Interdisciplinary-Project/first_map.py at master · MobilityPolito/Interdisciplinary-Project · GitHub

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import pandas as pd
import geopandas
import geopandas.tools
from shapely.geometry import Point
from shapely.geometry import Polygon
from geopandas.geoseries import GeoSeries
import matplotlib.pyplot as plt

#path = "./shapes.txt"
#shapes_df = pd.read_csv(path, index_col = 0)

import shapefile

path = "../SHAPE/Zonizzazione.dbf"
sf = shapefile.Reader(path)
shapes = sf.shapes()
ID = 0
shapes_df = pd.DataFrame(columns = ["shape_id", "shape_pt_lat", "shape_pt_lon"])
for shape in sf.iterShapes():
    for point in shape.points:
#        print point[0], point[1]
        s = pd.Series()
        s.loc["shape_id"] = ID
        s.loc["shape_pt_lat"] = float(point[0])
        s.loc["shape_pt_lon"] = float(point[1])
        shapes_df = pd.concat([shapes_df, pd.DataFrame(s).T], ignore_index=True)
    ID += 1

pl = []
for shape_id, group in shapes_df.groupby("shape_id"):
    print shape_id
    group["geometry"] = \
        group.apply(lambda row: (row["shape_pt_lon"], row["shape_pt_lat"]), axis=1)
    pl += [Polygon(list(group["geometry"].values))]
s = GeoSeries(pl).convex_hull
s.plot()
plt.show()

#import gmplot
#
#gmap = gmplot.GoogleMapPlotter(45.116177, 7.742615, 16)
#
#gmap.scatter(shapes_df["shape_pt_lat"][shapes_df.shape_id == 1640],\
#             shapes_df["shape_pt_lon"][shapes_df.shape_id == 1640],\
#             '#3B0B39', marker=False)
##gmap.scatter(marker_lats, marker_lngs, 'k', marker=True)
##gmap.heatmap(heat_lats, heat_lngs)
#
#gmap.draw("mymap.html")