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PropertyPricePredictor

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hongaik commited on Nov 11, 2022

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1 Parent(s): e234abd

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app.py +287 -0
data/district.csv +29 -0
data/expressway.cpg +1 -0
data/expressway.dbf +0 -0
data/expressway.prj +1 -0
data/expressway.shp +0 -0
data/expressway.shx +0 -0
data/mall.csv +126 -0
data/mrt.csv +172 -0
data/pri_sch_latlong.csv +184 -0
data/sec_sch_latlong.csv +144 -0
model/encoder.sav +0 -0
requirements.txt +11 -0
utils.py +80 -0

app.py ADDED Viewed

	@@ -0,0 +1,287 @@

+import numpy as np
+import pandas as pd
+import geopandas as gpd
+from shapely.geometry import Point, LineString
+import pickle
+import folium
+import requests
+import streamlit as st
+import seaborn as sns
+from streamlit_folium import st_folium
+import matplotlib.pyplot as plt
+from utils import *
+########## Title for the Web App ##########
+st.title("Property Price Predictor")
+st.markdown("""This app predicts your house price based on a few indicators, and displays amenities within 2 km. Please note the following:
+- Only property types allowed are HDB, Condominium, Executive Condominium and Apartment.
+- Model was trained on **resale, leasehold** properties from 2021 onwards to account for COVID-19 effects; predictions for new and/or freehold properties will not be accurate.
+- Geospatial features are obtained from OneMap API with postal code. Newer postal codes may not be available (eg. property under construction)
+""")
+testing_postal = st.text_input('Test your postal code here')
+if st.button('Click to retrieve data!'):
+    result = test_postal(testing_postal)
+    if result == 'INVALID LOCATION':
+        st.error('Invalid postal code, you may attempt to search for the name or address instead.')
+    else:
+        st.success('SEARCHVAL: ' + result[0] + ' ADDRESS: ' + result[1] + ' LATITUDE: ' + str(result[2]) + ' LONGITUDE: ' + str(result[3]))
+st.header('Predict your property price here!')
+with st.form("inputs"):
+    input_postal = st.text_input('Enter your postal code here e.g. 123456')
+    input_storey = st.text_input('Enter your property storey here e.g. 5')
+    input_age_asof_transaction = st.text_input('Enter the age in years of your property here e.g. 12')
+    input_floor_area_sqft = st.text_input('Enter the floor area in square feet of your property here e.g. 756')
+    input_propertyType = st.selectbox(
+        'Enter your property type here',
+        ('HDB', 'Condominium', 'Executive Condominium', 'Apartment'))
+    propertyType_Apartment = 0
+    propertyType_Condominium = 0
+    propertyType_Executive_Condominium = 0
+    propertyType_HDB = 0
+    submitted = st.form_submit_button("Predict!")
+    if submitted:
+        # validate postal
+        if len(input_postal) == 6:
+            try:
+                validate = int(input_postal)
+            except:
+                st.error('Invalid postal code, please enter a 6 digit integer.')
+                st.stop()
+        else:
+            st.error('Invalid postal code, please enter a 6 digit integer.')
+            st.stop()
+        # validate storey
+        try:
+            input_storey = int(input_storey)
+        except:
+            st.error('Invalid storey, please enter an integer.')
+            st.stop()
+        # validate age
+        try:
+            input_age_asof_transaction = int(input_age_asof_transaction)
+        except:
+            st.error('Invalid age, please enter an integer.')
+            st.stop()
+        # validate floor area
+        try:
+            input_floor_area_sqft = float(input_floor_area_sqft)
+        except:
+            st.error('Invalid floor area, please enter a number.')
+            st.stop()
+        try:
+            lat, long = getSVY21(input_postal)
+        except ValueError:
+            st.error('This postal code does not exist. Please use the widget above to test if the postal code exists.')
+            st.stop()
+        latlong_df = pd.DataFrame({'lat': [lat], 'long': [long]})
+        latlong_geo = gpd.GeoDataFrame(latlong_df, crs="EPSG:4326",
+                                    geometry=[Point(xy) for xy in zip(latlong_df['long'], latlong_df['lat'])])
+        latlong_geo.to_crs(epsg=3857, inplace=True)
+        # Filter geosubset to only properties (sold since 2017)
+        geosubset = geosubset[(geosubset['storey'] <= input_storey + 5) & (geosubset['storey'] >= input_storey - 5)] # filter storey +- 5
+        geosubset = geosubset[(geosubset['age_asof_t'] <= input_age_asof_transaction + 3) & (geosubset['age_asof_t'] >= input_age_asof_transaction - 3)] # filter age +- 3
+        geosubset = geosubset[(geosubset['floor_area'] <= input_floor_area_sqft + 100) & (geosubset['floor_area'] >= input_floor_area_sqft - 100)] # filter floor area to +- 50m
+        geosubset = geosubset[geosubset['propertyTy'] == input_propertyType] # filter property type
+        geosubset['distance_to_property'] = geosubset.geometry.apply(lambda x: latlong_geo.distance(x)) # filter property radius within 1km
+        geosubset = geosubset[geosubset['distance_to_property'] <= 1000] # filter distances within 1km
+        if input_propertyType == 'Apartment':
+            propertyType_Apartment = 1
+        elif input_propertyType == 'Condominium':
+            propertyType_Condominium = 1
+        elif input_propertyType == 'Executive Condominium':
+            propertyType_Executive_Condominium = 1
+        elif input_propertyType == 'HDB':
+            propertyType_HDB = 1
+        latlong_geo['district'] = postal_final.loc[postal_final['2dpostal'] == input_postal[:2], 'district'].item()
+        latlong_geo['storey'] = input_storey
+        latlong_geo['age_asof_transaction'] = input_age_asof_transaction
+        latlong_geo['mindist_expway'] = latlong_geo.geometry.apply(lambda x: expressway.distance(x).min())
+        latlong_geo['mindist_mrt'] = latlong_geo.geometry.apply(lambda x: geo_mrt.distance(x).min())
+        latlong_geo['mindist_mall'] = latlong_geo.geometry.apply(lambda x: geo_mall.distance(x).min())
+        latlong_geo['mindist_prisch'] = latlong_geo.geometry.apply(lambda x: geo_pri.distance(x).min())
+        latlong_geo['n_prisch_2km'] = latlong_geo.geometry.apply(lambda x: (geo_pri.distance(x) < 2000).sum())
+        latlong_geo['mindist_secsch'] = latlong_geo.geometry.apply(lambda x: geo_sec.distance(x).min())
+        latlong_geo['propertyType_Apartment'] = propertyType_Apartment
+        latlong_geo['propertyType_Condominium'] = propertyType_Condominium
+        latlong_geo['propertyType_Executive_Condominium'] = propertyType_Executive_Condominium
+        latlong_geo['propertyType_HDB'] = propertyType_HDB
+        # Do Predictions, Convert to total price with CI (different CI for different property type)
+        latlong_geo_nolatlong = latlong_geo.drop(columns=['lat', 'long', 'geometry'])
+        latlong_geo_nolatlong_encoded = enc.transform(latlong_geo_nolatlong)
+        prediction_psf = xgb.predict(latlong_geo_nolatlong_encoded).item()
+        prediction_price = round(prediction_psf * input_floor_area_sqft)
+        if latlong_geo_nolatlong_encoded['propertyType_Apartment'].item() == 1:
+            st.success("The predicted price of your property is ${:,}, with 95% confidence interval being ${:,} - ${:,}.".format(
+                prediction_price, int(prediction_price - 2*sd_hdb*input_floor_area_sqft), int(prediction_price + 2*sd_hdb*input_floor_area_sqft)))
+        elif latlong_geo_nolatlong_encoded['propertyType_Condominium'].item() == 1:
+            st.success("The predicted price of your property is ${:,}, with 95% confidence interval being ${:,} - ${:,}.".format(
+                prediction_price, int(prediction_price - 2*sd_condo*input_floor_area_sqft), int(prediction_price + 2*sd_condo*input_floor_area_sqft)))
