In [1]:
from sqlalchemy import create_engine

ttc_subway_times = create_engine('postgresql://localhost/ttc_subway_times')

In [2]:
import pandas as pd
import numpy as np

In [3]:
df = pd.read_sql_query("SELECT * FROM ntas_data", con=ttc_subway_times)

In [4]:
df.tail()


Out[4]:
requestid id station_char subwayline system_message_type timint traindirection trainid train_message
5741032 878649 13372591224 DML1 SHEP Normal 7.312651 East 464 Arriving
5741033 878649 13372591225 DML1 SHEP Normal 14.946141 East 461 Arriving
5741034 878649 13372591226 DML2 SHEP Normal 2.352987 West 463 Arriving
5741035 878649 13372591227 DML2 SHEP Normal 7.567651 West 464 Arriving
5741036 878649 13372591228 DML2 SHEP Normal 15.201141 West 461 Arriving

In [5]:
df.memory_usage()


Out[5]:
Index                        80
requestid              45928296
id                     45928296
station_char           45928296
subwayline             45928296
system_message_type    45928296
timint                 45928296
traindirection         45928296
trainid                45928296
train_message          45928296
dtype: int64

In [ ]: