从单列 Pandas 数据帧生成词云
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Generate word cloud from single-column Pandas dataframe
提问by the_bonze
I have a Pandas dataframe with one column: Crime type. The column contains 16 different "categories" of crime, which I would like to visualise as a word cloud, with words sized based on their frequency within the dataframe.
我有一个包含一列的 Pandas 数据框：犯罪类型。该列包含 16 种不同的犯罪“类别”，我想将其可视化为词云，词的大小根据它们在数据框中的频率而定。
I have attempted to do this with the following code:
我尝试使用以下代码执行此操作：
To bring the data in:
将数据引入：
fields = ['Crime type']
text2 = pd.read_csv('allCrime.csv', usecols=fields)
To generate the word cloud:
生成词云：
wordcloud2 = WordCloud().generate(text2)
# Generate plot
plt.imshow(wordcloud2)
plt.axis("off")
plt.show()
However, I get this error:
但是，我收到此错误：
TypeError: expected string or bytes-like object
I was able to create an earlier word cloud from the full dataset, using the following code, but I want the word cloud to only generate words from the specific column, 'crime type' ('allCrime.csv' contains approx. 13 columns):
我能够使用以下代码从完整数据集创建一个较早的词云，但我希望词云仅从特定列“犯罪类型”（“allCrime.csv”包含大约 13 列）生成词：
text = open('allCrime.csv').read()
wordcloud = WordCloud().generate(text)
# Generate plot
plt.imshow(wordcloud)
plt.axis("off")
plt.show()
I'm new to Python and Pandas (and coding generally!) so all help is gratefully received.
我是 Python 和 Pandas 的新手（以及一般的编码！）所以非常感谢所有帮助。
回答by languitar
The problem is that the WordCloud.generatemethod that you are using expects a string on which it will count the word instances but your provide a pd.Series.
问题是WordCloud.generate您使用的方法需要一个字符串，它将计算单词实例，但您提供一个pd.Series.
Depending on what you want the word cloud to generate on you can either do:
根据您希望词云生成的内容，您可以执行以下任一操作：
wordcloud2 = WordCloud().generate(' '.join(text2['Crime Type'])), which would concatenate all words in your dataframe column and then count all instances.Use
WordCloud.generate_from_frequenciesto manually pass the computed frequencies of words.
wordcloud2 = WordCloud().generate(' '.join(text2['Crime Type']))，这将连接数据框列中的所有单词，然后计算所有实例。使用
WordCloud.generate_from_frequencies手动传字的计算的频率。
回答by drorhun
df = pd.read_csv('allCrime.csv', usecols=fields)
text = df['Crime type'].values
wordcloud = WordCloud().generate(str(text))
plt.imshow(wordcloud)
plt.axis("off")
plt.show()
