Factor values for specific assets can be fetched either within pipeline or once the pipeline dataframe is fetched. One common way to access specific values from a dataframe is by using the pandas at
method (https://pandas.pydata.org/pandas-docs/version/0.18/generated/pandas.DataFrame.at.html). Something like this, in an algo, would fetch the sentiment for just APPL and return a scaler value.
# Fetch pipeline data
data = pipeline_output('my_pipe')
# Select the sentiment for a single asset using the 'at' method
apple = symbol('AAPL')
apple_sentiment = data.at[apple, 'mean_sentiment_5day']
Attached is a sample algo showing how this could potentially be used.
Now, one big issue. Sentdex only tracks sentiment for a limited number of stocks and doesn't track sentiment for ETFs including SPY. If you try to get sentiment data for SPY it will be all nans. As an alternative, one could create a factor which is the mean sentiment of the Q500US. That might be a similar indicator?
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