You can analyze it like this. The process up to this point is morphological analysis. For visualization, I think that the characteristics of the weathering with you appear in the words in the sentence are ** nouns **, so I will extract only ** nouns ** from the morphologically parsed words. The code looks like this

import numpy as np
import pandas as pd
import MeCab

#Apply Neologd to Mecab
tagger = MeCab.Tagger('-Owakati -d /usr/local/lib/mecab/dic/mecab-ipadic-neologd')

tagger.parse('')
def tokenize_ja(text, lower):
    node = tagger.parseToNode(str(text))
    while node:
        if lower and node.feature.split(',')[0] in ["noun"]:#Specify the part of speech to be acquired by word-separation
            yield node.surface.lower()
        node = node.next
def tokenize(content, token_min_len, token_max_len, lower):
    return [
        str(token) for token in tokenize_ja(content, lower)
        if token_min_len <= len(token) <= token_max_len and not token.startswith('_')
    ]

#Reading training data
path='../data/tenkinoko.csv'
df_tenki=pd.read_csv(path,encoding="SHIFT-JIS")


wakati_tenkinoko_text = []
for i in df_tenki['text']:
    txt = tokenize(i, 1, 10000, True)
    wakati_tenkinoko_text.append(txt)
np.savetxt("../work/tenki_corpus.txt", wakati_tenkinoko_text,fmt='%s', delimiter=',')

df_tenki['wakati_tenkinoko'] = wakati_tenkinoko_text

The result looks like this ↓ Now you can extract only nouns from the text!

Visualize with wordclud

Once you've done morphological analysis, it's finally time for wordcloud! So, it doesn't look like a word cloud like "this" or "there" ~~ (I just want to say) ~~ Some nonsense words come out, so I've removed them as stop_words. The code looks like this

from wordcloud import WordCloud

tenki_wordlist = df_tenki['wakati_tenkinoko'].values.tolist()
word_cloud_list = []
for i in tenki_wordlist:
    for j in i:
        word_cloud_list.append(j)
        
result = ','.join(word_cloud_list)

#Japanese font path
fpath = "../data/ipaexg.ttf"

stop_words = ["of","Hmm","what","Sa","!?","of","SaHmm","Yo","Etc.","thing","It","so","ちゃHmm","What","want to see","As it is","くHmm","もof","!?」","There","Where","By the way","this","pie","なHmm","here"]

wordcloud = WordCloud(background_color='white',
    font_path=fpath, width=800, height=600, stopwords=set(stop_words)).generate(result)

#Save image
wordcloud.to_file('./wordcloud.png')

Execution result

Here are the results! Hey!

** It looks like it! !! !! !! ** ** After all, the claim of the character name is very intense. That's right because it's a novel. Besides, "Sempai", "Sunny woman", "Rooftop" and so on. There are some words that you can think of. I don't feel like the scene of the movie comes to mind just by looking at this image. Yes. ~~ (I don't know what it is, but I was a little impressed) ~~

Summary

I think the result was pretty good. It's fun to play with data. Next, I'm going to analyze it with word2vec. Then ~