Generate word cloud from single-column Pandas dataframe

Question

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.

I have attempted to do this with the following code:

To bring the data in:

fields = ['Crime type']

text2 = pd.read_csv('allCrime.csv', usecols=fields)

To generate the word cloud:

wordcloud2 = WordCloud().generate(text2)
# Generate plot
plt.imshow(wordcloud2)
plt.axis("off")
plt.show()

However, I get this error:

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):

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.

Answer 1

The problem is that the WordCloud.generate method that you are using expects a string on which it will count the word instances but you provide a pd.Series.

Depending on what you want the word cloud to generate on you can either do:

1. wordcloud2 = WordCloud().generate(' '.join(text2['Crime Type'])), which would concatenate all words in your dataframe column and then count all instances.

2. Use WordCloud.generate_from_frequencies to manually pass the computed frequencies of words.

Answer 2

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()

Answer 3

You need to create a concatenated input text. This can be done with the join function.

fields = ['Crime type']
text2 = pd.read_csv('allCrime.csv', usecols=fields)

text3 = ' '.join(text2['Crime Type'])
wordcloud2 = WordCloud().generate(text3)
# Generate plot
plt.imshow(wordcloud2)
plt.axis("off")
plt.show()

Answer 4

You can generate a word cloud while removing all the stop words for a single column. Let's say your data frame is df and col name is comment then the following code can help:

#Final word cloud after all the cleaning and pre-processing
import matplotlib.pyplot as plt
from wordcloud import WordCloud, STOPWORDS
comment_words = ' '
stopwords = set(STOPWORDS) 

# iterate through the csv file 
for val in df.comment: 
  
   # typecaste each val to string 
   val = str(val) 

   # split the value 
   tokens = val.split() 
  
# Converts each token into lowercase 
for i in range(len(tokens)): 
    tokens[i] = tokens[i].lower() 
      
for words in tokens: 
    comment_words = comment_words + words + ' '


wordcloud = WordCloud(width = 800, height = 800, 
            background_color ='white', 
            stopwords = stopwords, 
            min_font_size = 10).generate(comment_words) 

# plot the WordCloud image                        
plt.figure(figsize = (8, 8), facecolor = None) 
plt.imshow(wordcloud) 
plt.axis("off") 
plt.tight_layout(pad = 0) 

plt.show()