# Project: I wanted to figure out a way to send mail to certain addresses for prospectice clients in certain locations. # I found a database with all the addresses (70,000) of the city of interest # I created a tool where I can put the longitude and latitude of certain streets and it would give all addresses within the chosen coordinates # I obtained the addreses and sent them mail. DONE! # FUTURE GOALS: # 1. Make it a web app so anyone can use it. Also, create a way for people to select the area of interest. # 2. Figure out a way to make it personalized. # If you have ideas, want to help, or have comment, reach out (juandavidcampolargo.com/contact)

# Start writing code here... import numpy as np import pandas as pd import matplotlib.pyplot as plt

df = pd.read_csv('city_of_aurora.csv')

df.head()

BBox = (df.LON.min(), df.LON.max(), df.LAT.min(), df.LAT.max())

df.count()

BBox

#Reduction of Data Frame #You can get coordinates by creating a map of the area using openstreetmap.org/export #LAT min: top |||| #LON min: left #Latitude #max df1 = df[df['LAT'] > 41.7308] #min df2 = df1[df1['LAT'] < 41.7967] #Longitude #min df3 = df2[df2['LON'] > -88.3745] #max df_final = df3[df3['LON'] < -88.2784]

#1st: check to the number ##df_final.count() df_final.count()

#2nd: check the map #color import plotly.express as px fig = px.scatter_mapbox(df_final, lat="LAT", lon="LON") fig.update_layout(mapbox_style="open-street-map") fig.show()

#B&W mapbox_key="pk.eyJ1IjoiamRjYW1wb2xhcmdvIiwiYSI6ImNreHMzZXh4cTRyOGcydW80aWcyc2ZrMXMifQ.SqgAQ26kdjR4jA4EcGnWCQ" fig = px.scatter_mapbox( df_final, lat="LAT", lon="LON", color="CITY", hover_name='CITY', hover_data=['CITY'], zoom=11) # Now using Mapbox fig.update_layout(mapbox_style="light", mapbox_accesstoken=mapbox_key) fig.show()

#1 Mariela Address (424 Forest Ave, Aurora, IL) #Reduction of Data Frame #You can get coordinates by creating a map of the area using openstreetmap.org/export #LAT min: top |||| #LON min: left #Latitude #max df1 = df[df['LAT'] > 41.77365] #min df2 = df1[df1['LAT'] < 41.77466] #Longitude #min df3 = df2[df2['LON'] > -88.30620] #max df_final1 = df3[df3['LON'] < -88.30122] #1st: check numbers df_final1.count() #2nd: check the map #color import plotly.express as px fig = px.scatter_mapbox(df_final1, lat="LAT", lon="LON", zoom=15) fig.update_layout(mapbox_style="open-street-map") fig.show()

df_Mariela = df_final1.drop(['LON', 'LAT','UNIT', 'REGION', 'ID', 'DISTRICT', 'HASH'], axis=1) ##Insert Column STATE with value (IL) at index 5 df_Mariela.insert (3, "STATE", "IL") # df_Mariela1 = df_Mariela['STATE'] = 'IL' df_Mariela.head(45)

print(df_Mariela)

#2 Victor Mancilla (420 W New York Ave, Aurora, IL) #Reduction of Data Frame #You can get coordinates by creating a map of the area using openstreetmap.org/export #LAT min: top |||| #LON min: left #Latitude #max max_lat = 41.7615 min_lat = 41.7621 df1 = df[df['LAT'] > max_lat] #min df2 = df1[df1['LAT'] < min_lat] #Longitude #min min_lon = -88.3247 max_lon = -88.3211 df3 = df2[df2['LON'] > min_lon] #max df_final1 = df3[df3['LON'] < max_lon] #1st: check numbers df_final1.count() #2nd: check the map #color import plotly.express as px fig = px.scatter_mapbox(df_final1, lat="LAT", lon="LON", zoom=15) fig.update_layout(mapbox_style="open-street-map") fig.show() df_Victor = df_final1.drop(['LON', 'LAT','UNIT', 'REGION', 'ID', 'DISTRICT', 'HASH'], axis=1) ##Insert Column STATE with value (IL) at index 5 df_Victor.insert (3, "STATE", "IL") # df_Mariela1 = df_Mariela['STATE'] = 'IL' df_Victor.head() print(df_Victor)