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

# In[1]:


import geopandas as gpd, folium, requests, pandas as pd, fiona, branca, json, numpy as np


# In[2]:


income = pd.read_csv("https://raw.githubusercontent.com/pri-data/50-states/master/data/income-counties-states-national.csv")
income.columns


# In[3]:


gdf = gpd.read_file("https://raw.githubusercontent.com/PublicaMundi/MappingAPI/master/data/geojson/us-states.json")
statesabbr=pd.read_json("https://gist.githubusercontent.com/mshafrir/2646763/raw/8b0dbb93521f5d6889502305335104218454c2bf/states_titlecase.json")
income = pd.read_csv("https://raw.githubusercontent.com/pri-data/50-states/master/data/income-counties-states-national.csv")
income['income-2015']=pd.to_numeric(income['income-2015'], errors='coerce')
income=income.groupby(by=['state'], as_index=False).median()
income['State']=pd.merge(income, statesabbr, left_on='state', right_on='abbreviation')['name']
income.head()
# income.dropna(subset=['income-2015'])[['state','income-2015']].groupby(by='state')


# In[4]:


gdf1=gdf.merge(income, left_on='name', right_on='State', how='left').fillna(0)


# In[5]:


gdf1.crs = fiona.crs.from_epsg(4326)
gdf1.head()


# In[6]:


gdf1=gdf1[gdf1['name']!='District of Columbia']


# In[7]:


roads = gpd.read_file(r"/Users/jasonbaker/Downloads/tl_2016_us_primaryroads/tl_2016_us_primaryroads.shp")
roads = roads.to_crs(gdf1.crs)
interstates = roads.loc[roads['RTTYP']=='I']
interstates.loc[:,'geometry']=interstates.geometry.simplify(tolerance=0.01, preserve_topology=False)
interstates = interstates.dissolve(by='FULLNAME', aggfunc='first', as_index=False)
interstates.loc[:,'FULLNAME'] = interstates['FULLNAME'].str.replace('- ','-')
interstates.head()


# In[8]:


variable = 'income-2015'
gdf1=gdf1.sort_values(by=variable, ascending=True)
colormap = folium.LinearColormap(colors=["red","orange","yellow","green"],vmin=gdf1.loc[gdf1[variable]>0, variable].min(), 
                                 vmax=gdf1.loc[gdf1[variable]>0, variable].max()).to_step(n=5)
colormap.caption = "2015 US Median Household Income"


# In[9]:


centroid=gdf1.geometry.centroid

m=folium.Map(location=[centroid.y.mean(), centroid.x.mean()], zoom_start=4, tiles='stamentoner')

folium.GeoJson(gdf1[['geometry','name',variable]],
               name="United States of America",
               style_function=lambda x: {"weight":2, 'color':'black','fillColor':colormap(x['properties'][variable]), 'fillOpacity':0.2},
              highlight_function=lambda x: {'weight':3, 'color':'black'},
               smooth_factor=2.0,
              tooltip=folium.features.Tooltip(fields=['name',variable,],
                                              aliases=['State','2015 Median Income'], 
                                              labels=True, 
                                              sticky=True,
                                              toLocaleString=True
                                             )
              ).add_to(m)


folium.GeoJson(interstates,
               name='US Interstate Highways',
               style_function=lambda x: {'weight':2,'color':'#5BDAE9','dashArray':'1 3'},
               highlight_function=lambda x: {'weight':5,'color':'yellow', 'dashArray':'1 7'},
               tooltip=folium.features.Tooltip(fields=['FULLNAME',],labels=False, toLocaleString=True),
               smooth_factor=5.0,
              ).add_to(m)


colormap.add_to(m)

folium.LayerControl(autoZIndex=False, collapsed=False).add_to(m)

m



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