The emoji does show how the color effect works, but it isn’t a great example. Word Cloud Color Example- image by author You may need to reduce max_font_size to improve the look of image details ) # note - need to set max font size, or font extends over the colors mask = np.array(Image.open(“paint1.png”)) emo_clr = WordCloud(background_color=”white”, mode=”RGBA”, max_words=3000, max_font_size=18, mask=mask).generate(emoji_text) # create coloring from image image_colors = ImageColorGenerator(mask) plt.figure(figsize=) plt.imshow(emo_clr.recolor(color_func=image_colors), interpolation=”bilinear”) plt.axis(“off”) plt.show() (The dark patches are the eyes and mouth of our emoji. You can also use the ImageColorGenerator function to set the colormap to match the image. emoji_mask = np.array(Image.open(“1F642_color.png”)) emoji_mask array(, …, ], dtype=uint8) # replace 0 with 255 emoji_mask = 255 emoji_mask array(, …, ], dtype=uint8) Colors You can inspect your image by looking at the array. The mask needs the white value to be 255 and not 0. If your image has a transparent background, it will throw an error. Word Cloud Shape - image by author Bad Transparency Mask Error Its tone can also be patronizing, passive-aggressive, or ironic, as if saying This is fine when it’s really not.” Conveys a wide range of positive, happy, and friendly sentiments. “A yellow face with simple, open eyes and a thin, closed smile. So, how do you make your Word Cloud jump out from the cloud? Getting Startedįor these examples, I will use an Emoji from OpenMojiand text about emojis from Wikipedia to form the cloud. They are handy as an introduction and to break up heavy text passages. Words Clouds are an excellent tool for drawing attention. There are plenty of other blogs for that. You didn’t read this blog to learn about how terrible Word Clouds are. The popularity and drawbacks of Word Clouds mean that they have many detractors - my favorite Word Cloud (or “Tag Cloud”) insult is that they are “the new mullets”… ouch. In some cases, the opposite meaning is highlighted - for example, the phrase “not good” would be represented on a Word Cloud as “good” after the stopword of “not” is removed.ĭespite these limitations, Word Clouds have become incredibly popular, primarily because they are easy to create. We don’t learn anything about the context of the words.Longer words receive greater emphasis than shorter words because their length takes up more space.However, in Word Clouds, the word order is at random. Positioning in visualization is usually very important.We don’t know how the words are weighted - what does a large font actually mean? Does the word with the large font occur 10 times or 1000 times?.We can distinguish between large, medium, and small fonts beyond that, it gets tricky. Font size is not an effective way to show differences.Here are some of the problems with Word Clouds. They may be more attractive to look at than a simple bar chart - but they provide far less information. They are not helpful for an in-depth analysis. However, Word Clouds do have limitations. They are eye-catching and easy to understand without the need for any additional explanation. Word Clouds are a straightforward way to summarize text and make the most popular words jump to your attention. This blog will cover Word Clouds, their limitations, followed by some formatting examples. Tips on Using and Designing Word Clouds in Python
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