In [9]:

    

import geopandas as gpd

%matplotlib inline

import matplotlib
import numpy as np
import matplotlib.pyplot as plt


    

In [11]:

    

dc_boundary = gpd.read_file('../data/dc-boundary.geojson')
dc_boundary.plot()


    

    
Out[11]:





<matplotlib.axes._subplots.AxesSubplot at 0x10e590c18>






    

In [14]:

    

dc_quadrants = gpd.read_file('../data/dc-quadrants.geojson')
dc_quadrants.plot()


    

    
Out[14]:





<matplotlib.axes._subplots.AxesSubplot at 0x10e92ea58>






    

In [18]:

    

last_30_days = gpd.read_file('../data/parking-enforcement-last-30-days.geojson')
last_30_days.plot()


    

    
Out[18]:





<matplotlib.axes._subplots.AxesSubplot at 0x10ed31748>






    

In [20]:

    

violations_with_quadrants = gpd.sjoin(last_30_days, dc_quadrants, how="inner", op='intersects')


    

In [22]:

    

violations_with_quadrants.head()


    

    
Out[22]:






  

    

      

      
ADDDATE
      
CITY
      
INSPECTIONDATE
      
INSPECTIONFLAG
      
INSPECTORNAME
      
LATITUDE
      
LONGITUDE
      
MARADDRESSREPOSITORYID
      
OBJECTID_left
      
ORGANIZATIONACRONYM
      
...
      
XCOORD
      
YCOORD
      
ZIPCODE
      
geometry
      
index_right
      
NAME
      
OBJECTID_right
      
QUADRANT
      
SHAPE_Area
      
SHAPE_Length
    
  
  

    

      
0
      
2016-06-30T17:03:59
      
WASHINGTON
      
None
      
N
      
None
      
38.898106
      
-76.998665
      
3495.0
      
1
      
DPW
      
...
      
400115.83
      
136695.02
      
20002
      
POINT (-76.9986670079 38.8981134889)
      
2
      
Northeast
      
3
      
NE
      
4.017519e+07
      
30312.733391
    
    

      
1
      
2016-06-30T17:04:30
      
WASHINGTON
      
None
      
N
      
None
      
38.897940
      
-76.998214
      
4008.0
      
2
      
DPW
      
...
      
400154.90
      
136676.58
      
20002
      
POINT (-76.9982166174 38.8979473687)
      
2
      
Northeast
      
3
      
NE
      
4.017519e+07
      
30312.733391
    
    

      
2
      
2016-06-30T17:00:40
      
WASHINGTON
      
None
      
N
      
None
      
38.898718
      
-76.999709
      
1211.0
      
3
      
DPW
      
...
      
400025.24
      
136762.92
      
20002
      
POINT (-76.99971131700001 38.898725164)
      
2
      
Northeast
      
3
      
NE
      
4.017519e+07
      
30312.733391
    
    

      
3
      
2016-06-30T17:02:28
      
WASHINGTON
      
None
      
N
      
None
      
38.898772
      
-76.998642
      
1181.0
      
4
      
DPW
      
...
      
400117.81
      
136768.91
      
20002
      
POINT (-76.99864417000001 38.8987791166)
      
2
      
Northeast
      
3
      
NE
      
4.017519e+07
      
30312.733391
    
    

      
14
      
2016-07-05T12:45:59
      
WASHINGTON
      
None
      
N
      
None
      
38.919496
      
-76.982295
      
50459.0
      
15
      
DPW
      
...
      
401535.40
      
139069.64
      
20018
      
POINT (-76.982297053 38.9195035543)
      
2
      
Northeast
      
3
      
NE
      
4.017519e+07
      
30312.733391
    
  

5 rows × 34 columns

In [25]:

    




    

In [26]:

    

base = dc_quadrants.plot(color='white')
last_30_days.plot(ax=base, marker='o', color='red', markersize=5)


    

    
Out[26]:





<matplotlib.axes._subplots.AxesSubplot at 0x115b50da0>






    

In [ ]: