具有特定形狀的多個詞云圖

我有一個相當具體的問題。對于出版事宜，我想為 LDA 生成的每個主題制作 wordcloud 圖。

我目前的代碼是這樣的：

import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
from wordcloud import WordCloud
sns.set()

topics_df = pd.DataFrame({'Unnamed: 0': {0: 'Topic1', 1: 'Topic2', 2: 'Topic3', 3: 'Topic4', 4: 'Topic5'}, 'Terms per Topic': {0: 'charge, model, infrastructure, station, time, base, propose, drive, public, service, range, problem, study, paper, network, user, travel, battery, city, method', 1: 'cost, emission, fuel, car, high, price, low, reduce, hybrid, carbon, battery, gas, alternative, benefit, compare, find, conventional, efficiency, gasoline, total', 2: 'market, technology, policy, paper, change, development, support, mobility, business, industry, government, focus, study, transition, innovation, decision, develop, technological, case, lead', 3: 'consumer, policy, adoption, effect, model, purchase, bev, factor, evs, study, incentive, choice, preference, subsidy, influence, environmental, state, level, suggest, analysis', 4: 'energy, system, electricity, demand, transport, scenario, impact, increase, power, phev, transportation, sector, potential, base, show, consumption, reserve, term, economic, grid'}})

wc = WordCloud(background_color="white", colormap="Dark2",
               max_font_size=150, random_state=42)

plt.rcParams['figure.figsize'] = [20, 15]

# Create subplots for each topic
for i in range(5):
    wc.generate(text=topics_df["Terms per Topic"][i])   
    plt.subplot(5, 4, i 1)
    plt.imshow(wc, interpolation="bilinear")
    plt.axis("off")
    plt.title(topics_df.index[i])
plt.show()

我想要的輸出是讓每個 wordcloud 圖都呈圓形，周圍有一個黑邊。我想在 PCA 圖表上使用每個 Wordcloud。

uj5u.com熱心網友回復：

你可以試試這個：

代碼

import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
from wordcloud import WordCloud
sns.set()
plt.rcParams['figure.figsize'] = [20, 15]

topics_df = pd.DataFrame({'Unnamed: 0': {0: 'Topic1', 1: 'Topic2', 2: 'Topic3', 3: 'Topic4', 4: 'Topic5'}, 'Terms per Topic': {0: 'charge, model, infrastructure, station, time, base, propose, drive, public, service, range, problem, study, paper, network, user, travel, battery, city, method', 1: 'cost, emission, fuel, car, high, price, low, reduce, hybrid, carbon, battery, gas, alternative, benefit, compare, find, conventional, efficiency, gasoline, total', 2: 'market, technology, policy, paper, change, development, support, mobility, business, industry, government, focus, study, transition, innovation, decision, develop, technological, case, lead', 3: 'consumer, policy, adoption, effect, model, purchase, bev, factor, evs, study, incentive, choice, preference, subsidy, influence, environmental, state, level, suggest, analysis', 4: 'energy, system, electricity, demand, transport, scenario, impact, increase, power, phev, transportation, sector, potential, base, show, consumption, reserve, term, economic, grid'}})

x, y = np.ogrid[:300, :300]
mask = (x - 150) ** 2   (y - 150) ** 2 > 130 ** 2
mask = 255 * mask.astype(int)

wordcloud = WordCloud(background_color="white", mask=mask, contour_width=0.1, 
                      contour_color="black",  max_font_size=150, random_state=42,
                      colormap="Dark2")

for i in range(5):
    wordcloud.generate(text=topics_df["Terms per Topic"][i])   
    plt.subplot(5, 4, i 1)
    plt.imshow(wordcloud, interpolation="bilinear")
    plt.axis("off")
    plt.title(topics_df.index[i])
plt.show()

結果

標籤：Python matplotlib 形状 词云

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