You can use libraries like spaCy or Stanza to visualize sentence dependency structure in Python. These libraries provide tools for natural language processing (NLP), including dependency parsing.
Here is the code uses the gensim library to load a pre-trained Word2Vec model and find words that are semantically similar to the word "king".
It is very convenient to use Python to load raw text data into the memory for data processing. Here, we provide the code template for your reference. It shows you how to list the data files that you want and read the text data into a list.
This post shows you how to calculate the keyword frequency from text and draw the bar chart by using the JpGraph library.