visualise_map.py

import pandas as pd
import numpy as np
import zipfile
import matplotlib.pyplot as pl
import seaborn as sns
from sys import exit

mapdata = np.loadtxt("../data/sf_map_copyright_openstreetmap_contributors.txt")
asp = mapdata.shape[0] * 1.0 / mapdata.shape[1]

lon_lat_box = (-122.5247, -122.3366, 37.699, 37.8299)
clipsize = [[-122.5247, -122.3366],[ 37.699, 37.8299]]

train = pd.read_csv('../data/train.csv', sep=',')

train['Xok'] = train[train.X<-121].X
train['Yok'] = train[train.Y<40].Y
train = train.dropna() # drop any row w missing values

g= sns.FacetGrid(train, col="Category", col_wrap=2, size=4, aspect=1/asp)

for ax in g.axes:
    ax.imshow(mapdata, cmap=pl.get_cmap('gray'), 
              extent=lon_lat_box, 
              aspect=asp)
g.map(sns.kdeplot, "Xok", "Yok", clip=clipsize, cmap="Blues_d")

pl.savefig('map_categories.png')