Example #1
0
from wordcloud import WordCloud
from csvcols import get_column
import matplotlib.pyplot as plt
import sys

categories = get_column(sys.argv[1], col=1)

wordcloud = WordCloud(width=1800,
                      height=1400,
                      max_words=10000,
                      random_state=1,
                      relative_scaling=0.25)
wordcloud.fit_words(categories.most_common(len(categories)))

plt.imshow(wordcloud)
plt.axis("off")
wordcloud.to_file("SFPD-wordcloud.png")
plt.show()
Example #2
0
from cloud import WordCloud
from csvcols import get_column
import matplotlib.pyplot as plt
import sys

categories = get_column(sys.argv[1], col=1)

wordcloud = WordCloud(width=1800,
                      height=1400,
                      max_words=10000,
                      random_state=1,
                      relative_scaling=0.25)
wordcloud.fit_words(categories.most_common(len(categories)))

plt.imshow(wordcloud)
plt.axis("off")
wordcloud.to_file("SFPD-wordcloud.png")
plt.show()
Example #3
0
from wordcloud import WordCloud
from csvcols import get_column
import matplotlib.pyplot as plt
import sys

neighborhoods = get_column(sys.argv[1], col=6)

wordcloud = WordCloud(width=1800,
                      height=1400,
                      max_words=10000,
                      random_state=1,
                      relative_scaling=0.25)
wordcloud.fit_words(neighborhoods.most_common(len(neighborhoods)))

plt.imshow(wordcloud)
plt.axis("off")
wordcloud.to_file("SFPD-hood-wordcloud.png")
plt.show()
Example #4
0
import sys

from csvcols import get_column

categories = get_column(sys.argv[1], col=1)
descriptions = get_column(sys.argv[1], col=2)

for c, n in categories.most_common(len(categories)):
    print "%6d %s" % (n, c)

for d, n in descriptions.most_common(len(descriptions)):
    print "%6d %s" % (n, d)