Generate a Word Cloud
A word cloud (also known as a tag cloud) is a visual representation of the most frequently used words in a piece of text. The size of each word in the cloud corresponds to its frequency of use, with the most frequently used words appearing larger and more prominent than less frequently used words.
Word clouds are often used to quickly and easily identify the most important or relevant words in a piece of text, such as a document, a webpage, or a set of social media posts. They can be used in a variety of applications, such as text mining, content analysis, and social media monitoring.
Opgave
Swipe to start coding
- Import
WordCloud,STOPWORDS,ImageColorGeneratorfromwordcloud. - Select only the
"neutral"tweets (the"sentiment"column). - Create a plot using the
plot_wordcloud()function.
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from PIL import Image
import numpy as np
from wordcloud import WordCloud, STOPWORDS, ImageColorGenerator
def plot_wordcloud(text, mask=None, max_words=200, max_font_size=100, figure_size=(24.0,16.0), color = 'white',
title = None, title_size=40, image_color=False):
stopwords = set(STOPWORDS)
more_stopwords = {"u", "im"}
stopwords = stopwords.union(more_stopwords)
wordcloud = WordCloud(background_color=color,
stopwords = stopwords,
max_words = max_words,
max_font_size = max_font_size,
random_state = 42,
width=600,
height=300,
mask = mask)
wordcloud.generate(str(text))
plt.figure(figsize=figure_size)
if image_color:
image_colors = ImageColorGenerator(mask);
plt.imshow(wordcloud.recolor(color_func=image_colors), interpolation="bilinear");
plt.title(title, fontdict={"size": title_size,
"verticalalignment":"bottom"})
else:
plt.imshow(wordcloud);
plt.title(title, fontdict={"size": title_size, "color": "black",
"verticalalignment": "bottom"})
plt.axis("off");
plt.tight_layout()
Neutral_sent = data[data["sentiment"]=="neutral"]
plot_wordcloud(Neutral_sent.text,color='white',max_font_size=100,title_size=30,
title="WordCloud of Neutral Tweets")
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