+        elif latlong_geo_nolatlong_encoded['propertyType_Executive_Condominium'].item() == 1:
+            st.success("The predicted price of your property is ${:,}, with 95% confidence interval being ${:,} - ${:,}.".format(
+                prediction_price, int(prediction_price - 2*sd_ec*input_floor_area_sqft), int(prediction_price + 2*sd_ec*input_floor_area_sqft)))
+        elif latlong_geo_nolatlong_encoded['propertyType_HDB'].item() == 1:
+            st.success("The predicted price of your property is ${:,}, with 95% confidence interval being ${:,} - ${:,}.".format(
+                prediction_price, int(prediction_price - 2*sd_hdb*input_floor_area_sqft), int(prediction_price + 2*sd_hdb*input_floor_area_sqft)))
+        # between Jan 2017 and Oct 2022, propertyType, age, floor area range, storey
+        # use geosubset to have boxplot and folium map
+        if len(geosubset) > 0:
+            st.markdown('There are ' + str(len(geosubset)) + ' resale ' + input_propertyType + 's transacted between Jan 2017 and Oct 2022 which are similar to yours (drag the markers around as they might be overlapping):')
+            map = folium.Map(location=[1.290270, 103.851959], zoom_start=11)
+            folium.Circle(
+                location=[latlong_geo['lat'].item(), latlong_geo['long'].item()],
+                tooltip='Your Home',
+                popup='Your Home',
+                color='crimson',
+                radius=10
+            ).add_to(map)
+            for index, row in geosubset.iterrows():
+                folium.Marker(
+                        [row['lat'], row['long']],
+                        tooltip=f'Resale date: {row["transactDa"].strftime("%b %Y")} <br>\n'
+                        f'Storey: {int(row["storey"])} <br>\n'
+                        f'Age: {int(row["age_asof_t"])} <br>\n'
+                        f'Area: {int(row["floor_area"])}sqft <br>\n'
+                        f'Resale Price: ${int(row["resale_pri"]):,}',
+                        icon=folium.Icon(color="blue", icon='usd', prefix='fa'),
+                        opacity=0.8,
+                        draggable=True,
+                        popup=f'Resale date: {row["transactDa"].strftime("%%b %%Y")} <br>\n'
+                        f'Storey: {int(row["storey"])} <br>\n'
+                        f'Age: {int(row["age_asof_t"])} <br>\n'
+                        f'Area: {int(row["floor_area"])}sqft <br>\n'
+                        f'Resale Price: ${int(row["resale_pri"]):,}'
+                    ).add_to(map)
+            st_folium(map, width=700, height=450)
+            fig, ax = plt.subplots()
+            sns.swarmplot(data=geosubset, y='resale_pri', orient='v', ax=ax)
+            plt.scatter(0, prediction_price, color='orange')
+            plt.text(0.05, prediction_price, 'Your predicted property price')
+            plt.ylabel('Resale Price ($)')
+            plt.title('Swarmplot of nearby similar properties')
+            st.pyplot(fig)
+        else:
+            st.markdown('Oops! There are no resale ' + input_propertyType + 's transacted between Jan 2017 and Oct 2022 which are similar to yours :(')
+        # Get folium visualisations
+        temp_mrt = latlong_geo.geometry.apply(lambda x: geo_mrt.distance(x)).melt().drop(columns=['variable'])
+        temp_mrt = temp_mrt[temp_mrt['value'] <= 2000]
+        temp_mrt = temp_mrt.merge(geo_mrt[['STN_NAME', 'lat','long']], how='left', left_index=True, right_index=True)
+        temp_mrt['category'] = 'MRT'
+        temp_mrt.columns = ['distance', 'name', 'lat', 'long', 'category']
+        temp_mall = latlong_geo.geometry.apply(lambda x: geo_mall.distance(x)).melt().drop(columns=['variable'])
+        temp_mall = temp_mall[temp_mall['value'] <= 2000]
+        temp_mall = temp_mall.merge(geo_mall[['mall', 'lat','long']], how='left', left_index=True, right_index=True)
+        temp_mall['category'] = 'Mall'
+        temp_mall.columns = ['distance', 'name', 'lat', 'long', 'category']
+        temp_pri = latlong_geo.geometry.apply(lambda x: geo_pri.distance(x)).melt().drop(columns=['variable'])
+        temp_pri = temp_pri[temp_pri['value'] <= 2000]
+        temp_pri = temp_pri.merge(geo_pri[['Name', 'lat','long']], how='left', left_index=True, right_index=True)
+        temp_pri['category'] = 'Primary School'
+        temp_pri.columns = ['distance', 'name', 'lat', 'long', 'category']
+        temp_sec = latlong_geo.geometry.apply(lambda x: geo_sec.distance(x)).melt().drop(columns=['variable'])
+        temp_sec = temp_sec[temp_sec['value'] <= 2000]
+        temp_sec = temp_sec.merge(geo_sec[['Name', 'lat','long']], how='left', left_index=True, right_index=True)
+        temp_sec['category'] = 'Secondary School'
+        temp_sec.columns = ['distance', 'name', 'lat', 'long', 'category']
+        temp_results = pd.concat([temp_mrt, temp_mall, temp_pri, temp_sec]).reset_index(drop=True).sort_values(['category', 'distance'])
+        st.markdown('**Here are the nearest amenities to your property:**')
+        for index, row in temp_results.groupby('category')[['category', 'distance', 'name']].head(2).iterrows():
+            if row['category'] == 'MRT':
+                st.markdown(row["name"] + ' :metro:: ' + str(int(row["distance"])) + 'm')
+            elif row['category'] == 'Mall':
+                st.markdown(row["name"] + ' :shopping_trolley:: ' + str(int(row["distance"])) + 'm')
+            elif row['category'] == 'Primary School':
+                st.markdown(row["name"] + ' :school:: ' + str(int(row["distance"])) + 'm')
+            elif row['category'] == 'Secondary School':
+                st.markdown(row["name"] + ' :mortar_board:: ' + str(int(row["distance"])) + 'm')
+        m = folium.Map(location=[1.290270, 103.851959], zoom_start=11)
+        folium.Marker(
+            [latlong_geo['lat'].item(), latlong_geo['long'].item()],
+            tooltip='Your Home',
+            popup='Your Home',
+            icon=folium.Icon(color="orange", icon='home', prefix='fa')
+        ).add_to(m)
+        folium.Circle(
+            radius=2000,
+            location=[latlong_geo['lat'].item(), latlong_geo['long'].item()],
+            color="black",
+            fill=False,
+            weight=1
+        ).add_to(m)
+        for index, row in temp_results.iterrows():
+            if row['category'] == 'MRT':
+                folium.Marker(
+                    [row['lat'], row['long']],
+                    tooltip=f'{row["name"]} <br>Distance: {int(row["distance"])}m</br>',
+                    icon=folium.Icon(color="red", icon='train', prefix='fa'),
+                    popup=f'{row["name"]} <br>Distance: {int(row["distance"])}m</br>'
+                ).add_to(m)
+            elif row['category'] == 'Mall':
+                folium.Marker(
+                    [row['lat'], row['long']],
+                    tooltip=f'{row["name"]} <br>Distance: {int(row["distance"])}m</br>',
+                    icon=folium.Icon(color="lightgreen", icon='shopping-cart', prefix='fa'),
+                    popup=f'{row["name"]} <br>Distance: {int(row["distance"])}m</br>'
+                ).add_to(m)
+            elif row['category'] == 'Primary School':
+                folium.Marker(
+                    [row['lat'], row['long']],
+                    tooltip=f'{row["name"]} <br>Distance: {int(row["distance"])}m</br>',
+                    icon=folium.Icon(color="lightblue", icon='book'),
+                    popup=f'{row["name"]} <br>Distance: {int(row["distance"])}m</br>'
+                ).add_to(m)
+            elif row['category'] == 'Secondary School':
+                folium.Marker(
+                    [row['lat'], row['long']],
+                    tooltip=f'{row["name"]} <br>Distance: {int(row["distance"])}m</br>',
+                    icon=folium.Icon(color="darkblue", icon='book', prefix='fa'),
+                    popup=f'{row["name"]} <br>Distance: {int(row["distance"])}m</br>'
+                ).add_to(m)
+        st_folium(m, width=700, height=450)

