Cleans the word by replacing non-friendly characters. Parameters ---------- word : str The word to be cleaned. Returns -

Read the PDF contents and extract the text that we need.

Get the entities and save them to .csv Parameters ---------- doc : spacy.doc A doc object.

Get the sentences, score and save them to .csv You will require to download the dataset (zip) from the following url: https://www.kaggle.com

Get the tokens and save them to .csv Parameters ---------- doc : spacy.doc A doc object.

Loads the model and processes it. The model used can be installed by running this command on your CMD/Terminal: python -m spacy download

Gets the number of counts per entity. Parameters ---------- df : pandas.DataFrame The DataFrame to be analyzed.

Gets the number of counts per state. Parameters ---------- df : pandas.DataFrame The DataFrame to be analyzed.

Gets the total word count and the total unique lemmas. Parameters ---------- df : pandas.DataFrame The DataFrame to be analyzed.

Generates a donut plot with the counts of 3 categories. Parameters ---------- df : pandas.DataFrame The DataFrame to be plotted.

Generates a map using the state counts. You will require to download the following file and extract its contents to a folder named: mexicostates

Generates a bar plot with the counts of the most used lemmas. Parameters ---------- df : pandas.DataFrame The DataFrame to be plo

Generates a bar plot with the sentiment scores of each sentence. Parameters ---------- df : pandas.DataFrame The DataFrame to be