.168374986878040,6.142721397154850,32.132882494393000,9.555319500430310,28.532676044360800
+206071142,12.622448327288900,9.006184498939790,18.366365705982200,2.168374986878040,6.142721397154850,32.132882494393000,9.555319500430310,28.532676044360800
+206071143,13.076741759486200,9.939637425157130,16.818179029188600,1.759218116906240,5.173174885408390,32.217763743197500,9.744160533569750,29.680528099834300
+206071144,11.995682388394800,9.005692872818030,16.872313752635200,1.971666858524470,6.023124941523950,32.260946860755500,9.760016919329430,27.292551708120700
+206071145,11.887086591773100,10.636318207561400,16.235096476715300,1.698303407451640,4.908314289323410,32.130385932897000,9.738800428616580,28.513069573123100
+209021205,13.699652533410800,7.217199314919030,17.306030096015800,1.673206955774990,4.886169081660020,34.202431436151400,11.112430947470700,26.003883316888400
+209021206,15.852271066433300,10.131079160215600,17.728049902162000,1.886345892218280,7.058511873059060,31.717006525798300,10.074729031679600,26.302117303902600
+209021207,16.238956181157700,10.273461177317800,17.706446567181600,2.137683908177100,7.103536804811070,32.750514457995100,10.084873258535400,29.050310695097100
+209021208,16.199114241516400,9.337111281378380,17.573762887008300,1.831584728301790,7.474769367124330,32.178993031752800,9.879020447175830,25.743270068661900
+211011255,12.369535826810900,9.789153249289020,16.308518768789800,1.572762453019960,4.439441012800790,32.222009458799500,10.348458671853600,28.775609006389600
+211021262,12.334205680564300,11.410891936312200,14.657464860462000,1.613080461829430,3.442352801402070,34.881858073545500,9.689208461635880,30.309199402925500
+211051274,12.935443199769800,11.496548593346300,14.525755719903400,1.795129557071540,3.300868454308390,33.767347578276000,10.279983689094700,30.478768523807400
+211051275,13.601121335064500,11.395066184682200,15.844250780928400,1.923588555394540,3.522334154318660,33.573044082435100,9.860024098406300,30.148236438409700
+211051276,14.053358761897100,13.527046170942700,16.457906203833400,2.072679042152880,3.450453120135110,32.632412349626500,9.644627943917300,30.306681647586000
+211051277,14.498060606852900,11.552616484768600,17.052270558282800,1.917754675049350,3.478610267776420,37.080322966577700,9.699014741888680,30.458270202084300
+211051278,13.775590635942300,11.651663964641200,16.696472691387800,1.871215420871820,3.605446724248960,32.802908680479000,10.369250603407400,30.054993649687500
+211051279,13.622161288243000,11.604883289425900,16.512875516943000,1.815501908373540,3.477070306076710,32.674973065842000,10.552980558697100,30.807004310243700
+211051280,13.601121335064500,11.395066184682200,15.844250780928400,1.923588555394540,3.522334154318660,33.573044082435100,9.860024098406300,30.148236438409700
+211051281,13.601121335064500,11.395066184682200,15.844250780928400,1.923588555394540,3.522334154318660,33.573044082435100,9.860024098406300,30.148236438409700
+211051282,12.935443199769800,11.496548593346300,14.525755719903400,1.795129557071540,3.300868454308390,33.767347578276000,10.279983689094700,30.478768523807400
+211051283,13.622161288243000,11.604883289425900,16.512875516943000,1.815501908373540,3.477070306076710,32.674973065842000,10.552980558697100,30.807004310243700
+211051284,12.935443199769800,11.496548593346300,14.525755719903400,1.795129557071540,3.300868454308390,33.767347578276000,10.279983689094700,30.478768523807400
+211051285,13.775590635942300,11.651663964641200,16.696472691387800,1.871215420871820,3.605446724248960,32.802908680479000,10.369250603407400,30.054993649687500
+211051286,14.286670253098500,12.737479538200300,17.573847849527900,1.961068977114340,3.565386289207720,32.197053356248300,9.801821425848730,29.984491846881200
+212011289,13.283324692569900,11.450435279242900,14.571520298902100,1.802390413572470,3.410016153135250,32.889938587005100,10.039746305378000,29.331357835301700
+212041311,15.659355782026000,7.822862426286850,15.661461950759200,1.953004683851460,9.643488337611080,31.879830970664500,9.696922005906160,26.404491951139700
+212041312,14.856834191013500,8.763300663588980,16.474810921146700,1.754142052283610,6.756548847049820,32.019228176415600,10.107073999105800,30.023333790448400
+212041314,11.172071030494800,8.367091628149020,19.564201911977500,1.565329290844160,6.529302955271800,31.525140637815700,10.637960170607700,29.413438359596500
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+213031351,11.955179228855500,7.771686293107790,17.547319619129800,1.750646696391470,6.670565513472870,32.229116441253200,9.489436058338920,24.155404216501000
+213031352,12.557119380792000,11.075759494098700,17.289087939051300,1.763780014611720,6.014059982444300,32.026627131811900,9.996570408365330,27.109923392290100
+213051363,16.101488791781200,9.075590274996890,16.683330523085600,2.062445134008670,7.762244147257760,32.433721983881400,10.769097691749100,25.350557009800500

SA2_by_DISEASES.py

+import pandas as pandas
+
+df = pandas.read_csv("SA2_diseases_percentage_vic.csv", dtype = "string")
+
+sa2s = set(pandas.read_csv("SA2_to_LGA.csv", dtype = "string")["SA2_MAINCODE_2011"].unique())
+
+df = df[df["area_code"].isin(sa2s)]
+df = df.drop("area_name", axis = 1)
+df = df.rename(columns = {"area_code": "SA2_MAINCODE_2011", "arthritis0": "arthritis", "asthma_me0": "asthma", 
+    "circ_me_2_": "circulatory_system_diseases", "copd_me_2_": "copd", "diabetes_0": "diabetes_t2", "hg_choles0": "high_cholestral", 
+    "hypertens0": "hypertension", "respirtry0": "respiratory_system_diseases"})
+df = df.sort_values(["SA2_MAINCODE_2011"])
+
+df.to_csv(path_or_buf = "SA2_DISEASES.csv", index = False)
\ No newline at end of file

SA2_to_LGA.py

@@ -5,7 +5,7 @@ df = pandas.read_csv("2011_SA2_to_LGA_vic.csv", dtype = "string")
 # Keep only Victorian LGAs
 #df = df[df["LGA_CODE_2011"].str[0] == "2"]
 # Only ones in AQ_to_LGA.csv
-lgas = set(pandas.read_csv("AQ_to_LGA.csv", dtype = "string")["LGA_CODE"].unique())
+lgas = set(pandas.read_csv("AQ_to_LGA.csv", dtype = "string")["LGA_CODE_2011"].unique())
 print(lgas)
 df = df[df["LGA_CODE_2011"].isin(lgas)]