Filtering Pandas DataFrames on dates

Solution 1:

If date column is the index, then use .loc for label based indexing or .iloc for positional indexing.

For example:

df.loc['2014-01-01':'2014-02-01']

See details here http://pandas.pydata.org/pandas-docs/stable/dsintro.html#indexing-selection

If the column is not the index you have two choices:

1. Make it the index (either temporarily or permanently if it's time-series data)
2. df[(df['date'] > '2013-01-01') & (df['date'] < '2013-02-01')]

See here for the general explanation

Note: .ix is deprecated.

Solution 2:

Previous answer is not correct in my experience, you can't pass it a simple string, needs to be a datetime object. So:

import datetime 
df.loc[datetime.date(year=2014,month=1,day=1):datetime.date(year=2014,month=2,day=1)]