[PYTHON] [Note] WordCloud from morphological analysis

Move the text that was in the python file to another file

textmining_source.txt

What is scaffold?
A convenient tool that automatically sets all the basic actions in addition to creating the routes, controllers, and views required for Rails development.

[Goodness of scaffold that I personally felt]
(1) Not only the creation of the controller, but also 7 basic actions are automatically set.
In the controller created by scaffold, seven actions of "index", "show", "new", "edit", "create", "update", and "destroy" are automatically defined. As a result, you can quickly browse, create, modify, or delete data without having to set your own actions.

(2) The routing corresponding to the created controller is also set automatically.
routes after the scaffold command.In rb, "resources:The description "Controller name" has been added, and the routing corresponding to the newly created controller is automatically set.

③ All views corresponding to the actions defined in the controller are automatically generated.
When scaffold is used, all view files corresponding to the actions defined in the controller are also automatically generated.

④ The necessary model and migration file are also automatically generated.
In scaffold, if you specify "column name: data type" when entering a command, a model and migration file containing the specified information will be automatically generated.
Therefore, the rest is "$ rake db:You can easily create a database table just by entering the "migrate" command. (Details of this area will be described later)

→ Of course, I think it's a little different (or rather wasteful) to create an application to be released to the world using scaffold, but personally I make a prototype to implement the function I'm interested in I find it extremely convenient above.

So, the procedure for creating a Rails application using scaffold is described below.
It's really easy, so if you like, please try it out!

And finally, visualization using WordCloud

with open('textmining_source.txt') as f:
    text = f.read()

keywords = t.parse(text)

words = []
for x in keywords.split("\n"):
    word = x.split("\t")[0]
    if word == "EOS":
        break
    else:
        category = x.split("\t")[1].split(",")[0]
        if category == "noun":
                words.append(word)
        else:
            category = x.split("\t")[1].split(",")[0]
            if category == "adjective":
                words.append(word)

splitted =' '. join(words)
keywords = splitted.replace(',',' ')
 
wordcloud = WordCloud(
    background_color="white",
    stopwords={"thing","this","For","It","By the way","Yo","of","Etc.","thing"},
    font_path="NotoSansCJKjp-hinted/NotoSansCJKjp-Regular.otf",
    width=800,height=600).generate(keywords)
 
 
wordcloud.to_file("./textmining_result.png ")

WordCloud

By the way, the following is a visualization of Steve Jobs' famous speech in WordCloud. It seems that you can get a sense of the whole story just by looking at it!

• Reference source for speech content: https://kigyotv.jp/news/special16/ The first story

Second story

Third story