原文转载 https://segmentfault.com/a/1190000014966210

Seaborn学习大纲

seaborn的学习内容主要包含以下几个部分:

  1. 风格管理

    • 绘图风格设置
    • 颜色风格设置
  2. 绘图方法

    • 数据集的分布可视化
    • 分类数据可视化
    • 线性关系可视化
  3. 结构网格

    • 数据识别网格绘图

本次将主要介绍颜色调控的使用。

颜色风格设置

 

在Seaborn的使用中,是可以针对数据类型而选择合适的颜色,并且使用选择的颜色进行可视化,节省了大量的可视化的颜色调整工作。还是一样,在介绍如何使用颜色外观设置之前,我们引入所需要的模块。

In [1]:
%matplotlib inline
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
sns.set(rc={"figure.figsize": (6, 6)})# 表示图标长宽尺寸,大小为英尺(inch)
np.random.seed(sum(map(ord, "palettes")))
 

建立调色板

 

对于不连续的外观颜色设置而言,最重要的函数恐怕要属color_palette了。这个函数拥有许多方法,让你可以随心所欲的可以生成各种颜色。并且,它可以被任何有palette参数的函数在内部进行使用(palette的中文意思是 "调色板")。 关于这个函数有几个点需要知道一下:

 

**(1)color_palette函数可以接受任何seaborn或者matplotlib颜色表中颜色名称(除了jet),也可以接受任何有效的matplotlib形式的颜色列表(比如RGB元组,hex颜色代码,或者HTML颜色名称)。

 

**(2)这个函数的返回值总是一个由RGB元组组成的列表,无参数调用color_palette函数则会返回当前默认的色环的列表。

In [2]:
sns.color_palette()
Out[2]:
[(0.2980392156862745, 0.4470588235294118, 0.6901960784313725),
(0.8666666666666667, 0.5176470588235295, 0.3215686274509804),
(0.3333333333333333, 0.6588235294117647, 0.40784313725490196),
(0.7686274509803922, 0.3058823529411765, 0.3215686274509804),
(0.5058823529411764, 0.4470588235294118, 0.7019607843137254),
(0.5764705882352941, 0.47058823529411764, 0.3764705882352941),
(0.8549019607843137, 0.5450980392156862, 0.7647058823529411),
(0.5490196078431373, 0.5490196078431373, 0.5490196078431373),
(0.8, 0.7254901960784313, 0.4549019607843137),
(0.39215686274509803, 0.7098039215686275, 0.803921568627451)]
 

**(3)还有一个相应的函数,是set_palette,它接受与color_palette一样的参数,并会对所有的绘图的默认色环进行设置。当然,你也可以在with语句中使用color_palette来临时的改变默认颜色。

 

有三种通用的color palette可以使用,它们分别是:qualitative,sequential,diverging。

 

分类色板(quanlitative)

 

Qualitative调色板,也可以说成是类型调色板,因为它对于分类数据的显示很有帮助。当你想要区别不连续的且内在没有顺序关系的 数据时,这个方式是最好的。 当导入seaborn时,默认的色环就被改变成一组包含10种颜色的调色板,它使用了标准的matplolib色环,为了让绘图变得更好看一些。

In [3]:
current_palette = sns.color_palette()
sns.palplot(current_palette)
 
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有6种不同的默认主题,它们分别是:deep,muted,pastel,birght,dark,colorblind。

In [6]:
themes = ['deep', 'muted', 'pastel', 'bright', 'dark', 'colorblind']
for theme in themes:
current_palette = sns.color_palette(theme)
sns.palplot(current_palette)
 
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使用色圈系统

 

默认的6种主题看上去真不错,但是如果我们想要超过6种颜色呢? 当你有超过6种类型的数据要区分时,最简单的方法就是 在一个色圈空间内使用均匀分布的颜色。这也是当需要使用更多颜色时大多数seaborn函数的默认方式。 最常用的方法就是使用 hls 色空间,它是一种简单的RGB值的转换。

In [7]:
sns.palplot(sns.color_palette("hls", 8))
 
aaarticlea/png;base64,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" alt="" />
 

除此之外,还有一个 hls_palette 函数,它可以让你控制 hls 颜色的亮度和饱和度。

In [8]:
sns.palplot(sns.hls_palette(8, l=.3, s=.8))
 
aaarticlea/png;base64,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" alt="" />
 

然而,由于人类视觉系统工作的原因,根据RGB颜色产生的平均视觉强度的颜色,从视觉上看起来并不是相同的强度。如果你观察仔细,就会察觉到,黄色和绿色会更亮一些,而蓝色则相对暗一些。因此,如果你想用hls系统达到一致性的效果,就会出现上面的问题。

 

为了修补这个问题,seaborn给hls系统提供了一个接口,可以让操作者简单容易的选择均匀分布,且亮度和饱和度看上去明显一致的色调。

In [9]:
sns.palplot(sns.color_palette("husl", 8))
 
aaarticlea/png;base64,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" alt="" />
 

同样与之对应的,也有个husl_palette函数提供更灵活的操作。

 

使用分类Color Brewer调色板

 

另外一种对分类数据比较友好的调色板来自Color Brewer工具。在matplotlib中也存在这些颜色表,但是它们并没有被合适的处理。在seaborn中,当你想要分类的 Color Brewer 调色板的时候,你总是可以得到不连续颜色,但是这也意味着在某一点上,这些颜色将会开始循环。

Color Brewer 网站中的一个很好的特点就是它提供了一个色盲安全指导。色盲颜色有很多种http://en.wikipedia.org/wiki/Color_blindness,但是最常见的当属辨别绿色和红色。如果可以避免使用红色和绿色来对绘图元素上色,那么对于一些色盲人群将会是一个很好的消息。

 

下面两组颜色就是使用红色和绿色组合,这可能并不是最好的选择。

In [10]:
sns.palplot(sns.color_palette("Paired"))
 
aaarticlea/png;base64,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" alt="" />
In [11]:
sns.palplot(sns.color_palette("Set2", 10))
 
aaarticlea/png;base64,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" alt="" />
 

为了避免这些组合,我们需要从Color Brewer库中进行选择调色,有一个专门的 choose_colorbrewer_palette 函数可以实现这个功能。这个函数需要在 IPython notebook 中使用,因为 notebook 是一个交互式的工具,可以让你浏览各种选择并且调节参数。

In [15]:
sns_type = ["qualitative", "sequential", "diverging"]
for elem in sns_type:
sns.choose_colorbrewer_palette(elem)
#n:调节颜色的个数;
#desat:调节明暗和饱和度;
 
 

当然,您可能只想使用一组您特别喜欢的颜色。因为color_palette()接受一个颜色列表,这很容易做到。

In [16]:
flatui = ["#9b59b6", "#3498db", "#95a5a6", "#e74c3c", "#34495e", "#2ecc71"]
sns.palplot(sns.color_palette(flatui))
 
aaarticlea/png;base64,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" alt="" />
 

使用xkcd颜色来命名颜色

 

在众多的努力帮助下,xkcd 完成了随机的 RGB 颜色的命名。一共生成了954个颜色http://xkcd.com/color/rgb/,并可可以随时通过xkcd_rgb字典调用。

In [17]:
plt.plot([0, 1], [0, 1], sns.xkcd_rgb["pale red"], lw=3)
plt.plot([0, 1], [0, 2], sns.xkcd_rgb["medium green"], lw=3)
plt.plot([0, 1], [0, 3], sns.xkcd_rgb["denim blue"], lw=3);
 
aaarticlea/png;base64,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" alt="" />
 

如果想要从 xkcd_rgb 字典中单独的抽取出一些颜色,你也可以将一组选择好的颜色放到 xkcd_palette 函数中。

In [18]:
colors = ["windows blue", "amber", "greyish", "faded green", "dusty purple"]
sns.palplot(sns.xkcd_palette(colors))
 
aaarticlea/png;base64,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" alt="" />
 

连续色板(sequential)

 

调色板的第二大类被成为 "顺序",这种调色板对于有从低(无意义)到高(有意义)范围过度的数据非常适合。尽管有些时候你可能想要在连续色板中使用不连续颜色,但是更通用的情况下是连续色板会作为颜色表在 kdeplot() 或者 corrplot() 或是一些 matplotlib 的函数中使用。

对于连续的数据,最好是使用那些在色调上有相对细微变化的调色板,同时在亮度和饱和度上有很大的变化。这种方法将自然地将数据中相对重要的部分成为关注点。

Color Brewer 的字典中就有一组很好的调色板。它们是以在调色板中的主导颜色(或颜色)命名的。

In [19]:
sns.palplot(sns.color_palette("Blues"))
 
aaarticlea/png;base64,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" alt="" />
 

就像在matplotlib中一样,如果您想要翻转渐变,您可以在面板名称中添加一个_r后缀。

In [20]:
sns.palplot(sns.color_palette("BuGn_r"))
 
aaarticlea/png;base64,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" alt="" />
 

seaborn还增加了一个允许创建没有动态范围的"dark"面板。如果你想按顺序画线或点,这可能是有用的,因为颜色鲜艳的线可能很难区分。

In [21]:
sns.palplot(sns.color_palette("dark"))
 
aaarticlea/png;base64,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" alt="" />
 

类似的,这种暗处理的颜色,需要在面板名称中添加一个_d后缀。

In [22]:
sns.palplot(sns.color_palette("GnBu_d"))
 
aaarticlea/png;base64,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" alt="" />
 

注意,你可能想使用 choose_colorbrewer_palette() 函数取绘制各种不同的选项。如果你想返回一个变量当做颜色映射传入seaborn或matplotlib的函数中,可以设置 as_cmap 参数为True。

 

“cubehelix”连续调色板

 

cubehelix调色板系统在亮度和色变变化上具有线性上升或下降的特点。这意味着,当颜色表中的信息被转化为黑色和白色或者被一个色盲者看到的时候,它将会被保存下来。

 

matplotlib 有内建的默认cubehelix 版本:

In [23]:
sns.palplot(sns.color_palette("cubehelix", 8))
 
aaarticlea/png;base64,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" alt="" />
 

seaborn为cubehelix系统添加一个接口使得其可以在各种变化中都保持良好的亮度线性梯度。

通过seaborn的cubehelix_palette()函数返回的调色板与matplotlib默认值稍有所不同,它不会在色轮周围旋转或覆盖更广的强度范围。seaborn还改变了排序使得更重要的值显得更暗:

In [24]:
sns.palplot(sns.cubehelix_palette(8))
 
aaarticlea/png;base64,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" alt="" />
 

其他cubehelix_palette()的参数主要调整色板的视觉。两个重要的选择是:start(值的范围为03)和rot,或者旋转的次数(-1和1之间)

In [25]:
sns.palplot(sns.cubehelix_palette(8, start=.5, rot=-.75))
 
aaarticlea/png;base64,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" alt="" />
 

你也可以控制断点的亮度和甚至对调结果顺序:

In [26]:
sns.palplot(sns.cubehelix_palette(8, start=2, rot=0, dark=0, light=.95, reverse=True))
 
aaarticlea/png;base64,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" alt="" />
 

默认情况下你只会得到一些像seaborn其它调色板一样的颜色列表,但你也可以通过使用as_cmap=True让调色板返回一个可以被传入seaborn或matplotlib函数的颜色映射对象。

In [27]:
x, y = np.random.multivariate_normal([0, 0], [[1, -.5], [-.5, 1]], size=300).T
cmap = sns.cubehelix_palette(light=1, as_cmap=True)
sns.kdeplot(x, y, cmap=cmap, shade=True);
 
aaarticlea/png;base64,iVBORw0KGgoAAAANSUhEUgAAAXMAAAD7CAYAAACYLnSTAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy8QZhcZAAAVvklEQVR4nO3dfajldZ3A8fcdG5UcnO1B0yZtlOrTA4ZSbZBK1A6xLLFupMnGRhD2ABEEZbCboBYFu5BKixBtDxQWhhXSYixsa7SJLEUlRuYX2xzTcdrKTHcmsEnv/nHudU/He+/5PXx/T9/zfoEwM3fuOV9n5r7P535/v/P7ra2vryNJmrZdQy9AktSeMZekAhhzSSqAMZekAhhzSSrA0wZ4zhOAVwGHgccHeH5JmqLjgNOB7wOPLX5wiJi/CvjuAM8rSSW4ELht8ReHiPlhgGNHHwXPcZekatbW2H3SybDR0EVDxHy2tbK+DutPDPD0kjRFTx7i3HJ72gOgklQAYy5JBTDmklQAYy5JBTDmklQAYy5JBTDmklQAYy5JBTDmklQAYy5JBTDmklQAYy5JBTDmklQAYy5JBTDmklQAYy5JBWh1c4qI+AhwMbAOfDaldE2WVUmSamk8mUfEa4HXAy8HXgm8LyIi18IkSdU1jnlK6TvA61JKfwROZTblH821MElSda32zFNKxyLiauAu4D+AQ1lWJUmqpfUB0JTSlcApwBnAO1uvSJJUW5s98xdHxLkAKaXfA19ntn8uSepZm7NZzgaujogLmJ3NchHwuSyrkiTV0uYA6DeBW4AfAT8Abk8p3ZhrYZKk6tbW19f7fs79wL3HjjwC60/0/dySNE1ru9i9Zy/AWcDBxQ/7DlBJKoAxl6QCGHNJKoAxl6QCGHNJKoAxl6QCGHNJKoAxl6QCGHNJKoAxl6QCGHNJKoAxl6QCGHNJKoAxl6QCGHNJKoAxl6QCGHNJKoAxl6QCGHMV5+j993H0/vuGXobUq6cNvQCprqqhrvL7Tjrj+W2XI42CMdfodTllLz62cddUtYp5RFwJvGXjp7eklD7UfklStwGv8rxGXVPTeM88Ig4AbwDOA84FXhERb8q1MK2msex3j2UdUlVtJvPDwAdSSn8AiIifAmdmWZVWzljDefT++5zSNQmNY55S+snmjyPihcy2W87PsSitjrFGfJ5bL5qC1qcmRsTLgH8HLk8p3dN+SVoVUwj5PLdeNGZtD4CeD3wNeH9K6cY8S1Lpph5EJ3WNUeOYR8QZwM3ApSmlW/MtSSXrKuRHDv6SPftP6+SxtzP//2LYNbQ2k/kHgROBayJi89c+lVL6VOtVqUhtQ37k4C8bf7zr0Hu+uoa2tr6+3vdz7gfuPXbkEVh/ou/n1gDaRHxZwJvoe4LfjsFXLWu72L1nL8BZwMHFD/sOUHWqaci7iPjiYw8d9Z3+bAy96jLm6kyTkHcZ8Z2ea+iwL3LbRnUZc2U39ojv9Pxji/omD7ZqGWOurKYY8nljntY3GXZtxZgrm6mHfNGUwm7UZcyVRZ8h/90vHq78e//szGc0eo5FQ572WIVRlzFXa32EvE7At/u8XGFf1Oa7i9wvBF4YbHUZc7VSN+R9RXzZY3UV9rq2+vNoG3iDvpqMuRqbUsiXPfZY4g559uoN+uox5mqk64tldRnyKs83lri3OWXSoK8WY67aut4j7zvkddcwROibRt2grw5jrlpWIeTLtF1jmxeDJleHNOirwZirMkOex1b/n3UCb9C1ldZ3GtJqMOTd+t0vHq71Z3Dk4C9rH1Ce+k1BtDNjrk6M+Z2dY9Yk6nUY9HK5zaKlpnTmyq8feDTbYy065Xknd/bYizb/TKpsv9TddnHLpUzGXDuayvVWuox4m+do+wLwu188bNBViXca0rbG/Db9eX2EPJemca96gLTJ+ehGfSKW3GnIPXNtyYm8G79+4NEn/6uj6otek78D99HLYMw1mLZT+dRCvqhu1LsOulGfNmOup5jCVD71kM+rE/Uugw5GfcpaHwCNiJOB24E3ppQOtl6RBtXXF3KbqbxtyA8dPtLq8zftO31PlsfZ9OsHHq20p97VQdF5Xh99elrFPCJeDfwL8KI8y9EU9TmVNw15roDv9Jg54j6moINRn5K22yzvBN4LPJhhLRrYFKbyug4dPtJJyHd6rrbP18WWS9sXXLdexq9VzFNKl6WUvptrMZqesU7lfUa8i+fPHXRo/3flfvq4eQBUwPin8rohH4s2Ue8q6Ea9TL4DVKPXZcgP/uqRSr9v/6l7az3uokOHj2Q/YDqv6h76pjY3vdjkfvq4GHMVM2VVDXnVgG/3OU3D3iToVQ+IQr3ruWzKFXWDPjy3WTRqVafyKiE/+KtHGoU85+M02Xbp6t2i89puv7j1MjyvzbLi2n4Bdnktltwh70rTSb3Jtkvda7s0uatRmykd3HbpjNdmUcmWhTzXNN7FczQ5MNpkSq87qeeY0tU/Y65RqhKtKiHv01iDDv1H3W2X/hnzFVbyF1vfIZ9/3rrP3XQfvc+oN1Xyv7Gx8WwWTVLOc8l//tBvdvz42c96du3HPPirR2rvpTc92wXq76X3eSqjZ7v0w8lcxak6Gf/8od8sDXmd37fVOvqY0qHZpN7nlO6E3j1jrtFZFqUcU3mTOBv1GYM+TsZcrbQ9jS23PvbKh4h60z31Lm5+AQZ9jIz5ClvVfcwmId7ucfqKOvQzrdeZ0j3TZVyMuVqrM51XOejW9o72fWsb9T6n9ar6uLyuQc/LmK+4VZ3Ou9A06tDftN7FLerAbZcxMObKIvd03lTbqxvmkCPqXR8wNejl8dosAvJ9QVX9gl4WiTZntFQJYa5986qanKs+r+6LVJ3z1atsa9V5AW5zUNzvFHfgtVlUxdi+iKa2b77M5rTe1/56nUm9ypTe1x2NnNKbczLXn8jxxeR0Xk/Tqb3OtF5lUndCH7klk7kx11NMJeg5LrQ1lqBvahL2qlEfIuhg1LNxm0V1TeULKMdt2NruZefWZCum6vZLlW2XqlsubruMj5O5ttXXjSuG3m6B8U3oi6q+6FSZ0nNN6OCU3isnczXV9oun6hfusiC0ORhadQtibBP6oqrTep8TOtS/RZ1TeneMuXbU1zTUJujLJs1Sgg7VvoOYQtA9Jz0/t1lUSZsvolzbLTCdLZef/fZQ5d/7gmfuq/34VV54+t5ygX7vObpy2y5usyiHNl84ubZbYHlYdopTXxN6nZBv/v66n5NrQq+i7jVdvEb6MFpN5hHxVuAKYDdwXUrp+gqfth8n88lyQt9Z3Shvpc6kvuyFJ9d0vqnu8Ys+DpCuzITe1WQeEfuAjwEXAOcC74qIlzZ9PE1DXxN624Oiyyb0KpFrMqE32TJZVOcFYdkLTq79801NbnxRR5Mp3Ql9ps02ywHg1pTSb1NKR4GvAhfnWZbGrI+gQ/uzXHIdGB1Cjgm/jq6uvAjNzkuvG3Wvkd4u5s8FDs/9/DDwvHbL0VSsStCHPMNlzEGHfqJe1yoHvU3MdwHzG+5rgJvgK8Sgby3HVktOdQ6E9nHf0a7vZrSqQW8T8weA0+d+fhrwYLvlaGraBj3nG4u6PBd9Cueg59LXzaQNel5tYv4t4C8i4pSIeDrwZuDf8ixLUzKWd4pCt28uOvtZz64c9Rc8c1/rCX3oCX9M9xw16Ms1jnlK6RDwYeDbwB3Al1NK38u1ME3LqgQd6k3pQwc5hzb3HM35LlKDvjPfAars+jgXHaZ1+dy6BzNznmsO+c/caXLFylyX1617Lnox56F7PXMNYQpXXBzqeug7hb3uJJ/zaopNDXGLupUMujHXUKYQdJj2HYvGEPNNVaNu0Bvy2iwayklnPH8U13Tp+nouQ53pMrYzbKruq+e+56hmjLk6Z9DzG1vI5+W8vO5OmrxLtGTGXL2YQtB3UjXofUS27nMMcdmCHEF3Oq/HmKs3bbZd2txubN6Ub3LR5MViyOvP9DGht7lzUWmMuXrXZdCb3BxhXs6g54p6XxN/F5q86Whe7um85K0WY65BdHlmwdDXcpnXJsRtIz7mq0IqP2OuwTQJ+hgOiEL9UG6Geac4z/+ethGfUshzHAwVPG3oBUh17dl/2ij2SvefurfRrdm63DIZY8QPHT7S6B2jqsfJXIOa8nYLjCueY1rLPEPeD2MutTSGiI5hDU21OWVU/8+Ya3Bd7p0vk2M6H9LU9seHNvm39O/AmKtobU9VrGqIoE4h4m1fDPv6+yuBMZeWqBqkPuNaSsjbbrHk+g6tBJ7NopV3yvNOznZ63GZkm5zlUufxx26M21Mlb7GAk7kmqu9TE+vGKXd0p7Q3nutSuMu2WJzK/5STuQZX6lusF+NbZ1qfSrjn5bxJhXvl9RlziWpbLftO39PqWiNTDHQVdb9ryXEq4srdmKICt1lUvKpTXpXIjHEveCj7Tt/TScidyptxMpdq2gxY2ysCTlVXN3MGbxfXRuvJPCI+GhFXZViLNLg6WwCrNqU3mcTBkPel8WQeEXuBa4C/Bf4p24qkDvzZmc+ofG3sOqcqzset1Em96YtWzoiDZ68s02ab5SLgHuATmdYidapu0KHe5VlLDHuXkzh0G/JVmsqhRcxTSl8EcItFU1In6NAs6rB1BKcW+K7PUjHkeS2NeURcAly78Mt3p5QOdLMkqVt1gw7Noz5vuziOLfJjmcbBkNexNOYppZuAm3pYi9SbzaA0jTrku0POYjyHjPtYpnEw5HV5aqImKdfdhppGHZ4asi7i3mfYc76Dc1HXEYfVDjkYc01YztvHzcem6R3hu4h7X+e0dxXyum8AMuTNra2vr/f9nPuBe48deQTWn+j7uTVSba7P0uVFt5qGfTs5Ap8z7F1uqxjyzNZ2sXvPXoCzgIOLH3Yy1+RtRqCLqC8GqW3cc0zvObZhSog4rFDIK3Ay12jkvHpin5fIzTm9t5ncl4W96zf/gCHv1JLJ3JhrVLq8HG5fgc8R91wHU9voMuJgyGsz5pqaIa5v3nXo2wS+77CPOeKwoiEHY65pGsMNK8Z2YLWPqBvyETPmmqoxBH1RF4EfOuxdnjM+z5C3ZMw1dWOM+rycgW+6HVM37k3v9mPIB2TMVYqxR31TjrjnPr+9raEiDob8SZ5nrlIsflGPNe6LAWsS9zaXGcipzS3cvP54v4y5JmuniW1MoZ+PWt2w57jMQBNt78OZK+RO5dUZcxWpbgT6in+bd6t2HfZcN1J2Ih+GMZfYOv5dBr7NtA55LjOQK97zDPlwjLm0jb726HNcW6aLMNeVO+RusdRjzKWK5uPSRdi7vGBY15zIh2fMpQa6DHvbLZi+GfJxMOZSS5thX7Vp3YiPizGXMukj6jCOsBvy8THmUmZdRh3yvCkpx/N2yYOf9RlzqSNdHzDdtFNk64TeaXvajLnUg66n9e0Y6NWxa+gFSKvkpDOe7xbCEv75NNN4Mo+I84FrgeOBh4B3pJTGc0EMacT62oLR6mgzmX8JuCyldO7Gjz+ZZ0nSatmc1p1IncrbaBTziDgBuCKldOfGL90JnJltVdKKWuWwr+L/c06NtllSSo8BNwBExC7gKuDmfMuS5FaM6lga84i4hNne+Ly7U0oHIuJ44Asbj/PxDtYnif6v6tg3p/L2Gt82LiL2AN9gdvDz7zam9Sr2423jpE5MLfBGvIYObxt3A/Az4D0pJassjcBUbq0Hhjy3RpN5RJwH/BC4Czi28csPppT+qsKn78fJXBrM0IE34g0tmcwbb7O0sB9jLo1Cn2E34i11uM0iaeL62JYx4v0w5pKelCPuxnsYxlzStgzzdHihLUkqgDGXpAIYc0kqgDGXpAIYc0kqgDGXpAIYc0kqgDGXpAIYc0kqgDGXpAIYc0kqgDGXpAIYc0kqgDGXpAIYc0kqgDGXpAIYc0kqgDGXpAI0vm1cRFwIXAccD9wLvD2l9HCuhUmSqmszmX8eeFtK6RzgLuDyPEuSJNXV5obOL0kpHYuI3cA+4M5Ma5Ik1dR4Mt8I+TnAA8DrgBuzrUqSVMvSyTwiLgGuXfjlu1NKB1JKPwaeExHvBr4CvKaDNUqSllhbX1+v/UkRcSLwlymlmzd+fhLwPymlPRU+fT9w77Ejj8D6E7WfW5JW0toudu/ZC3AWcHDxw023WY4B10fEKzZ+/hbgtoaPJUlqqVHMU0qPA5cCn46IO4CLgctyLkySVF2jbZaW9uM2iyTV09E2iyRpRIy5JBXAmEtSAYy5JBXAmEtSAYy5JBXAmEtSAYy5JBWgzSVwmzoOgLU1fC2RpIrW1jZ/dNxWHx4i5qcD7D7p5AGeWpIm73Tgvxd/cYi3858AvAo4DDze95NL0kQdxyzk3wceW/zgEDGXJGXmprUkFcCYS1IBjLkkFcCYS1IBjLkkFcCYS1IBjLkkFWCId4B2LiLOA/4rpXTC0GvZSkRcCFwHHA/cC7w9pfTwsKvaWkScD1zLbK0PAe9IKd037Kq2FxEfBR5PKV019FrmRcRbgSuA3cB1KaXrB17StiLiZOB24I0ppYMDL2dLEXEl8JaNn96SUvrQkOvZTkR8hNkN79eBz6aUrunquYqbzCPi6cA/M4vPWH0eeFtK6RzgLuDygdezky8Bl6WUzt348ScHXs+WImJvRHwW+MDQa1kUEfuAjwEXAOcC74qIlw67qq1FxKuB24AXDb2W7UTEAeANwHnM/jxfERFvGnZVTxURrwVeD7wceCXwvoiIrp6vuJgDn2A29Y7ZS1JKd0XEbmAfMNap/ATgipTSnRu/dCdw5oBL2slFwD3M/v7H5gBwa0rptymlo8BXmU1rY/RO4L3Ag0MvZAeHgQ+klP6QUjoG/JQR/rtMKX0HeF1K6Y/Aqcx2Qo529XxFbbNExF8DT08pfbXDF8DWUkrHIuIc4FvAMeAfBl7SllJKjwE3AETELuAq4OYh17SdlNIXASLiqoGXspXnMgvQpsPAnw+0lh2llC4DGPnXz082fxwRL2S23XL+cCva3sbX+tXAB4GbgENdPdckYx4RlzDbx513N3AysyloFLZbZ0rpQErpx8BzIuLdwFeA1/S+wDk7rTUijge+wOzfy8d7X9ycndY5xHoq2sVsz3TTGvDEQGspRkS8DLgFuDyldM/Q69lOSunKiPhH4F+Zfefz6S6eZ5IxTyndxOxV7kkRcRnw98B/bk4VEXEHcGFK6X97XyTbrvPEiPiblNLmhHsDI9ga2GqtABGxB/gGs4OfF218WzuY7dY5cg8AF879/DTGvY0xehsH5r8GvD+ldOPQ69lKRLwYODGldEdK6fcR8XVm++edmGTMt5JS+gzwmc2fR8T6xkG7sTkGXB8R96eUfsDsW8TbBl7TTm4Afga8J6XkNNnMt4CrIuIUZnumbwbeNeySpisizmC23XdpSunWodezg7OBqyPiAmbfmV0EfK6rJyvxAOiopZQeBy4FPr3xncPFwGXDrmprG6d4XsRsP/KHEXFHRHxz4GVNTkrpEPBh4NvAHcCXU0rfG3ZVk/ZB4ETgmo1/k3dExHuGXtSilNI3mW0D/Qj4AXB7l99FeD1zSSqAk7kkFcCYS1IBjLkkFcCYS1IBjLkkFcCYS1IBjLkkFcCYS1IB/g9rYxtz7yRtuwAAAABJRU5ErkJggg==" alt="" />
 

与前面一样,也可以在notebook中使用choose_cubehelix_palette()来调节参数帮助选择更适合的调色板或颜色映射。如果想让函数返回一个类似hexbin的颜色映射而非一个列表则需要传入as_cmap=True。

 

定制的连续调色板

 

对于一个更简单的接口定制连续色板,你可以使用light_palette() 或者 dark_palette()函数。它们都是单一颜色,并且能产生从亮值或者暗去饱和的值到这个颜色的调色板。伴随着这些函数,也同样有 choose_light_palette 和 choose_dark_palette 两个函数来交互式的调节创建调色板。

In [28]:
sns.palplot(sns.light_palette("green"))
 
aaarticlea/png;base64,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" alt="" />
In [29]:
sns.palplot(sns.dark_palette("purple"))
 
aaarticlea/png;base64,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" alt="" />
In [31]:
sns.palplot(sns.light_palette("navy", reverse=True))
 
aaarticlea/png;base64,iVBORw0KGgoAAAANSUhEUgAAAV0AAABECAYAAAAiJuZQAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy8QZhcZAAACMklEQVR4nO3ZMWoUcQDF4ZdsUAKSKiKKB0hjmS4hbc7gCbbMcVJZegYLm6BdSi9gYEkQbFyEoLCsjSAuulXmjW6+rxmYPwtvmh/LzNZyuQwAHdtjDwC4T0QXoEh0AYpEF6BoZ83ZwySHSW6SLDpzAP57kyRPk1wm+bZ6uC66h0neDTQKYNMdJ3m/enNddG+S5OjoVWaz+VCjRvXx41lOT1+PPWMwb968zNnZ27FnDOLg4Emm0xc5P/8w9pRBTKcvcnHxaewZgzk5eZJPG/p429vJ48dJfjZ01broLpJkNpvn6urL3S/7R1xffx17wqA+f74de8Ig5vPvv1030e3tZr/VW2z24yV/eS3rQxpAkegCFIkuQJHoAhSJLkCR6AIUiS5AkegCFIkuQJHoAhSJLkCR6AIUiS5AkegCFIkuQJHoAhSJLkCR6AIUiS5AkegCFIkuQJHoAhSJLkCR6AIUiS5AkegCFIkuQJHoAhSJLkCR6AIUiS5AkegCFIkuQJHoAhSJLkCR6AIUiS5AkegCFIkuQJHoAhSJLkCR6AIUiS5AkegCFIkuQJHoAhSJLkCR6AIUiS5AkegCFIkuQNHOmrNJkjx/vleaMo5nzx6NPWFQ+/u7Y08YxN7eg9+um2h3dzL2hEFNNvTxtn/9lf3jE24tl8u//fYoybu7nwRwLxwneb96c110HyY5THKTZDHcLoCNMknyNMllkm+rh+uiC8Ad8yENoEh0AYpEF6BIdAGKfgBwGkcB9IBEewAAAABJRU5ErkJggg==" alt="" />
 

它们也可以创建一个颜色映射对象,而不仅仅是颜色列表。

In [32]:
pal = sns.dark_palette("palegreen", as_cmap=True)
sns.kdeplot(x, y, cmap=pal);
 
aaarticlea/png;base64,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" alt="" />
 

默认情况下,任何有效的matplotlib颜色可以作为输入。另外辅助的解释可以由input参数来控制。目前你可以在hls或husl空间中提供默认的rgb元组,您还可以使用任何有效的xkcd颜色的种子。

In [33]:
sns.palplot(sns.light_palette((210, 90, 60), input="husl"))
 
aaarticlea/png;base64,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" alt="" />
In [34]:
sns.palplot(sns.dark_palette("muted purple", input="xkcd"))
 
aaarticlea/png;base64,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" alt="" />
 

需要注意的是,husl是提供交互的组件的默认input空间,这与函数自身默认的并不同,但这在背景下却是更有用的。

 

离散色板

调色板中的第三类被称为“离散”。这类色板适用于数据特征含有大的低值和大的高值。数据中通常有一个意义明确的中点。例如,如果你想要从某个基线时间点绘制温度变化,最好使用离散的颜色表显示相对降低和相对增加面积的地区。 除了你想满足一个低强度颜色的中点以及用不同起始颜色的两个相对微妙的变化,其实选择离散色板的规则类似于顺序色板。同样重要的是,起始值的亮度和饱和度是相同的。 同样重要的是要强调,应该避免使用红色和绿色,因为大量的潜在观众将无法分辨它们。 同样,Color Brewer颜色字典里也同时拥有一套精心挑选的离散颜色映射:

In [35]:
sns.palplot(sns.color_palette("BrBG", 7))
 
aaarticlea/png;base64,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" alt="" />
In [36]:
sns.palplot(sns.color_palette("RdBu_r", 7))
 
aaarticlea/png;base64,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" alt="" />
In [37]:
sns.palplot(sns.color_palette("coolwarm", 7))
 
aaarticlea/png;base64,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" alt="" />
 

定制的离散色板

 

你也可以使用seaborn函数 diverging_palette() 为离散的数据创建一个定制的颜色映射。(当然也有一个类似配套的互动工具:choose_diverging_palette())。该函数使用husl颜色系统的离散色板。你需要传递两种色调,并可选择性的设定明度和饱和度的端点。函数将使用husl的端点值及由此产生的中间值进行均衡。

In [38]:
sns.palplot(sns.diverging_palette(220, 20, n=7))
 
aaarticlea/png;base64,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" alt="" />
In [39]:
sns.palplot(sns.diverging_palette(145, 280, s=85, l=25, n=7))
 
aaarticlea/png;base64,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" alt="" />
 

sep参数控制面板中间区域的两个渐变的宽度。

In [40]:
sns.palplot(sns.diverging_palette(10, 220, sep=80, n=7))
 
aaarticlea/png;base64,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" alt="" />
 

也可以用中间的色调来选择调色,而不是用亮度。

In [41]:
sns.palplot(sns.diverging_palette(255, 133, l=60, n=7, center="dark"))
 
aaarticlea/png;base64,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" alt="" />
 

设置默认的调色板

 

color_palette() 函数有一个名为set_palette()的配套使用函数。 set_palette()。set_palette()接受与color_palette()相同的参数,但是它会更改默认的matplotlib参数,以便成为所有的调色板配置。

In [47]:
def sinplot(flip=1):
x = np.linspace(0, 14, 100)
for i in range(1, 7):
plt.plot(x, np.sin(x + i * .5) * (7 - i) * flip)
sns.set_palette("husl")
sinplot()
 
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" alt="" />
 

color_palette()函数也可以在一个with块中使用,以达到临时更改调色板的目的。

In [43]:
with sns.color_palette("PuBuGn_d"):
sinplot()
 
aaarticlea/png;base64,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" alt="" />
In [48]:
with sns.color_palette("deep"):
sinplot()
 
aaarticlea/png;base64,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" 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