词云图wordcloud多个案例展示

#!/usr/bin/env python """ Colored by Group Example ======================== Generating a word cloud that assigns colors to words based on a predefined mapping from colors to words """ from wordcloud import (WordCloud, get_single_color_func) import matplotlib.pyplot as plt class SimpleGroupedColorFunc(object): """Create a color function object which assigns EXACT colors to certain words based on the color to words mapping Parameters ---------- color_to_words : dict(str -> list(str)) A dictionary that maps a color to the list of words. default_color : str Color that will be assigned to a word that's not a member of any value from color_to_words. """ def __init__(self, color_to_words, default_color): self.word_to_color = {word: color for (color, words) in color_to_words.items() for word in words} self.default_color = default_color def __call__(self, word, **kwargs): return self.word_to_color.get(word, self.default_color) class GroupedColorFunc(object): """Create a color function object which assigns DIFFERENT SHADES of specified colors to certain words based on the color to words mapping. Uses wordcloud.get_single_color_func Parameters ---------- color_to_words : dict(str -> list(str)) A dictionary that maps a color to the list of words. default_color : str Color that will be assigned to a word that's not a member of any value from color_to_words. """ def __init__(self, color_to_words, default_color): self.color_func_to_words = [ (get_single_color_func(color), set(words)) for (color, words) in color_to_words.items()] self.default_color_func = get_single_color_func(default_color) def get_color_func(self, word): """Returns a single_color_func associated with the word""" try: color_func = next( color_func for (color_func, words) in self.color_func_to_words if word in words) except StopIteration: color_func = self.default_color_func return color_func def __call__(self, word, **kwargs): return self.get_color_func(word)(word, **kwargs) text = """The Zen of Python, by Tim Peters Beautiful is better than ugly. Explicit is better than implicit. Simple is better than complex. Complex is better than complicated. Flat is better than nested. Sparse is better than dense. Readability counts. Special cases aren't special enough to break the rules. Although practicality beats purity. Errors should never pass silently. Unless explicitly silenced. In the face of ambiguity, refuse the temptation to guess. There should be one-- and preferably only one --obvious way to do it. Although that way may not be obvious at first unless you're Dutch. Now is better than never. Although never is often better than *right* now. If the implementation is hard to explain, it's a bad idea. If the implementation is easy to explain, it may be a good idea. Namespaces are one honking great idea -- let's do more of those!""" # Since the text is small collocations are turned off and text is lower-cased wc = WordCloud(collocations=False).generate(text.lower()) color_to_words = { # words below will be colored with a green single color function '#00ff00': ['beautiful', 'explicit', 'simple', 'sparse', 'readability', 'rules', 'practicality', 'explicitly', 'one', 'now', 'easy', 'obvious', 'better'], # will be colored with a red single color function 'red': ['ugly', 'implicit', 'complex', 'complicated', 'nested', 'dense', 'special', 'errors', 'silently', 'ambiguity', 'guess', 'hard'] } # Words that are not in any of the color_to_words values # will be colored with a grey single color function default_color = 'grey' # Create a color function with single tone # grouped_color_func = SimpleGroupedColorFunc(color_to_words, default_color) # Create a color function with multiple tones grouped_color_func = GroupedColorFunc(color_to_words, default_color) # Apply our color function wc.recolor(color_func=grouped_color_func) # Plot plt.figure() plt.imshow(wc, interpolation="bilinear") plt.axis("off") plt.show()