#!/usr/bin/env python
# coding: utf-8

# ## Geocoding and Isolines Services
# 
# This example illustrates how to combine both the Geocoding and Isolines Data Services.
# 
# _Note: You'll need [CARTO Account](https://carto.com/signup) credentials to reproduce this example._

# In[1]:


from cartoframes.auth import set_default_credentials

set_default_credentials('creds.json')


# In[2]:


from pandas import DataFrame

df = DataFrame([
         ['Calle Serrano 15'],
         ['Calle de San Pedro 21'],
         ['Calle Gran Vía 46'],
         ['Paseo de la Castellana 200'],
         ['Calle Ntra. Sra. del Carmen 7'],
         ['Calle de San Germán 12'],
         ['Calle de Bravo Murillo 377'],
    ],
    columns=['address']
)
df


# In[3]:


from cartoframes.data.services import Geocoding

gc = Geocoding()
gdf, metadata = gc.geocode(df, street='address', city={'value': 'Madrid'}, country={'value': 'Spain'})


# In[4]:


gdf


# In[5]:


metadata


# In[6]:


from cartoframes.viz import Layer

Layer(gdf)


# In[7]:


from cartoframes.data.services import Isolines

iso_service = Isolines()
isochrones = iso_service.isochrones(gdf, [100, 200, 300], mode='walk', dry_run=True)

print('Available Quota: {0}'.format(iso_service.available_quota()))
print('Required Quota: {0}'.format(isochrones.metadata.get('required_quota')))


# In[8]:


isochrones = iso_service.isochrones(gdf, [100, 200, 300], mode='walk')

isochrones.data.head()


# In[9]:


from cartoframes.viz import Map, Layer, basic_style

Map([
    Layer(isochrones.data, basic_style(color='green', opacity='0.3')),
    Layer(gdf, basic_style(size=3))
])