Geographic Visualization Examples from Zillow Data

Useful Links http://darribas.org/gds15/slides/lecture_03.html http://darribas.org/gds15/index.html https://www.census.gov/geo/maps-data/maps/datamapper.html https://catalog.data.gov/dataset?res_format=KML



In [19]:

    
import geopandas as gp
%matplotlib inline
import matplotlib.pyplot as plt
import vincent
import numpy as np
import pandas as pd
import operator
import sys
import os
# Importing our contained utilities.
from utils import zillow_helpers as zh
sys.path.insert(0,'../')
%load_ext autoreload
%autoreload 2









    



---------------------------------------------------------------------------
ImportError                               Traceback (most recent call last)
<ipython-input-19-1efc9e406beb> in <module>()
      2 get_ipython().magic('matplotlib inline')
      3 import matplotlib.pyplot as plt
----> 4 import vincent
      5 import numpy as np
      6 import pandas as pd

ImportError: No module named 'vincent'



In [3]:

    
df = pd.read_pickle('main&propinfo46.pickle')



In [22]:

    
df.plot.scatter('PropertyAddressLatitude', 'PropertyAddressLongitude')









    Out[22]:





<matplotlib.axes._subplots.AxesSubplot at 0x11b5d4a8>



In [23]:

    
df_lat_long = df[['PropertyAddressLatitude', 'PropertyAddressLongitude']].copy()



In [24]:

    
df_lat_long.info()









    



<class 'pandas.core.frame.DataFrame'>
Int64Index: 439771 entries, 0 to 439770
Data columns (total 2 columns):
PropertyAddressLatitude     59856 non-null float64
PropertyAddressLongitude    59856 non-null float64
dtypes: float64(2)
memory usage: 10.1 MB



In [25]:

    
df.info()









    



<class 'pandas.core.frame.DataFrame'>
Int64Index: 439771 entries, 0 to 439770
Columns: 198 entries, TransId to BatchID_y
dtypes: float64(84), int64(5), object(109)
memory usage: 667.7+ MB



In [28]:

    
# conda install -c esri arcgis
from arcgis.gis import GIS
my_gis = GIS()
my_gis.map()



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