Quantopian's community platform is shutting down. Please read this post for more information and download your code.
Back to Community
Datetime compare with string
Jeff Scott
posted Mar 2, 2015

Hi

Sorry for the rudimentary questions. When I print a History datetime index I see something like this:

PRINT Security(3766 [IBM]) 2010-12-31 20:30:00+00:00
dtype: object

For back testing and development in general, I want to display a number of prices around a specific datetime, but I don't know how to do a comparison so I can print, i.e.

hiidx = price_history_hi.idxmax()

if hiidx == '2011-01-03 14:31:00+00:00':
print 'Datetime found'

but this comparison does not work. How can I convert the History dataframe's datetime index to a string for comparison?

Thanks in advance

J

1 response
Michael Van Kleeck
Mar 2, 2015

The index is a Timestamp, which you can convert to a datetime and compare to another datetime that you create. For an example, paste the following code into an algorithm, run it with daily data from 2/26/2015 to 2/27/2015, and view the log.

from datetime import datetime  
from pytz import UTC

def initialize(context):  
    context.sec = sid(8554)  
    schedule_function(date_example,  
        date_rule=date_rules.week_end(),  
        time_rule=time_rules.market_close())    

def handle_data(context, data):  
    pass

def date_example(context, data):  
    prices = history(5, '1d', 'price')  
    log.info('Prices: \n{p}'.format(p=prices))  
    dt = datetime(2015, 2, 24, 0, 0, 0, 0, UTC)  
    log.info('dt: {d}'.format(d=dt))  
    max_price_series = prices.idxmax()  # Pandas Series, 1 element  
    log.info('Series: \n{s}'.format(s=max_price_series))  
    max_timestamp = max_price_series[0]  # Pandas Timestamp  
    log.info('Timestamp of max price: {mt}'.format(mt=max_timestamp))  
    max_dt = max_timestamp.to_datetime()  
    if dt == max_dt:  
        log.info('Dates match')  
    else:  
        log.info('Dates do not match')
About Quantopian
Careers
Community
Events
Documentation
Academia
Lectures
Status
Facebook
Twitter
LinkedIn
YouTube
Terms of Use
Privacy Policy

The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by Quantopian.

In addition, the material offers no opinion with respect to the suitability of any security or specific investment. No information contained herein should be regarded as a suggestion to engage in or refrain from any investment-related course of action as none of Quantopian nor any of its affiliates is undertaking to provide investment advice, act as an adviser to any plan or entity subject to the Employee Retirement Income Security Act of 1974, as amended, individual retirement account or individual retirement annuity, or give advice in a fiduciary capacity with respect to the materials presented herein. If you are an individual retirement or other investor, contact your financial advisor or other fiduciary unrelated to Quantopian about whether any given investment idea, strategy, product or service described herein may be appropriate for your circumstances. All investments involve risk, including loss of principal. Quantopian makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances.