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Accessing dataframe of CSV from quandl
Jeremy Steele
posted Jun 30, 2015
Fetcher Using Data

I am trying to get access to the fama french factors from quandl

Using the code below the df seems to preview ok and I can print that days data with "print data['FAMA_FRENCH']" and I can see the various factors.

But if I try:

data['FAMA_FRENCH'].HML #attribute error
or
data['FAMA_FRENCH']['HML'] #attribute error
or
getattr(data['FAMA_FRENCH'],'HML') # Not allowed

My aim would be to have a dataframe of the daily factors prior to this day (for some lookback period).

How is best to do this? Am I just going about it the wrong way?

def initialize(context):  
        fetch_csv('https://www.quandl.com/api/v1/datasets/KFRENCH/FACTORS_D.csv?sort_order=asc&trim_start=2002-01-01',  
                  symbol = 'FAMA_FRENCH',  
              date_column = 'Month',  
              date_format = '%Y-%m-%d',  
             post_func=preview)

def preview(df):  
    log.info(df.head())  
    return df  
# Will be called on every trade event for the securities you specify.  
def handle_data(context, data):  
    print data['FAMA_FRENCH']  
    order(sid(24), 0) # It seems to skip handle_data if you don't have an order function
2 responses
Gus Gordon
Jun 30, 2015

The problem is that those attributes are not properly present on the first day. The easiest way to fix this is to check that the attributes exist before you try to access them. Sorry, there should be a better way of managing this in the future!

Disclaimer

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.

JOHN CHAN
Jul 19, 2015

Hey I'm new to quantopian and trying to build an algo model . Im having some trouble figuring out fetcher... cant gt it to function... wats missing....

import pandas as pd
import numpy as np

def initialize(context):

auth_code ='JbEsXXXXXXXXXXXXXX'
database = 'ZES'
dataset = 'AAPL'
url = 'https://quandl.com/api/v1/datasets/{0}/{1}.csv?auth_code={2}'
url = url.format(database, dataset, auth_code)
fetch_csv(url,
date_column='DATE',
symbol=dataset,
date_format='%Y-%m-%d',
post_func=post_func) 

# ffill: propagate last valid observation forward to next valid def post_func(df): return df.fillna(method='ffill')

def handle_data(context, data):

pass

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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.