Python Pandas Select Index where index is larger than x

Example of selecting from a DataFrame with the use of index:

from numpy.random import randn
from pandas import DataFrame
from datetime import timedelta as td
import dateutil.parser

d = dateutil.parser.parse("2014-01-01")
df = DataFrame(randn(6,2), columns=list('AB'), index=[d + td(days=x) for x in range(1,7)])

In [1]: df
Out[1]:
                   A         B
2014-01-02 -1.172285  1.706200
2014-01-03  0.039511 -0.320798
2014-01-04 -0.192179 -0.539397
2014-01-05 -0.475917 -0.280055
2014-01-06  0.163376  1.124602
2014-01-07 -2.477812  0.656750

In [2]: df[df.index > dateutil.parser.parse("2014-01-04")]
Out[2]:
                   A         B
2014-01-05 -0.475917 -0.280055
2014-01-06  0.163376  1.124602
2014-01-07 -2.477812  0.656750

The existing answer is correct, however if we are selecting based on the index, the second method from here would be faster:

# Set index
df = df.set_index(df['date'])

# Select observations between two datetimes
df.loc[pd.Timestamp('2002-1-1 01:00:00'):pd.Timestamp('2002-1-1 04:00:00')]