scarsdale-properties-complete.py

# import libraries
import pandas as pd
import numpy as np
import folium
import matplotlib.cm

# define color vector function
def ColorVector(values, number_of_colors, cmap_name):
    buckets = pd.qcut(values, number_of_colors).codes
    cmap = matplotlib.cm.get_cmap(name = cmap_name)
    colors = []
    for i in range(0, number_of_colors):
        r = int(cmap(i/number_of_colors)[0]*255)
        g = int(cmap(i/number_of_colors)[1]*255)
        b = int(cmap(i/number_of_colors)[2]*255)
        color = "#{0:02x}{1:02x}{2:02x}".format(r, g, b)  
        colors.append(color)
    values = []
    for j in range(0, len(buckets)):
        value = colors[buckets[j]]
        values.append(value)
    return values
  
# define color categories function
def ColorCategories(variable, colors):
    properties['Colors'] = colors
    counts = properties.groupby(['Colors', variable]).size().reset_index().rename(columns={0:'count'})
    color_list = counts.Colors.unique()
    for color in color_list:
        temp = counts[(counts.Colors == color)]
        print(color, min(temp[variable]), max(temp[variable]), len(temp))
        
# read in the data
properties = pd.read_csv('/Users/erikgregorywebb/Documents/Python/scarsdale/data/scarsdale-properties-final.csv')

# prepare map components
lats = properties['LAT']
lngs = properties['LNG']
vals = properties['TotalAssessedVal']
addresses = properties['Address']
sqft = properties['SqFootLivingArea']
owners = properties['Owner']

##### View 1 - Year Built #####

years = []
for year in year_built:
    if pd.isnull(year) == False:
        year = int(year)
    else:
        year = None
    years.append(year)
    
# coloring    
properties['YearBuilt'] = years
colors = ColorVector(properties['YearBuilt'].values, 20, 'coolwarm')
ColorCategories('YearBuilt', colors)

# determine color vector
colors = ColorVector(properties['YearBuilt'].values, 20, 'coolwarm')

# create base map
m = folium.Map(location=[np.mean(properties.LAT), np.mean(properties.LNG)], 
               tiles = 'Stamen Toner', zoom_start = 13)

# loop through properties to add map layers
for i in range(len(lats)):
    folium.Circle(location=[lats[i], lngs[i]], 
                  popup = ("""<b>{}</b><br>Year Built: {}""".format(addresses[i], years[i])),
                  radius = 20, 
                  color = colors[i],
                  fill = True,
                  fill_color = colors[i], 
                  fill_opacity=.30).add_to(m)
    
# save map as html file    
m.save('view-1.html')

##### View 2 - Total Assessed Value #####

# stylize as currency
dollar_vals = []
for i in range(0, len(vals)):
    dollar_val = '${:0,.0f}'.format(vals[i]).replace('$-','-$')
    
# stylize as number (commas)
num_sqfts = []
for i in range(0, len(sqft)):
    num_sqft = '{:0,.0f}'.format(sqft[i])
    num_sqfts.append(num_sqft)
    
# determine color vector    
colors = ColorVector(properties['TotalAssessedVal'].values, 10, 'plasma')
ColorCategories('TotalAssessedVal', colors)

# create the base map
m = folium.Map(location=[np.mean(properties.LAT), np.mean(properties.LNG)], 
               tiles = 'Stamen Toner', zoom_start = 13)

# loop through properties to add map layers
for i in range(len(lats)):
    folium.Circle(location=[lats[i], lngs[i]], 
                  popup = ("""<b>{}</b><br>{}<br>{} sq. ft.<br>""".format(addresses[i], dollar_vals[i], num_sqfts[i])),
                  radius = 20, 
                  color = colors[i],
                  fill = True,
                  fill_color = colors[i], 
                  fill_opacity=.30).add_to(m)
# save map as html file      
m.save('view-2.html')

##### View 3 - Years Since Last Sale #####

# calculate the number of years since last sale
SalesDates = list(properties['SaleDate'])
YearsSinceSale = []
for SaleDate in SalesDates:
    if pd.isnull(SaleDate) == False:
        Year = int(SaleDate[-2:])
        if Year < 19:
            Year = Year + 2000
        else:
            Year = Year + 1900
        Years = 2018 - Year
    else:
        Year = None
        Years = None
    YearsSinceSale.append(Years)
    
properties['YearsSinceSale'] = YearsSinceSale
colors = ColorVector(properties['YearsSinceSale'].values, 15, 'summer')
ColorCategories('YearsSinceSale', colors)

# replace Nan with 'None' for simplicity
properties['SaleDate'] = properties['SaleDate'].fillna('None')
SalesDates = list(properties['SaleDate'])

# create the base map
m = folium.Map(location=[np.mean(properties.LAT), np.mean(properties.LNG)], 
               tiles = 'Stamen Toner', zoom_start = 13)

# loop through properties to add map layers
for i in range(len(lats)):
    folium.Circle(location=[lats[i], lngs[i]], 
                  popup = ("""<b>{}</b><br>Sale Date: {}<br>Years Since Sale: {}""".format(addresses[i], SalesDates[i], YearsSinceSale[i])),
                  radius = 15, 
                  color = colors[i],
                  fill = True,
                  fill_color = colors[i], 
                  fill_opacity=.7).add_to(m)
    
# save map as html file        
m.save('view-3.html')