data/district.csv ADDED Viewed

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+district,town,2dpostal
+1,"RAFFLES PLACE, CECIL, MARINA, PEOPLE'S PARK","01, 02, 03, 04, 05, 06"
+2,"ANSON, TANJONG PAGAR","07, 08"
+3,"BUKIT MERAH,�QUEENSTOWN,�TIONG BAHRU","14, 15, 16"
+4,"TELOK BLANGAH, HARBOURFRONT","09, 10"
+5,"PASIR PANJANG, HONG LEONG GARDEN, CLEMENTI NEW TOWN","11, 12, 13"
+6,"HIGH STREET, BEACH ROAD (PARTIAL)",17
+7,"MIDDLE ROAD, GOLDEN MILE, BEACH ROAD (PARTIAL)","18, 19"
+8,"LITTLE INDIA,�FARRER PARK,�JALAN BESAR,�LAVENDER","20, 21"
+9,"ORCHARD, CAIRNHILL, RIVER VALLEY","22, 23"
+10,"ARDMORE,�BUKIT TIMAH, HOLLAND ROAD, TANGLIN","24, 25, 26, 27"
+11,"WATTEN ESTATE,�NOVENA, THOMSON","28, 29, 30"
+12,"BALESTIER,�TOA PAYOH, SERANGOON","31, 32, 33"
+13,"MACPHERSON, BRADDELL, POTONG PASIR, BIDADARI","34, 35, 36, 37"
+14,"GEYLANG, EUNOS, ALJUNIED","38, 39, 40, 41"
+15,"KATONG, JOO CHIAT, AMBER ROAD","42, 43, 44, 45"
+16,"BEDOK, UPPER EAST COAST, EASTWOOD, KEW DRIVE","46, 47, 48"
+17,"LOYANG, CHANGI","49, 50, 81"
+18,"SIMEI, TAMPINES, PASIR RIS","51, 52"
+19,"SERANGOON GARDEN,�HOUGANG,�PUNGGOL","53, 54, 55, 82"
+20,"BISHAN,�ANG MO KIO","56, 57"
+21,"UPPER BUKIT TIMAH, CLEMENTI PARK, ULU PANDAN","58, 59"
+22,"PENJURU, JURONG, PIONEER, TUAS","60, 61, 62, 63, 64"
+23,"HILLVIEW, DAIRY FARM, BUKIT PANJANG, CHOA CHU KANG, BUKIT BATOK","65, 66, 67, 68"
+24,"LIM CHU KANG, TENGAH","69, 70, 71"
+25,"KRANJI, WOODGROVE, WOODLANDS","72, 73"
+26,"UPPER THOMSON, SPRINGLEAF","77, 78"
+27,"YISHUN, SEMBAWANG, SENOKO, CANBERRA","75, 76"
+28,SELETAR,"79, 80"

data/expressway.cpg ADDED Viewed

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1	+ ISO-8859-1

data/expressway.dbf ADDED Viewed

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data/expressway.prj ADDED Viewed

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+ PROJCS["WGS_1984_Web_Mercator_Auxiliary_Sphere",GEOGCS["GCS_WGS_1984",DATUM["D_WGS_1984",SPHEROID["WGS_1984",6378137.0,298.257223563]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Mercator_Auxiliary_Sphere"],PARAMETER["False_Easting",0.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",0.0],PARAMETER["Standard_Parallel_1",0.0],PARAMETER["Auxiliary_Sphere_Type",0.0],UNIT["Meter",1.0]]

data/expressway.shp ADDED Viewed

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data/expressway.shx ADDED Viewed

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data/mall.csv ADDED Viewed

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+mall,lat,long,geometry
+I12 KATONG,1.30522306203042,103.905043928938,POINT (11566656.5810221 145309.33518929142)
+ION ORCHARD,1.30397974144505,103.832032328465,POINT (11558528.966835443 145170.89348854078)
+BUGIS+,1.30095171530648,103.855172625542,POINT (11561104.93292286 144833.72804790206)
+LOT ONE,1.38497459672379,103.745011766388,POINT (11548841.882176489 154189.68319064792)
+NORTHPOINT CITY,1.42790288991304,103.836177650973,POINT (11558990.422026208 158969.87913312975)
+SEMBAWANG SHOPPING CENTRE,1.44185307934021,103.824970378482,POINT (11557742.83415933 160523.29422201548)
+HOLLAND ROAD SHOPPING CENTRE,1.31027747574118,103.795371163103,POINT (11554447.864575457 145872.13654214397)
+MARINA BAY LINK MALL,1.28003113385646,103.854284863268,POINT (11561006.107678574 142504.26871829436)
+TEKKA CENTRE,1.30671098278725,103.85013440636,POINT (11560544.080929015 145475.01280651498)
+FUNAN,1.29134759697794,103.849989790085,POINT (11560527.982318923 143764.3288594248)
+HILLION MALL,1.37843100827586,103.762842789877,POINT (11550826.822631605 153461.04239749498)
+PEOPLE'S PARK COMPLEX,1.28404487854559,103.842590753293,POINT (11559704.325310875 142951.18860965632)
+THE SELETAR MALL,1.39147015374628,103.876125507257,POINT (11563437.397046026 154912.97758468584)
+BEDOK MALL,1.32475054237912,103.92918919889,POINT (11569344.420178223 147483.69700686546)
+CITY SQUARE MALL,1.31139349427341,103.856487111691,POINT (11561251.260851622 145996.40367746312)
+PLAZA SINGAPURA,1.30083497231103,103.845072925117,POINT (11559980.639414383 144820.72892664242)
+DJITSUN MALL,1.32611970329469,103.929554495615,POINT (11569385.084823638 147636.152093794)
+KALLANG WAVE MALL,1.30307515150401,103.873149707591,POINT (11563106.132542504 145070.16893048552)
+TIONG BAHRU PLAZA,1.28633177192832,103.827550771424,POINT (11558030.082187679 143205.82847351837)
+WISMA ATRIA,1.30368769989282,103.833203583562,POINT (11558659.35035643 145138.37515230273)
+THE ADELPHI,1.29118503658447,103.851184338699,POINT (11560660.95886236 143746.22812262655)
+ERA APAC CENTRE,1.33167653374942,103.849383945185,POINT (11560460.539973153 148254.90205003312)
+SELETAR MALL,1.39131549124709,103.876213231014,POINT (11563447.162409985 154895.75555609525)
+VIVOCITY,1.26429316783973,103.82230469365,POINT (11557446.091481214 140751.89441436098)
+THE PARAGON,1.30387230879994,103.835857545469,POINT (11558954.788044503 145158.93104354606)
+QUEENSWAY SHOPPING CENTRE,1.28761792586115,103.803391140455,POINT (11555340.644370455 143349.03860044328)
+KATONG SHOPPING CENTRE,1.3040973115095,103.901515916971,POINT (11566263.84452642 145183.98471877558)
+TAMPINES 1,1.37166822424446,103.932914115463,POINT (11569759.075994376 152707.995870831)
+FU LU SHOU COMPLEX,1.30151258571919,103.854497235401,POINT (11561029.748836277 144896.1799616709)
+THE MAJESTIC,1.28471077015851,103.843197416212,POINT (11559771.858718101 143025.33395335102)
+YEW TEE POINT,1.39708432396576,103.746598000147,POINT (11549018.46091082 155538.1292467078)
+BUGIS JUNCTION,1.29911287475873,103.855411173758,POINT (11561131.487988794 144628.9765507228)
+PARKWAY PARADE,1.30091736056425,103.90533928065,POINT (11566689.459424283 144829.90270946815)
+PIONEER MALL,1.34167331883255,103.697244542805,POINT (11543524.459170619 149368.04198144574)
+GREAT WORLD CITY,1.29342272650003,103.832022146655,POINT (11558527.833401538 143995.3899994859)
+WATERWAY POINT,1.4064128346795,103.902188891645,POINT (11566338.759724446 156576.88516463953)
+ORCHARD TOWERS,1.30758079522771,103.829476735628,POINT (11558244.479542155 145571.86508814918)
+HARBOURFRONT CENTRE,1.26396991176004,103.820243325181,POINT (11557216.620992908 140715.90095194863)
+HOLLAND PIAZZA,1.31067976097165,103.795260908624,POINT (11554435.591102999 145916.9304452947)
+DAWSON PLACE,1.29270339855062,103.810958956467,POINT (11556183.089795329 143915.29438199895)
+MILLENIA WALK,1.29267926922552,103.860302888543,POINT (11561676.031187767 143912.60763402536)
+NGEE ANN CITY,1.3022727300848,103.834899517575,POINT (11558848.140867176 144980.8206945949)
+MARINA SQUARE,1.29145526802576,103.857007335679,POINT (11561309.171921063 143776.31779079596)
+FAR EAST PLAZA,1.30717698071189,103.833792932243,POINT (11558724.9563515 145526.90095677547)
+JCUBE,1.33332312550425,103.740187071348,POINT (11548304.799581403 148438.24938659594)
+LEISURE PARK KALLANG,1.30230108405227,103.876473975883,POINT (11563476.18839603 144983.97785930184)
+ESPLANADE MALL,1.29036586550079,103.8547977273,POINT (11561063.19944146 143655.01526936505)
+PUNGGOL PLAZA,1.39417447299355,103.913120037036,POINT (11567555.609263161 155214.10999804424)
+CLEMENTI MALL,1.31489619639366,103.764423054189,POINT (11551002.736850135 146386.42512213686)
+CHANGI CITY POINT,1.33403637902708,103.962917615531,POINT (11573099.05034396 148517.66992054947)
+SUNTEC CITY,1.29350132535558,103.857307495824,POINT (11561342.585595561 144004.1418140981)
+TAMPINES MALL,1.35259361362837,103.944785968039,POINT (11571080.64457791 150584.01972618993)
+JURONG POINT,1.33945271661445,103.70668501289,POINT (11544575.367493331 149120.77799638768)
+CITYLINK MALL,1.2927777312893,103.854173501417,POINT (11560993.710934024 143923.57117126122)
+CAPITOL SINGAPORE,1.2935414355709,103.851569286784,POINT (11560703.811087163 144008.6080009693)
+ORCHARD CENTRAL,1.30083890839245,103.839434733899,POINT (11559352.998839002 144821.16720217513)
+TANG PLAZA,1.30505783063001,103.83306065595,POINT (11558643.439727442 145290.93694087424)
+MARINA BAY SANDS,1.28345419690844,103.860809048956,POINT (11561732.376707202 142885.41772234382)
+WESTGATE,1.33415767556867,103.742766484424,POINT (11548591.938531566 148531.17625094252)
+GEK POH SHOPPING CENTRE,1.34874357136408,103.697732091001,POINT (11543578.732787535 150155.31586859017)
+TANJONG PAGAR CENTRE,1.2755961982077,103.842393171342,POINT (11559682.3305887 142010.45113722907)
+OUR TAMPINES HUB,1.35218046898785,103.940598001519,POINT (11570614.442277445 150538.01586070567)
+LUCKY PLAZA,1.30450604646634,103.833962339817,POINT (11558743.814716375 145229.49667804473)
+CENTURY SQUARE,1.35227804040128,103.943727694121,POINT (11570962.838064237 150548.88048642385)
+CANBERRA PLAZA,1.44349544527985,103.830345369213,POINT (11558341.175390523 160706.1795339727)
+INTERNATIONAL PLAZA,1.27588674266836,103.845923793168,POINT (11560075.357612554 142042.80241770542)
+HDB HUB,1.33201387005935,103.84984949662,POINT (11560512.364921834 148292.46430390378)
+DUO,1.29953434891664,103.85840168774,POINT (11561464.390482482 144675.90690623393)
+ORCHARD GATEWAY,1.30160116957544,103.838868886519,POINT (11559290.008996794 144906.04361633817)
+THE CATHAY,1.29918373808483,103.847789785765,POINT (11560283.078958277 144636.86704838052)
+PEOPLE'S PARK CENTRE,1.28564781446701,103.843861556498,POINT (11559845.790476555 143129.6714953169)
+THE SHOPPES AT MARINA BAY SANDS,1.28423496027027,103.85898228297,POINT (11561529.022047842 142972.35372605218)
+JUNCTION 8,1.3504812534505,103.848760473211,POINT (11560391.135390485 150348.80743019588)
+WHEELOCK PLACE,1.30467628730252,103.830642027577,POINT (11558374.199248541 145248.45271486975)
+SIM LIM SQUARE,1.30290658774258,103.853031869482,POINT (11560866.625048349 145051.39964510401)
+COMPASS ONE,1.39205314156706,103.89507054384,POINT (11565546.348871507 154977.89464305568)
+OASIS TERRACES,1.40278015725693,103.913215101343,POINT (11567566.191773407 156172.3758193433)
+ONE RAFFLES PLACE,1.28434954622306,103.851072545834,POINT (11560648.514137553 142985.1125811013)
+HOUGANG MALL,1.37249493810003,103.893775562605,POINT (11565402.192219839 152800.0516308496)
+IMM,1.33487526118006,103.746894773008,POINT (11549051.497514585 148611.07918863875)
+UNITED SQUARE,1.31724362960663,103.844003130499,POINT (11559861.550422255 146647.80914341682)
+GOLDEN MILE COMPLEX,1.3027512163519,103.865163649543,POINT (11562217.128627157 145034.09930866418)
+SUN PLAZA,1.44820036592783,103.819530140823,POINT (11557137.229673335 161230.09570974388)
+600 @ TOA PAYOH,1.33403623894465,103.850977706475,POINT (11560637.956668403 148517.6543224169)
+MUSTAFA CENTRE,1.31011213190394,103.855290873926,POINT (11561118.096272754 145853.72573699447)
+321 CLEMENTI,1.31200212030821,103.764986676365,POINT (11551065.478983767 146064.1733763485)
+JUNCTION 10,1.38055127973087,103.760106974822,POINT (11550522.273092777 153697.1383636429)
+PALAIS RENAISSANCE,1.30665484543191,103.829588045188,POINT (11558256.870465694 145468.76199922094)
+DOWNTOWN EAST,1.37595122154029,103.955598940037,POINT (11572284.33911469 153184.91403746555)
+AMK HUB,1.36938922690344,103.84847796594,POINT (11560359.68682493 152454.22645013712)
+LIAT TOWERS,1.30508722710852,103.830722581168,POINT (11558383.166433275 145294.21019098454)
+SQUARE 2,1.27822949964567,103.850812513482,POINT (11560619.567468539 142303.66172543532)
+EASTPOINT MALL,1.34269199750599,103.953050756306,POINT (11572000.676599305 149481.47189381268)
+WHITE SANDS,1.37228761596577,103.949733905672,POINT (11571631.446475692 152776.96601424794)
+HEARTLAND MALL,1.35954177325561,103.885167372726,POINT (11564443.932905857 151357.70200382103)
+ALEXANDRA RETAIL CENTRE,1.27414893629254,103.801399416665,POINT (11555118.926692354 141849.30278758265)
+JEM,1.33305999269581,103.743503708169,POINT (11548674.005903462 148408.9496448728)
+WEST MALL,1.35009714832628,103.74921385957,POINT (11549309.657049773 150306.03716653708)
+JEWEL CHANGI AIRPORT,1.36006289399606,103.989989170512,POINT (11576112.642059429 151415.7292406353)
+THE CENTREPOINT,1.30145045537088,103.840034074858,POINT (11559419.717169369 144889.26185821815)
+RAFFLES CITY,1.29408304748297,103.853339531257,POINT (11560900.873800479 144068.91533836423)
+CAUSEWAY POINT,1.43600784474269,103.78568873405,POINT (11553370.021503637 159872.40042875698)
+NEX,1.35076935257845,103.872296143862,POINT (11563011.114262832 150380.88739109543)
+THE STAR VISTA,1.30681500712523,103.788462732266,POINT (11553678.821572501 145486.59575529105)
+PENINSULA PLAZA,1.29231742228801,103.850803179769,POINT (11560618.528444361 143872.31676603836)
+ROCHESTER MALL,1.30540765569962,103.788446680148,POINT (11553677.0346589 145329.88939636093)
+HOUGANG 1,1.35659543728082,103.889837028233,POINT (11564963.756579075 151029.62522742926)
+THOMSON PLAZA,1.35436282723449,103.83030941613,POINT (11558337.17311163 150781.02264811573)
+CAPITOL PIAZZA,1.29307884763132,103.851261982149,POINT (11560669.602091677 143957.09982545662)
+THE CLEMENTI MALL,1.31489619639366,103.764423054189,POINT (11551002.736850135 146386.42512213686)
+CHINATOWN POINT,1.28299209695303,103.843245630659,POINT (11559777.22592579 142833.96408653253)
+NOVENA SQUARE,1.32057156550961,103.843219261065,POINT (11559774.290476015 147018.37144736745)
+WEST COAST PLAZA,1.30362457527941,103.765858386923,POINT (11551162.517359205 145131.34633313888)
+VELOCITY@NOVENA SQUARE,1.31978949204523,103.844033569199,POINT (11559864.938842839 146931.28831189274)
+CATHAY CINELEISURE ORCHARD,1.30152101873533,103.836429655016,POINT (11559018.474987952 144897.1189629879)
+CHANGE ALLEY,1.28412271103554,103.852544637414,POINT (11560812.38662264 142959.8550591836)
+FORUM THE SHOPPING MALL,1.30609752164563,103.828678556041,POINT (11558155.626596967 145406.70486913418)
+SOUTH BEACH AVENUE,1.29443171770814,103.85601091893,POINT (11561198.251315948 144107.73903505644)
+JUNCTION NINE,1.4331228398318,103.84166098599,POINT (11559600.82408815 159551.14245872086)
+MUSTAFA CENTRE,1.31011213190394,103.855290873926,POINT (11561118.096272754 145853.72573699447)
+ORCHARD ROAD SHAW HOUSE,1.30580981580562,103.831507365654,POINT (11558470.528242638 145374.66928016834)
+SHAW CENTRE,1.30615048740141,103.83185337296,POINT (11558509.045599751 145412.60252243307)
+HILTON SINGAPORE ORCHARD,1.30206450556085,103.836340953476,POINT (11559008.600777686 144957.63525897707)
+CITY GATE,1.30231590504573,103.862331661034,POINT (11561901.873108402 144985.62815102638)
+MYVILLAGE AT SERANGOON GARDEN,1.36511490572797,103.865159501442,POINT (11562216.666862663 151978.27568578548)

data/mrt.csv ADDED Viewed

	@@ -0,0 +1,172 @@

+STN_NAME,STN_NO,lat,long,geometry
+ESPLANADE MRT STATION,CC3,1.2932599009494317,103.855611730623,POINT (11561153.813876882 143977.25972322148)
+PAYA LEBAR MRT STATION,EW8/CC9,1.31736940114175,103.89227219447312,POINT (11565234.838044923 146661.81366790616)
+DHOBY GHAUT MRT STATION,NS24/NE6/CC1,1.2990442033847656,103.84583316073905,POINT (11560065.268456714 144621.33012301076)
+DAKOTA MRT STATION,CC8,1.3083751546214861,103.88866829966075,POINT (11564833.654309537 145660.31581804075)
+LAVENDER MRT STATION,EW11,1.3073717303890142,103.86283780108813,POINT (11561958.216361497 145548.58603583908)
+RENJONG LRT STATION,SW8,1.3867475127345048,103.89042878872309,POINT (11565029.631055502 154387.10104518078)
+DOVER MRT STATION,EW22,1.3113946904069214,103.77864915459556,POINT (11552586.379103368 145996.53686532134)
+HOUGANG MRT STATION,NE14,1.371281175152925,103.8923475339162,POINT (11565243.224793361 152664.89741662212)
+PHOENIX LRT STATION,BP5,1.3786249497953063,103.75803362284962,POINT (11550291.468606979 153482.63811900956)
+ALJUNIED MRT STATION,EW9,1.3164324723857483,103.88290604375914,POINT (11564192.202916747 146557.4876806285)
+COVE LRT STATION,PE1,1.3993617069380282,103.90591743982358,POINT (11566753.819809085 155791.72186749076)
+PASIR RIS MRT STATION,EW1,1.3729518745158271,103.94925763848777,POINT (11571578.428655261 152850.9321622951)
+ADMIRALTY MRT STATION,NS10,1.4405870900082878,103.8009770091412,POINT (11555071.904501896 160382.3203376982)
+KEMBANGAN MRT STATION,EW6,1.3210380680383345,103.9129475274572,POINT (11567536.405584693 147070.31607272758)
+PUNGGOL POINT LRT STATION,PW3,1.4169108528743335,103.90653551174151,POINT (11566822.623260263 157745.87399860815)
+MARSILING MRT STATION,NS8,1.4325651685513625,103.77419400298993,POINT (11552090.433895223 159489.04335861353)
+COMPASSVALE LRT STATION,SE1,1.3944787834858998,103.9005552779689,POINT (11566156.906681871 155247.99572051817)
+KHATIB MRT STATION,NS14,1.4175768090823964,103.83303805986112,POINT (11558640.924342334 157820.03058972285)
+LAYAR LRT STATION,SW6,1.392092872617292,103.88015787537157,POINT (11563886.27821123 154982.3187890766)
+TAMPINES WEST MRT STATION,DT31,1.3455175068462677,103.9384294702698,POINT (11570373.042483013 149796.09272306375)
+TAMPINES MRT STATION,EW2/DT32,1.353289191281307,103.94515900808243,POINT (11571122.17120559 150661.4726686996)
+TAMPINES EAST MRT STATION,DT33,1.3562130027776913,103.95480497267452,POINT (11572195.95507219 150987.0408807443)
+TAI SENG MRT STATION,CC11,1.335453104061741,103.88816447597783,POINT (11564777.568913706 148675.42183319925)
+SUMANG LRT STATION,PW6,1.408353297018006,103.89851028717388,POINT (11565929.259347893 156792.9616271752)
+STEVENS MRT STATION,DT10,1.320065954923104,103.82602302655928,POINT (11557860.014407277 146962.0721869328)
+STADIUM MRT STATION,CC6,1.3028541001828107,103.87534796324088,POINT (11563350.841242082 145045.5552457105)
+SIXTH AVENUE MRT STATION,DT7,1.3307848582698434,103.79732046012039,POINT (11554664.85932684 148155.6143914006)
+SOUTH VIEW LRT STATION,BP2,1.3802982863129039,103.74529180004235,POINT (11548873.055380294 153668.96708927798)
+SOO TECK LRT STATION,PW7,1.4052096467859656,103.89723440867311,POINT (11565787.229202872 156442.9065743286)
+SOMERSET MRT STATION,NS23,1.3002576150886098,103.83907542830768,POINT (11559313.001123536 144756.4412536795)
+SIMEI MRT STATION,EW3,1.343197438643703,103.95337711850748,POINT (11572037.007073388 149537.75280291872)
+SERANGOON MRT STATION,NE12/CC13,1.3496172245316762,103.87363463482953,POINT (11563160.11439577 150252.59746399353)
+SENGKANG MRT STATION,NE16,1.3915276814947555,103.89541608066608,POINT (11565584.813855035 154919.3834334129)
+BRADDELL MRT STATION,NS18,1.3404441148884796,103.84679989936878,POINT (11560172.885308705 149231.17013437828)
+NOVENA MRT STATION,NS20,1.320430081393632,103.84381813023575,POINT (11559840.956287153 147002.6173237617)
+FARRER PARK MRT STATION,NE8,1.312448228414031,103.85427015829734,POINT (11561004.470728727 146113.8469306267)
+BEDOK MRT STATION,EW5,1.324011319398632,103.93017252059741,POINT (11569453.883049976 147401.3850926784)
+REDHILL MRT STATION,EW18,1.2896195393319383,103.81679002803264,POINT (11556832.201712795 143571.91355870623)
+CHANGI AIRPORT MRT STATION,CG2,1.3573079313565826,103.98837058050897,POINT (11575932.46144449 151108.96195398265)
+CORAL EDGE LRT STATION,PE3,1.3939263508217195,103.91256353528017,POINT (11567493.659771075 155186.48098662618)
+CLEMENTI MRT STATION,EW23,1.315078227515149,103.76523302884567,POINT (11551092.902816473 146406.69407190688)
+BUKIT BATOK MRT STATION,NS2,1.34899664622402,103.7495406556263,POINT (11549346.035820354 150183.49584195326)
+OASIS LRT STATION,PE6,1.402350879683705,103.91263185203226,POINT (11567501.264757132 156124.57453696936)
+NIBONG LRT STATION,PW5,1.4117555857480237,103.90029894818544,POINT (11566128.372180901 157171.8173986583)
+MERIDIAN LRT STATION,PE2,1.3968523393495353,103.90899093869116,POINT (11567095.960137978 155512.2971595746)
+BUKIT GOMBAK MRT STATION,NS3,1.3586719215924352,103.75191010878359,POINT (11549609.802139282 151260.8433106341)
+EUNOS MRT STATION,EW7,1.319779231523703,103.90336181865256,POINT (11566469.329361666 146930.14581277402)
+CHINESE GARDEN MRT STATION,EW25,1.3421449755958947,103.7328143945828,POINT (11547484.076958116 149420.56097565332)
+KADALOOR LRT STATION,PE5,1.3996385100843882,103.9163949789851,POINT (11567920.174133312 155822.5446471391)
+CHENG LIM LRT STATION,SW1,1.3962489158283502,103.8939079084962,POINT (11565416.924897054 155445.10440144964)
+SAM KEE LRT STATION,PW1,1.409613764005498,103.9048311129408,POINT (11566632.890453659 156933.31860778105)
+KRANJI MRT STATION,NS7,1.4252396282240647,103.76218063472041,POINT (11550753.111856747 158673.31427826764)
+ANG MO KIO MRT STATION,NS16,1.3699486593657557,103.8496163526122,POINT (11560486.411449607 152516.51998526446)
+RIVIERA LRT STATION,PE4,1.394636478299355,103.9162237902967,POINT (11567901.11749569 155265.55542793244)
+BANGKIT LRT STATION,BP9,1.3800154937551705,103.77266121865229,POINT (11551919.80512326 153637.47763038703)
+PASIR PANJANG MRT STATION,CC26,1.2762296708847953,103.79134196548895,POINT (11553999.336348757 142080.98648170006)
+HOLLAND VILLAGE MRT STATION,CC21,1.3119456172770734,103.79623333609268,POINT (11554543.841233645 146057.88183834363)
+LABRADOR PARK MRT STATION,CC27,1.2723234942723962,103.80292770505237,POINT (11555289.054977419 141646.04532671935)
+BOTANIC GARDENS MRT STATION,CC19/DT9,1.3221094921518408,103.81498942390112,POINT (11556631.759377753 147189.6181943206)
+ONE-NORTH MRT STATION,CC23,1.2996564796266807,103.78739399247746,POINT (11553559.850003451 144689.5059327703)
+KENT RIDGE MRT STATION,CC24,1.2934009384330032,103.78449793871876,POINT (11553237.462773722 143992.96394482808)
+HAW PAR VILLA MRT STATION,CC25,1.2825029020151386,103.78182132891398,POINT (11552939.503933202 142779.49350457196)
+MARINA BAY MRT STATION,NS27/TE20/CE2,1.275950352815708,103.85514510996279,POINT (11561101.869902594 142049.8852230529)
+KING ALBERT PARK MRT STATION,DT6,1.335638111428803,103.78387153256621,POINT (11553167.73155979 148696.02235539054)
+LITTLE INDIA MRT STATION,NE7/DT12,1.3071673594980848,103.84861049976973,POINT (11560374.44042337 145525.82964935843)
+ROCHOR MRT STATION,DT13,1.3039275604923852,103.85243888615356,POINT (11560800.614446178 145165.08322684388)
+SENJA LRT STATION,BP13,1.3826992422861197,103.76236875421941,POINT (11550774.053223584 153936.3179973449)
+MOUNTBATTEN MRT STATION,CC7,1.3061937868831155,103.88254701483167,POINT (11564152.235999363 145417.42385146447)
+CHOA CHU KANG MRT STATION,NS4,1.3851720516680506,103.74436906787206,POINT (11548770.33730496 154211.67019864143)
+BOON KENG MRT STATION,NE9,1.3194470902702067,103.86168108598112,POINT (11561829.451424792 146893.16220894022)
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data/pri_sch_latlong.csv ADDED Viewed

	@@ -0,0 +1,184 @@

+Name,lat,long,geometry
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+PAYA LEBAR METHODIST GIRLS' SCHOOL (PRIMARY),1.34947276268396,103.884971343143,POINT (11564422.110992495 150236.51158272126)
+PEI CHUN PUBLIC SCHOOL,1.33677864390672,103.855341310212,POINT (11561123.710814428 148823.02038434843)
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+PUNGGOL VIEW PRIMARY SCHOOL,1.40514582647962,103.905156371376,POINT (11566669.098057041 156435.79999321717)
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+SINGAPORE CHINESE GIRLS� SCHOOL (PRIMARY),1.32080725235992,103.827744749548,POINT (11558051.675733667 147044.61495907264)
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data/sec_sch_latlong.csv ADDED Viewed

	@@ -0,0 +1,144 @@

+Name,lat,long,geometry
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+ANGLO-CHINESE SCHOOL (INDEPENDENT),1.30370409257783,103.780363417671,POINT (11552777.209996013 145140.2004501405)
+ANG MO KIO SECONDARY SCHOOL,1.36733710171069,103.842154973672,POINT (11559655.814545367 152225.71975491787)
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+CHIJ ST. NICHOLAS GIRLS' SCHOOL,1.37347687878916,103.834253269436,POINT (11558776.200853419 152909.39216023145)
+CHIJ ST. THERESA'S CONVENT,1.27535177510054,103.822440701642,POINT (11557461.231821628 141983.23533812325)
+CHUA CHU KANG SECONDARY SCHOOL,1.38319029263484,103.751878290333,POINT (11549606.260125564 153990.99739923218)
+CHRIST CHURCH SECONDARY SCHOOL,1.42656780901455,103.793451105242,POINT (11554234.124712078 158821.21248545684)
+CHUNG CHENG HIGH SCHOOL (MAIN),1.30509154753048,103.891653229373,POINT (11565165.93516516 145294.69126295196)
+CHUNG CHENG HIGH SCHOOL (YISHUN),1.41922603586175,103.837390782849,POINT (11559125.46724891 158003.67794612917)
+CLEMENTI TOWN SECONDARY SCHOOL,1.31553912945073,103.762020598524,POINT (11550735.296708854 146458.01496312665)
+COMMONWEALTH SECONDARY SCHOOL,1.31920395934801,103.745637393049,POINT (11548911.526617816 146866.08982159942)
+COMPASSVALE SECONDARY SCHOOL,1.39614083952009,103.899847164494,POINT (11566078.079850422 155433.06982890505)
+CRESCENT GIRLS' SCHOOL,1.29331947077104,103.817544461755,POINT (11556916.184890606 143983.89269511588)
+DAMAI SECONDARY SCHOOL,1.33692798510393,103.927091653438,POINT (11569110.92248659 148839.64949665839)
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+DUNEARN SECONDARY SCHOOL,1.36357900792871,103.74472109107,POINT (11548809.524348103 151807.25183950562)
+DUNMAN HIGH SCHOOL,1.29996216014962,103.88294155989,POINT (11564196.15655435 144723.5428911554)
+DUNMAN SECONDARY SCHOOL,1.36065258337022,103.956213906966,POINT (11572352.79692008 151481.39166813152)
+EAST SPRING SECONDARY SCHOOL,1.35622508992581,103.960640700298,POINT (11572845.585299645 150988.3867929523)
+EDGEFIELD SECONDARY SCHOOL,1.40059309981824,103.902687385465,POINT (11566394.251802653 155928.8408259741)
+EVERGREEN SECONDARY SCHOOL,1.44149131273737,103.794137756171,POINT (11554310.562343847 160483.00979618495)
+FAIRFIELD METHODIST SECONDARY SCHOOL,1.30163374395823,103.784099647149,POINT (11553193.12515899 144909.67071594935)
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+FUCHUN SECONDARY SCHOOL,1.43070452883799,103.777625748539,POINT (11552472.454062277 159281.85321826424)
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+GAN ENG SENG SCHOOL,1.28907114485773,103.823733673089,POINT (11557605.164744718 143510.8511047384)
+GEYLANG METHODIST SCHOOL (SECONDARY),1.31764900474601,103.882661129303,POINT (11564164.939164205 146692.94722955022)
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+HAI SING CATHOLIC SCHOOL,1.37434641160381,103.954957944437,POINT (11572212.983810896 153006.21594618028)
+HILLGROVE SECONDARY SCHOOL,1.35273576615912,103.752986488399,POINT (11549729.62416997 150599.84848447377)
+HOLY INNOCENTS' HIGH SCHOOL,1.37154508822261,103.896398814264,POINT (11565694.211258741 152694.2845029248)
+HOUGANG SECONDARY SCHOOL,1.37764019332164,103.882533963338,POINT (11564150.783113735 153372.98381138817)
+HUA YI SECONDARY SCHOOL,1.35234365488339,103.721832320169,POINT (11546261.558026519 150556.18669209132)
+HWA CHONG INSTITUTION,1.3249477928719,103.805704361472,POINT (11555598.150956161 147505.6607027077)
+JUNYUAN SECONDARY SCHOOL,1.35361315263537,103.933886165824,POINT (11569867.284145588 150697.54594577954)
+JURONG SECONDARY SCHOOL,1.33002032220942,103.723952961648,POINT (11546497.626756115 148070.483677783)
+JURONG WEST SECONDARY SCHOOL,1.33525634688323,103.702098904443,POINT (11544064.844236288 148653.5129742614)
+JURONGVILLE SECONDARY SCHOOL,1.35128862770284,103.728907710089,POINT (11547049.186829578 150438.70890750457)
+JUYING SECONDARY SCHOOL,1.3387227734133,103.687310264575,POINT (11542418.580376657 149039.49889353552)
+KENT RIDGE SECONDARY SCHOOL,1.30122773426098,103.764889617566,POINT (11551054.674447687 144864.46226133357)
+KRANJI SECONDARY SCHOOL,1.39005109871311,103.741190664845,POINT (11548416.519098451 154754.96255238494)
+KUO CHUAN PRESBYTERIAN SECONDARY SCHOOL,1.35017129930314,103.854983746416,POINT (11561083.906994732 150314.2939078006)
+LOYANG VIEW SECONDARY SCHOOL,1.36658417167238,103.956944585725,POINT (11572434.135707464 152141.88010671528)
+MANJUSRI SECONDARY SCHOOL,1.32747123084846,103.901719963831,POINT (11566286.558918973 147786.64380123367)
+MARIS STELLA HIGH SCHOOL,1.34139473351039,103.877852484979,POINT (11563629.64332665 149337.02150254181)
+MARSILING SECONDARY SCHOOL,1.43664424769955,103.776008090454,POINT (11552292.377187978 159943.26674814863)
+MAYFLOWER SECONDARY SCHOOL,1.36827266209722,103.835360726863,POINT (11558899.482450265 152329.89554453458)
+MERIDIAN SECONDARY SCHOOL,1.3672468492013,103.948972483629,POINT (11571546.685361587 152215.6700301149)
+METHODIST GIRLS' SCHOOL (SECONDARY),1.35096755912522,103.885120050588,POINT (11564438.66502955 150402.95777690993)
+MONTFORT SECONDARY SCHOOL,1.37396131656912,103.888928372577,POINT (11564862.605494143 152963.3350308644)
+NAN CHIAU HIGH SCHOOL,1.38879582498399,103.890004423764,POINT (11564982.390964346 154615.18502305483)
+NAN HUA HIGH SCHOOL,1.30809529518605,103.768561446725,POINT (11551463.420599947 145629.15388546584)
+NANYANG GIRLS' HIGH SCHOOL,1.33058326666479,103.802420979943,POINT (11555232.646596272 148133.1672629472)
+NAVAL BASE SECONDARY SCHOOL,1.41937881620441,103.831050390247,POINT (11558419.657973025 158020.6905955229)
+NEW TOWN SECONDARY SCHOOL,1.30977590011357,103.77318863421,POINT (11551978.51675458 145816.2868008886)
+NGEE ANN SECONDARY SCHOOL,1.35447525755806,103.956747262496,POINT (11572412.16978609 150793.5418322182)
+NORTH VISTA SECONDARY SCHOOL,1.381131285358,103.899188813886,POINT (11566004.792595975 153761.72304987357)
+NORTHBROOKS SECONDARY SCHOOL,1.42081285020652,103.845147332528,POINT (11559988.922409488 158180.375576229)
+NORTHLAND SECONDARY SCHOOL,1.43580183362637,103.840104687784,POINT (11559427.577764334 159849.4601725573)
+ORCHID PARK SECONDARY SCHOOL,1.41532032779634,103.837859241343,POINT (11559177.615809917 157568.76346340694)
+OUTRAM SECONDARY SCHOOL,1.28651357464735,103.837127264403,POINT (11559096.132509686 143226.0717617956)
+PASIR RIS CREST SECONDARY SCHOOL,1.37284060102246,103.959728202919,POINT (11572744.006556064 152838.54169681272)
+PASIR RIS SECONDARY SCHOOL,1.37284060102246,103.959728202919,POINT (11572744.006556064 152838.54169681272)
+PAYA LEBAR METHODIST GIRLS' SCHOOL (SECONDARY),1.35096755912522,103.885120050588,POINT (11564438.66502955 150402.95777690993)
+PEI HWA SECONDARY SCHOOL,1.39037504993234,103.878461745339,POINT (11563697.465879684 154791.03525520363)
+PEICAI SECONDARY SCHOOL,1.35951583222214,103.870010749055,POINT (11562756.705276655 151354.81344805082)
+PEIRCE SECONDARY SCHOOL,1.36665944653812,103.83021606804,POINT (11558326.781649785 152150.262050655)
+PING YI SECONDARY SCHOOL,1.3270167275387,103.920700671987,POINT (11568399.481685797 147736.03514635738)
+PRESBYTERIAN HIGH SCHOOL,1.38201194250223,103.843149382823,POINT (11559766.511665696 153859.78586195203)
+PUNGGOL SECONDARY SCHOOL,1.40205738421399,103.909213706482,POINT (11567120.75853502 156091.8929842118)
+QUEENSTOWN SECONDARY SCHOOL,1.29352126774652,103.813190980055,POINT (11556431.557524582 144006.36235675865)
+QUEENSWAY SECONDARY SCHOOL,1.30022271592188,103.802207291625,POINT (11555208.858921524 144752.55529563106)
+RAFFLES GIRLS' SCHOOL (SECONDARY),1.34217479932295,103.84313404727,POINT (11559764.804519746 149423.8818488619)
+RAFFLES INSTITUTION,1.34610222088556,103.844023836251,POINT (11559863.855376024 149861.20075219436)
+REGENT SECONDARY SCHOOL,1.39327908335682,103.751034411529,POINT (11549512.319966812 155114.4061831275)
+RIVERSIDE SECONDARY SCHOOL,1.44110157139127,103.78830823641,POINT (11553661.623172482 160439.61025726734)
+RIVER VALLEY HIGH SCHOOL,1.34407801149725,103.709022156436,POINT (11544835.537122784 149635.80468490944)
+ST. ANDREW'S SECONDARY SCHOOL,1.33069360968075,103.866249138562,POINT (11562337.96471201 148145.45390457948)
+ST. PATRICK'S SCHOOL,1.30788341871801,103.917638193713,POINT (11568058.56816377 145605.56175767496)
+SEMBAWANG SECONDARY SCHOOL,1.44531502131387,103.816843258118,POINT (11556838.12725879 160908.79819277974)
+SENGKANG SECONDARY SCHOOL,1.38652129134849,103.898365549236,POINT (11565913.147194348 154361.91081902673)
+SERANGOON GARDEN SECONDARY SCHOOL,1.36932570490947,103.869270301476,POINT (11562674.279029202 152447.15319408747)
+SERANGOON SECONDARY SCHOOL,1.36932570490947,103.869270301476,POINT (11562674.279029202 152447.15319408747)
+SINGAPORE CHINESE GIRLS' SCHOOL,1.3206340835184,103.828164966953,POINT (11558098.454121213 147025.33276929165)
+SINGAPORE SPORTS SCHOOL,1.42641140556342,103.789444793951,POINT (11553788.144179204 158803.79633543073)
+SPRINGFIELD SECONDARY SCHOOL,1.34957303471476,103.930354460693,POINT (11569474.136528773 150247.67691109842)
+ST. ANTHONY'S CANOSSIAN SECONDARY SCHOOL,1.33466313498855,103.941977166932,POINT (11570767.97026894 148587.4589998603)
+ST. GABRIEL'S SECONDARY SCHOOL,1.34648798732177,103.876094163287,POINT (11563433.907851245 149904.155933149)
+ST. HILDA'S SECONDARY SCHOOL,1.34973922385379,103.937608032148,POINT (11570281.600409577 150266.1821353054)
+ST. MARGARET'S SECONDARY SCHOOL,1.32006821363359,103.80995114006,POINT (11556070.900186088 146962.32369218295)
+MALCOLM ROAD SAINT JOSEPH'S INSTITUTION,1.32365313490152,103.828498974985,POINT (11558135.635725256 147361.50153136978)
+SWISS COTTAGE SECONDARY SCHOOL,1.36471742697475,103.750396136688,POINT (11549441.267536525 151934.0159952587)
+TANGLIN SECONDARY SCHOOL,1.30970169234123,103.758158358303,POINT (11550305.354094133 145808.02387067425)
+TAMPINES SECONDARY SCHOOL,1.34926094811197,103.944263709507,POINT (11571022.507024065 150212.9259519053)
+TANJONG KATONG GIRLS' SCHOOL,1.30821274627283,103.895820094229,POINT (11565629.788439132 145642.23188915337)
+TANJONG KATONG SECONDARY SCHOOL,1.30873515955341,103.897225196199,POINT (11565786.203674944 145700.4018377545)
+TECK WHYE SECONDARY SCHOOL,1.38333422637073,103.75510327583,POINT (11549965.263868906 154007.02470002385)
+TEMASEK SECONDARY SCHOOL,1.31591673150616,103.947564112022,POINT (11571389.906151446 146500.06051722702)
+UNITY SECONDARY SCHOOL,1.40001524119441,103.74602091483,POINT (11548954.220067186 155864.4946818901)
+VICTORIA SCHOOL,1.3087130270751,103.927980966639,POINT (11569209.920379281 145697.93741867875)
+WEST SPRING SECONDARY SCHOOL,1.38782283303782,103.760128840155,POINT (11550524.707130514 154506.8402508995)
+WESTWOOD SECONDARY SCHOOL,1.35373698510994,103.701772102139,POINT (11544028.464770216 150711.33476201666)
+WHITLEY SECONDARY SCHOOL,1.35505208480649,103.842552378136,POINT (11559700.053407941 150857.7719021517)
+WOODGROVE SECONDARY SCHOOL,1.42831828137013,103.79604758539,POINT (11554523.163560009 159016.1346663915)
+WOODLANDS RING SECONDARY SCHOOL,1.43648894729939,103.800148469692,POINT (11554979.671912309 159925.97335125387)
+WOODLANDS SECONDARY SCHOOL,1.43648894729939,103.800148469692,POINT (11554979.671912309 159925.97335125387)
+XINMIN SECONDARY SCHOOL,1.37255884700002,103.88305161385,POINT (11564208.407705138 152807.16797880508)
+YIO CHU KANG SECONDARY SCHOOL,1.37797597740925,103.84213696352,POINT (11559653.809664419 153410.3739353481)
+YISHUN SECONDARY SCHOOL,1.42813324276086,103.828764316679,POINT (11558165.17342752 158995.5298613849)
+YISHUN TOWN SECONDARY SCHOOL,1.43232156717386,103.838094226361,POINT (11559203.774222465 159461.91730028315)
+YUAN CHING SECONDARY SCHOOL,1.34200635764467,103.72089870437,POINT (11546157.628391176 149405.1258617339)
+YUHUA SECONDARY SCHOOL,1.34718626876968,103.722687235839,POINT (11546356.726803575 149981.90974946608)
+YUSOF ISHAK SECONDARY SCHOOL,1.40693702458178,103.896275149571,POINT (11565680.444968086 156635.25530826193)
+YUYING SECONDARY SCHOOL,1.35713595302467,103.890194755287,POINT (11565003.57857257 151089.81204118932)
+ZHENGHUA SECONDARY SCHOOL,1.38836583415352,103.765510638527,POINT (11551123.806184838 154567.30460216367)
+ZHONGHUA SECONDARY SCHOOL,1.34840720846208,103.869430481414,POINT (11562692.110178335 150117.86174741428)

