In [1]:

    

import psycopg2
import pandas.io.sql as sql
conn_string = "host='localhost' port=5432 dbname='drcog' user='postgres' password='postgres'"
conn = psycopg2.connect(conn_string)
cur = conn.cursor()
parcels_urbancen = sql.read_frame('select parcel_id, urban_cen from parcels_spatial',conn)


    

In [7]:

    

import pandas as pd


    

In [8]:

    

store = pd.HDFStore('c:\\urbansim\\data\\drcog.h5')


    

In [9]:

    

store['parcels_urbancen'] = parcels_urbancen


    

    




c:\Anaconda\lib\site-packages\pandas\io\pytables.py:1992: PerformanceWarning: 
your performance may suffer as PyTables will pickle object types that it cannot
map directly to c-types [inferred_type->mixed,key->block1_values] [items->['urban_cen']]

  warnings.warn(ws, PerformanceWarning)

In [10]:

    

store.close()