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Users might want to manually sift through some of the news/social media data we retrieve about a specific stock. To allow for this, we should add another command to cogs/sentiment_cog.py, allowing the user to query for sentiment data and download that data in CSV format. This will require the following (in a new command function within the sentiment cog):
Calling backend functions to retrieve the list of data to be saved
Formatting data in CSV format -> the user should be able to discern if a given data point is a headline, a tweet, or a Reddit comment.
Uploading the CSV file to Discord
Note that this command doesn't require any data analysis. It is just a way for the user to interface with our data retrieval system.
The text was updated successfully, but these errors were encountered:
Users might want to manually sift through some of the news/social media data we retrieve about a specific stock. To allow for this, we should add another command to
cogs/sentiment_cog.py
, allowing the user to query for sentiment data and download that data in CSV format. This will require the following (in a new command function within the sentiment cog):Note that this command doesn't require any data analysis. It is just a way for the user to interface with our data retrieval system.
The text was updated successfully, but these errors were encountered: