#!/usr/bin/env python

# coding: utf-8

# In[2]:

import tweepy

from wordcloud import WordCloud, STOPWORDS

import collections

import numpy as np

from PIL import Image

import matplotlib.pyplot as plt

import MeCab

import subprocess

import pandas as pd

import csv

# In[29]:

df = pd.read_csv("tweet_selection.csv")

data = ""

for i in range(len(df.index)):

if df.iat[i,1] == 0:

data = data + df.iat[i,0]

# In[4]:

#テキストの分かち書き

me = MeCab.Tagger ("-Owakati")

me.parseToNode('')

nodes = me.parseToNode(data)

#各変数の初期化

meishi_count = 0

doushi_count = 0

keiyou_count = 0

meishi_list=[]

doushi_list=[]

keiyou_list=[]

# In[24]:

#形態素のうち名詞，動詞，形容詞のみを抽出し，カウント

while nodes:

if nodes.feature.split(",")[0] == "名詞":

meishi_count = meishi_count + 1

meishi_list.append(nodes.surface)

elif nodes.feature.split(",")[0] == "動詞":

doushi_count = doushi_count + 1

doushi_list.append(nodes.surface)

elif nodes.feature.split(",")[0] == "形容詞":

keiyou_count = keiyou_count + 1

keiyou_list.append(nodes.surface)

else:

pass

nodes = nodes.next

text = ""+ " ".join(meishi_list) + " ".join(doushi_list) + " ".join(keiyou_list)

# In[27]:

#WCの下ごしらえ

stop_words = ["https", "co", "てる", "する", "そう", "すぎ", "いい", "さん", "こと"]

fpath = "/Library/Fonts//ヒラギノ丸ゴ ProN W4.ttc"

wc = WordCloud(

)

# WordCloudの実行

wc.generate(text)

wc.to_file("word_cloud.png")

plt.figure(figsize=(15,12))

plt.imshow(wc)

plt.axis("off")

plt.show()