In [1]:

    

import pandas as pd
import matplotlib.pyplot as plt
import matplotlib as mpl
import numpy as np

from mpl_toolkits.basemap import Basemap
from matplotlib.collections import PatchCollection
from matplotlib.patches import Polygon

colors = ['#fff5eb','#fee6ce','#fdd0a2','#fdae6b','#fd8d3c','#f16913','#d94801','#a63603','#7f2704']

transit = pd.read_csv(r"datasets/ACS_15_5YR_B08101-4 DCMDVA/ACS_15_5YR_B08101.csv")
transit["Drive_Pct"] = (transit["HD01_VD10"] + transit["HD01_VD18"])/transit["HD01_VD01"]
transit = transit.set_index("GEO.id")
transit.head()


    

    
Out[1]:






  

    

      

      
GEO.id2
      
GEO.display-label
      
HD01_VD01
      
HD02_VD01
      
HD01_VD03
      
HD02_VD03
      
HD01_VD04
      
HD02_VD04
      
HD01_VD05
      
HD02_VD05
      
...
      
HD02_VD53
      
HD01_VD54
      
HD02_VD54
      
HD01_VD55
      
HD02_VD55
      
HD01_VD56
      
HD02_VD56
      
HD01_VD57
      
HD02_VD57
      
Drive_Pct
    
    

      
GEO.id
      

      

      

      

      

      

      

      

      

      

      

      

      

      

      

      

      

      

      

      

      

    
  
  

    

      
1400000US11001000100
      
11001000100
      
Census Tract 1, District of Columbia, District...
      
3133
      
335
      
4
      
10
      
266
      
220
      
1509
      
266
      
...
      
104
      
90
      
71
      
72
      
67
      
49
      
57
      
29
      
32
      
0.330035
    
    

      
1400000US11001000201
      
11001000201
      
Census Tract 2.01, District of Columbia, Distr...
      
1222
      
308
      
618
      
223
      
560
      
225
      
19
      
30
      
...
      
20
      
0
      
12
      
10
      
23
      
0
      
12
      
0
      
12
      
0.061375
    
    

      
1400000US11001000202
      
11001000202
      
Census Tract 2.02, District of Columbia, Distr...
      
2234
      
324
      
83
      
61
      
695
      
283
      
692
      
138
      
...
      
43
      
12
      
18
      
43
      
38
      
24
      
25
      
39
      
30
      
0.318263
    
    

      
1400000US11001000300
      
11001000300
      
Census Tract 3, District of Columbia, District...
      
4065
      
420
      
0
      
17
      
691
      
292
      
2263
      
317
      
...
      
82
      
72
      
75
      
16
      
24
      
73
      
95
      
26
      
28
      
0.496433
    
    

      
1400000US11001000400
      
11001000400
      
Census Tract 4, District of Columbia, District...
      
777
      
100
      
11
      
14
      
29
      
26
      
284
      
83
      
...
      
54
      
31
      
25
      
12
      
13
      
13
      
13
      
19
      
17
      
0.581725
    
  

5 rows × 115 columns

In [2]:

    

transit.hist("Drive_Pct")
plt.show()


    

In [3]:

    

fig = plt.figure(figsize=(8,8))
ax = fig.add_subplot(111, axisbg='w', frame_on=False)

m = Basemap(projection='merc',llcrnrlat=38.7,urcrnrlat=39.15,\
            llcrnrlon=-77.4,urcrnrlon=-76.8,resolution='c')
m.readshapefile(r"datasets/gz_2010_11_140_00_500k/gz_2010_11_140_00_500k",'dc',drawbounds = False)
m.readshapefile(r"datasets/gz_2010_24_140_00_500k/gz_2010_24_140_00_500k",'md',drawbounds = False)
m.readshapefile(r"datasets/gz_2010_51_140_00_500k/gz_2010_51_140_00_500k","va",drawbounds = False)


    

    
Out[3]:





(1905,
 5,
 [-83.67541299999999, 36.540738, 0.0, 0.0],
 [-75.242266, 39.466012, 0.0, 0.0])

In [4]:

    

for state in [zip(m.dc_info,m.dc),zip(m.va_info,m.va),zip(m.md_info,m.md)]:
    for info, shape in state:
        geo_id = info["GEO_ID"]
        if geo_id not in transit.index:
            color = "#000000"
        else:
            drive_pct = transit.loc[geo_id,"Drive_Pct"]
            if drive_pct > 0.9:
                color = colors[8]
            elif drive_pct > 0.8:
                color = colors[7]
            elif drive_pct > 0.7:
                color = colors[6]
            elif drive_pct > 0.6:
                color = colors[5]
            elif drive_pct > 0.5:
                color = colors[4]
            elif drive_pct > 0.4:
                color = colors[3]
            elif drive_pct > 0.3:
                color = colors[2]
            elif drive_pct > 0.2:
                color = colors[1]
            else:
                color = colors[0]

        patches = [Polygon(np.array(shape), True)]
        pc = PatchCollection(patches)
        pc.set_facecolor(color)
        ax.add_collection(pc)


    

In [5]:

    

labels = ["<20%",">20%",">30%",">40%",">50%",">60%",">70%",">80%",">90%"]
for i in range(0,len(labels)):
    m.plot(0,0,color=colors[i],label=labels[i])


    

In [6]:

    

m.readshapefile(r"datasets/DC Metro Lines/Metro_Lines_Regional", "metro", linewidth=2, color="blue")
# m.readshapefile(r"datasets/interstates/in101503", "highways", linewidth=2, color="grey")
plt.legend(loc=2)
plt.show()


    

In [ ]: