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This is a continuation of the data analysis project using L.A. city's data 'Great Streets Pedestrian Survey 2015'.
The data shown is already data wrangled and cleaned which is described on my other repo. This project is to demonstrate how to use SQL data with python.
- requests module
- json module for google maps api
- urllib
- pip install request
- pip install json
- pip install urllib
- pip install folium
- get google maps API key before starting
base_url= "https://maps.googleapis.com/maps/api/geocode/json?"
AUTH_KEY = ""
# set up your search parameters - address and API key
parameters = {"address": "Venice Blvd. and Moore st, Los Angeles",
"key": AUTH_KEY}
import folium
from folium.plugins import MarkerCluster
m = folium.Map(location=[34.0453119,-118.3083065], zoom_start=12)
marker_cluster = MarkerCluster().add_to(m)
See the open issues for a list of proposed features (and known issues).
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ykimdeveloper - message me for any questions
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The original setup of this repository is by yosep kim.
For a full list of all authors and contributors, see the contributors page.
MAPS-Great-Streets-Survey-ykimdeveloper follows good practices of security, but 100% security cannot be assured. MAPS-Great-Streets-Survey-ykimdeveloper is provided "as is" without any warranty. Use at your own risk.
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This project is licensed under the MIT license.
See LICENSE for more information.