In [1]:

    

import pandas as pd
hh = pd.read_csv('c://urbansim//data//travel_model//2015//households2012.csv')
jobs = pd.read_csv('c://urbansim//data//travel_model//2015//jobs2012.csv')


    

In [5]:

    

hh.dtypes


    

    
Out[5]:





tempid              int64
parcel_id           int64
urbancenter_id     object
x                   int64
y                   int64
taz05_id            int64
dist_trans        float64
dtype: object

In [4]:

    

jobs.dtypes


    

    
Out[4]:





tempid             int64
parcel_id          int64
urbancenter_id    object
x                  int64
y                  int64
taz05_id           int64
jobtypename       object
dtype: object

In [6]:

    

import psycopg2
import cStringIO


    

In [10]:

    

conn_string = "host='paris.urbansim.org' dbname='denver' user='drcog' password='M0untains#' port=5433"
conn = psycopg2.connect(conn_string)
cursor = conn.cursor()


    

In [11]:

    

cursor.execute("DROP TABLE IF EXISTS jobs_xy;")
conn.commit()

cursor.execute("CREATE TABLE jobs_xy (tempid integer,parcel_id integer,urbancenter_id text,x integer,y integer,taz05_id integer,jobtypename text);")
conn.commit()

output = cStringIO.StringIO()
jobs.to_csv(output, sep='\t', header=False, index=False)
output.seek(0)
cursor.copy_from(output, 'jobs_xy', columns =tuple(jobs.columns.values.tolist()))
conn.commit()


    

In [12]:

    

cursor.execute("DROP TABLE IF EXISTS hh_xy;")
conn.commit()

cursor.execute("CREATE TABLE hh_xy (tempid integer,parcel_id integer,urbancenter_id text,x integer,y integer,taz05_id integer,dist_trans numeric);")
conn.commit()

output = cStringIO.StringIO()
hh.to_csv(output, sep='\t', header=False, index=False)
output.seek(0)
cursor.copy_from(output, 'hh_xy', columns =tuple(hh.columns.values.tolist()))
conn.commit()


    

In [ ]: