带有matplotlib散点图的颜色的季节性循环 [英] seaborn cycle through colours with matplotlib scatter

问题描述

在绘制散点图时如何获得 seaborn 颜色?

How can I get seaborn colors when doing a scatter plot?

import matplotlib.pyplot as plt
import seaborn as sns
ax=fig.add_subplot(111)
for f in files:
    ax.scatter(args) # all datasets end up same colour
    #plt.plot(args) #  cycles through palette correctly

推荐答案

您必须告诉matplotlib使用哪种颜色.例如，使用 seaborn 的默认调色板:

You have to tell matplotlib which color to use. To Use, for example, seaborn's default color palette:

import matplotlib.pyplot as plt
import seaborn as sns
import itertools
ax=fig.add_subplot(111)

palette = itertools.cycle(sns.color_palette())

for f in files:
    ax.scatter(args, color=next(palette))

itertools.cycle 确保我们不会用完颜色并在使用完最后一个后再次从第一个开始.

The itertools.cycle makes sure we don't run out of colors and start with the first one again after using the last one.

更新:

根据@Iceflower的评论，通过创建自定义调色板

As per @Iceflower's comment, creating a custom color palette via

palette = sns.color_palette(None, len(files))

可能是更好的解决方案.不同之处在于，我最上面的原始答案会根据需要多次遍历默认颜色，而此解决方案创建的调色板具有与文件一样多的色相.这意味着不会重复任何颜色，但是颜色之间的差异可能非常细微.

might be a better solution. The difference is that my original answer at the top iterates through the default colors as often as it has to, whereas this solution creates a palette with as much hues as there are files. That means that no color is repeated, but the difference between colors might be very subtle.

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