<jupyter_start><jupyter_text>Wordcloud for previous topics presented at The Hacker WithinBy <NAME>, licensed CC-BY 4.0 and the MIT licenseData scraped from [THW's website](http://www.thehackerwithin.org/berkeley/previous.html) in an embarassingly manual way. I cleaned up some terms and replaced "R" with "RR" because the wordcloud package has trouble with single-letter words.<jupyter_code>!pip install wordcloud
%matplotlib inline
from os import path
from wordcloud import WordCloud


# Read the whole text.
text = open('session_titles.tsv').read().lower()

# Generate a word cloud image
wordcloud = WordCloud(width=3000, height=2000, prefer_horizontal=1, stopwords=None).generate(text)

# Display the generated image:
# the matplotlib way:
import matplotlib.pyplot as plt
plt.figure(figsize=(30,15))
plt.imshow(wordcloud)
plt.axis("off")
plt.savefig("cloud2.png")<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.1015625, 'fraction_numerical': 0.017857142857142856, 'mean_word_length': 6.413223140495868, 'pattern_counts': {'":': 0, '<': 6, '<?xml version=': 0, '>': 6, 'https://': 0, 'lorem ipsum': 0, 'www.': 1, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '233960', 'license': 'CC-BY-3.0', 'n_tokens_mistral': 292, 'n_tokens_neox': 275, 'n_words': 88, 'path': 'code_examples/spring17_survey/session_titles.ipynb', 'repo_name': 'matthew-brett/UoB', 'size': '906'}