!pip install wordcloudRequirement already satisfied: wordcloud in c:\programdata\anaconda3\lib\site-packages (1.8.2.2)
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import numpy as np # linear algebra
import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)import nltk
nltk.download('punkt')
from nltk import wordpunct_tokenize
nltk.download('stopwords')
from nltk.corpus import stopwords[nltk_data] Downloading package punkt to C:\Users\Jonathan
[nltk_data] Oliva\AppData\Roaming\nltk_data...
[nltk_data] Package punkt is already up-to-date!
[nltk_data] Downloading package stopwords to C:\Users\Jonathan
[nltk_data] Oliva\AppData\Roaming\nltk_data...
[nltk_data] Package stopwords is already up-to-date!
import os
print(os.listdir())['.git', '.ipynb_checkpoints', 'dataset', 'LICENSE', 'README.md', 'wordcloud1.jpg', 'wordcloud_demostration.ipynb']
from wordcloud import WordCloud
import matplotlib.pyplot as plt
from PIL import Imagemydata = "dataset"print(os.listdir(mydata))['dnd-spells.csv', 'dnd.png']
df_dataset = pd.read_csv(mydata+"/dnd-spells.csv")df_dataset[:5]
<style scoped>
.dataframe tbody tr th:only-of-type {
vertical-align: middle;
}
</style>
.dataframe tbody tr th {
vertical-align: top;
}
.dataframe thead th {
text-align: right;
}
| name | classes | level | school | cast_time | range | duration | verbal | somatic | material | material_cost | description | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Acid Splash | Artificer, Sorcerer, Wizard | 0 | Conjuration | 1 Action | 60 Feet | Instantaneous | 1 | 1 | 0 | NaN | You hurl a bubble of acid. Choose one creature... |
| 1 | Blade Ward | Bard, Sorcerer, Warlock, Wizard | 0 | Abjuration | 1 Action | Self | 1 round | 1 | 1 | 0 | NaN | You extend your hand and trace a sigil of ward... |
| 2 | Booming Blade | Artificer, Sorcerer, Warlock, Wizard | 0 | Evocation | 1 Action | Self (5-foot radius) | 1 round | 0 | 1 | 1 | a melee weapon worth at least 1 sp | You brandish the weapon used in the spell’s ca... |
| 3 | Chill Touch | Sorcerer, Warlock, Wizard | 0 | Necromancy | 1 Action | 120 Feet | 1 round | 1 | 1 | 0 | NaN | You create a ghostly, skeletal hand in the spa... |
| 4 | Control Flames | Druid, Sorcerer, Wizard | 0 | Transmutation | 1 Action | 60 Feet | Instantaneous or 1 hour | 0 | 1 | 0 | NaN | You choose nonmagical flame that you can see w... |
def calcData(row):
counter = 0
for element in row:
if element == True:
counter+=1
return counterdf_dataset.isnull().apply(lambda x: calcData(x))name 0
classes 0
level 0
school 0
cast_time 0
range 0
duration 0
verbal 0
somatic 0
material 0
material_cost 264
description 0
dtype: int64
sum(df_dataset.duplicated('description'))0
stopwords_english = set(stopwords.words('english'))len(stopwords_english)179
def createCloudUnigrams(x):
y = nltk.word_tokenize(x)
return [word for word in y if not word in stopwords_english and word.isalnum()]
df_dataset['unigrams'] = df_dataset.apply(lambda x: createCloudUnigrams(x['description']),axis=1)df_dataset['unigrams'][:5]0 [You, hurl, bubble, acid, Choose, one, creatur...
1 [You, extend, hand, trace, sigil, warding, air...
2 [You, brandish, weapon, used, spell, casting, ...
3 [You, create, ghostly, skeletal, hand, space, ...
4 [You, choose, nonmagical, flame, see, within, ...
Name: unigrams, dtype: object
unigrams = df_dataset['unigrams']
cloud_set = {}
for terms in unigrams:
counter = 0
for term in terms:
cloud_set[term] = cloud_set.get(term,0) + 1dict(list(cloud_set.items())[:10]){'You': 660,
'hurl': 9,
'bubble': 1,
'acid': 37,
'Choose': 56,
'one': 379,
'creature': 1298,
'within': 603,
'range': 359,
'choose': 187}
# getting figure
tweet_mask = np.array(Image.open(mydata + "/dnd.png"))wc = WordCloud(background_color="white", mask=tweet_mask,contour_width=1)
wc.generate_from_frequencies(cloud_set)
plt.figure( figsize=(20,20))
plt.imshow(wc)
plt.axis("off")
plt.show()
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