A function to featurize the data into a dataframe with desired features independently represented.
Basically we're trying to ensure that things like upvotes/downvotes are seperated, # of views, # of comments.

Directly prior to returning the new Dataframe, a column 'Sentiment' will be created to hold the average post sentiment as a feature.

Params: Pandas Dataframe

Returns: Pandas Dataframe

A function to calculate the sentiment of a given post.

Params: Post Body String (Most likely a string extracted from Pandas Dataframe. Alternatively a key for the dataframe can be passed.)

Returns: Sentiment score object. List with positive, neutral, and negative.

A function to use the Pandas Dataframe in order to train a Feed-Forward model using the featurized data as well as the stock price on a given day to learn the relationship between any features and the actual stock price.
The network will be created with another function and should be called prior to this function. The network will be globally declared in the class and will be referred to as self.network

Params: Pandas Dataframe

Returns: True if network successfully trained, False if an error occurs.

Function to pull the reddit data using the pullshift API.

Params: TBD

Returns: Pandas dataframe

A function to add historical price data to the corresponding data for each reddit post within the Pandas Dataframe
The dataframe will be declared as an instance variable and will be accessed with self.df .

A row 'Price' will needed to be added to this dataframe as a part of this function.

Params: Pandas Dataframe of Reddit posts.

Returns: True if adding price data is successful, False if error occurs.