如何在python的wordcloud中显示每个用户制作的推文的正色和负色类别

问题描述

我正在尝试使用情感值基于类别和类别频率计数为用户创建wordcloud，如果情感值为“正”，则类别应以绿色显示，而负数应以红色显示。

|id                                  |sentiment|category|sentiment_count|category_count|rank|
+------------------------------------+---------+--------+---------------+--------------+----+
|276c08e3-29c6-416a-b522-5b1c7ad0a865|positive |Business|9              |9             |1   |
|276c08e3-29c6-416a-b522-5b1c7ad0a865|negative |Business|1              |1             |2   |
|09eb80df-76fd-4d94-8bb1-f4ffb0ece4c6|negative |World   |10             |10            |1   |
|09eb80df-76fd-4d94-8bb1-f4ffb0ece4c6|positive |Business|7              |7             |2   |
|09eb80df-76fd-4d94-8bb1-f4ffb0ece4c6|positive |Sci/Tech|6              |6             |3   |
|09eb80df-76fd-4d94-8bb1-f4ffb0ece4c6|negative |Business|2              |2             |4   |
|09eb80df-76fd-4d94-8bb1-f4ffb0ece4c6|negative |Sci/Tech|1              |1             |5   |
|09eb80df-76fd-4d94-8bb1-f4ffb0ece4c6|positive |Sports  |1              |1             |5   |
|09eb80df-76fd-4d94-8bb1-f4ffb0ece4c6|positive |World   |1              |1             |5   |
|4f11697e-d3f0-47a0-b1f8-aaacf7b720b7|positive |Sports  |12             |12            |1   |
|4f11697e-d3f0-47a0-b1f8-aaacf7b720b7|positive |Sci/Tech|1              |1             |2   |
|f29a2c29-91cf-41d8-a586-453218331710|positive |Sci/Tech|759            |759           |1   |
|f29a2c29-91cf-41d8-a586-453218331710|negative |Business|524            |524           |2   |
|f29a2c29-91cf-41d8-a586-453218331710|positive |Business|508            |508           |3   |
|f29a2c29-91cf-41d8-a586-453218331710|negative |World   |279            |279           |4   |
|f29a2c29-91cf-41d8-a586-453218331710|negative |Sci/Tech|220            |220           |5   |

我尝试使用代码。但不确定如何根据情绪（正负）对颜色进行分类

from wordcloud import WordCloud
import matplotlib.pyplot as plt
from wordcloud import WordCloud
import matplotlib.pyplot as plt
import pandas as pd 
import numpy as np
source1 = 'path_to_csv'
df1 = pd.read_csv(source1)
print(df1)            

uids1 = np.unique(df1['id'])

fig,axes = plt.subplots(nrows=(len(uids)+2)//3,ncols=3,figsize=(20,8),gridspec_kw={'hspace': 0.05,'wspace': 0.05,'left': 0.01,'right': 0.99,'top': 0.99,'bottom': 0.01})
for id,ax in zip(uids,axes.ravel()):
    data = df[df['id'] == id].set_index('category')['category_count'].to_dict()
    wc = WordCloud(width=800,height=400,max_words=200).generate_from_frequencies(data)
    ax.imshow(wc,interpolation='bilinear')
    ax.set_title(f'id = {id}')
    ax.axis('off')
    plt.savefig("/path/wordcloud_twitte.png",format="png")

解决方法

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