model/encoder.sav ADDED Viewed

Binary file (2.87 kB). View file

requirements.txt ADDED Viewed

	@@ -0,0 +1,11 @@

+numpy
+pandas
+geopandas
+shapely
+pickle
+folium
+requests
+streamlit
+seaborn
+streamlit_folium
+matplotlib.pyplot

utils.py ADDED Viewed

	@@ -0,0 +1,80 @@

+import pandas as pd
+import geopandas as gpd
+from shapely.geometry import Point, LineString
+import pickle
+import requests
+# Load geospatial data
+expressway = gpd.read_file('data/expressway.shp')
+expressway.to_crs(epsg=3857, inplace=True)
+geosubset = gpd.read_file('data/geosubset.shp')
+geosubset.to_crs(epsg=3857, inplace=True)
+geosubset['storey'] = geosubset['storey'].astype(int)
+geosubset['floor_area'] = geosubset['floor_area'].astype(float)
+geosubset['age_asof_t'] = geosubset['age_asof_t'].astype(int)
+geosubset['transactDa'] = pd.to_datetime(geosubset['transactDa'])
+mrt_raw = pd.read_csv('data/mrt.csv')
+geo_mrt = gpd.GeoDataFrame(mrt_raw, crs="EPSG:4326",
+                             geometry=[Point(xy) for xy in zip(mrt_raw['long'], mrt_raw['lat'])])
+geo_mrt.to_crs(epsg=3857, inplace=True)
+mall_df = pd.read_csv('data/mall.csv')
+geo_mall = gpd.GeoDataFrame(mall_df, crs="EPSG:4326",
+                             geometry=[Point(xy) for xy in zip(mall_df['long'], mall_df['lat'])])
+geo_mall.to_crs(epsg=3857, inplace=True)
+pri_sch_raw = pd.read_csv('data/pri_sch_latlong.csv')
+geo_pri = gpd.GeoDataFrame(pri_sch_raw, crs="EPSG:4326",
+                             geometry=[Point(xy) for xy in zip(pri_sch_raw['long'], pri_sch_raw['lat'])])
+geo_pri.to_crs(epsg=3857, inplace=True)
+sec_sec_raw = pd.read_csv('data/sec_sch_latlong.csv')
+geo_sec = gpd.GeoDataFrame(sec_sec_raw, crs="EPSG:4326",
+                             geometry=[Point(xy) for xy in zip(sec_sec_raw['long'], sec_sec_raw['lat'])])
+geo_sec.to_crs(epsg=3857, inplace=True)
+postal = pd.read_csv('data/district.csv')
+postal_melt = pd.DataFrame(postal['2dpostal'].str.split(",").to_list(), index=postal.district).stack().reset_index()[['district', 0]]
+postal_final = postal_melt.merge(postal, how='left', on='district').drop(columns=['2dpostal'])
+postal_final.columns = ['district', '2dpostal', 'town']
+postal_final['2dpostal'] = postal_final['2dpostal'].astype(str).str.strip()
+# Load models
+xgb = pickle.load(open('model/xgb_final.sav', "rb"))
+enc = pickle.load(open('model/encoder.sav', "rb"))
+# Load CIs
+sd_hdb = 34.88572450193993
+sd_condo = 112.3696357113714
+sd_ec = 66.34935799217807
+sd_apt = 137.16498181900047
+# test one map api here
+def test_postal(location):
+    searchQuery = "https://developers.onemap.sg/commonapi/search?searchVal=" + location + "&returnGeom=Y&getAddrDetails=Y"
+    response = requests.get(searchQuery)
+    try:
+        result = response.json()['results'][0]
+        latitude = result['LATITUDE']
+        longitude = result['LONGITUDE']
+        return [result['SEARCHVAL'], result['ADDRESS'], float(latitude), float(longitude)]
+    except:
+        return 'INVALID LOCATION'
+# Actual predictions
+def getSVY21(location):
+    searchQuery = "https://developers.onemap.sg/commonapi/search?searchVal=" + location + "&returnGeom=Y&getAddrDetails=Y"
+    response = requests.get(searchQuery)
+    try:
+        result = response.json()['results'][0]
+        latitude = result['LATITUDE']
+        longitude = result['LONGITUDE']
+        return float(latitude), float(longitude)
+    except:
+        return 'INVALID LOCATION'
+print('utils imported!')