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

# # How to draw a GeoPandas.GeoDataFrame into folium
# 
# GeoPandas is a project to add support for geographic data to [pandas](http://pandas.pydata.org) objects.
# (See https://github.com/geopandas/geopandas)
# 
# It provides (among other cool things) a `GeoDataFrame` object that represents a Feature collection.
# When you have one, you may be willing to use it on a folium map. Here's the simplest way to do so.

# In this example, we'll use the same file as GeoPandas demo ; it's containing
# [the boroughs of New York City](http://www.nyc.gov/html/dcp/download/bytes/nybb_14aav.zip).

# In[1]:


import geopandas

url = (
    "https://raw.githubusercontent.com/python-visualization/folium/master/examples/data"
)
nybb = f"{url}/nybb.zip"
boros = geopandas.read_file(nybb)

boros


# To create a map with these features, simply put them in a `GeoJson`:

# In[2]:


import folium


m = folium.Map([40.7, -74], zoom_start=10, tiles="cartodbpositron")

folium.GeoJson(boros).add_to(m)

m


# Quite easy.
# 
# Well, you can also take advantage of your `GeoDataFrame` structure to set the style of the data. For this, just create a column `style` containing each feature's style in a dictionnary.

# In[3]:


boros["style"] = [
    {"fillColor": "#ff0000", "weight": 2, "color": "black"},
    {"fillColor": "#00ff00", "weight": 2, "color": "black"},
    {"fillColor": "#0000ff", "weight": 2, "color": "black"},
    {"fillColor": "#ffff00", "weight": 2, "color": "black"},
    {"fillColor": "#00ffff", "weight": 2, "color": "black"},
]

boros


# In[4]:


m = folium.Map([40.7, -74], zoom_start=10, tiles="cartodbpositron")

folium.GeoJson(boros).add_to(m)

m


# Folium should work with any object that implements the `__geo_interface__` but be aware that sometimes you may need to convert your data to `epsg='4326'` before sending it to `folium`.

# In[5]:


import fiona
import shapely

fname = f"{url}/2014_08_05_farol.gpx"
with fiona.open(fname, "r", layer="tracks") as records:
    tracks = [shapely.geometry.shape(record["geometry"]) for record in records]

track = tracks[0]

m = folium.Map(tiles="cartodbpositron")
folium.GeoJson(track).add_to(m)

m.fit_bounds(m.get_bounds())

m