multiple filters for blaze expression?

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multiple filters for blaze expression?

posted

Seeking Help Using Data Research

Hi all,

I'm trying to explore the use of a random forest to predict stock price through the use of twitter data.

Ideally I would like to filter companies based on market cap and sector and then collect monthly summations of each sentiment metric, which would then be input into the model.

I'm fairly new to coding and have never used Blaze to pull data. Specifically I would like to have a filter that looks something like this below:

twitter_data = odo(psych[psych.sid in companies & psych.asof_date <= end_date & psych.asof_date >= start_date], pd.DataFrame)

psych is the psychsingnal data base
companies is a set of equity objects
start_date / end_date are datetime objects

For the life of me I cannot find how to do so on any online source - thank you for any input!

1 response

Here's a nice translation from pandas to blaze: http://blaze.readthedocs.io/en/latest/rosetta-pandas.html

You can string clauses together with boolean operators like so:

from quantopian.interactive.data.psychsignal import twitter_withretweets_free as twitter_mood  
aapl = twitter_mood[(twitter_mood.sid == 24) & (twitter_mood.asof_date > '2012-01-01')]

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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.

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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.