The 'hands-on” in the palette world-palettable

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• Some friends say that python visualization’s built-in colors are ugly, then you must not have encountered palettable , palettable is a colorbar (Colormap) library written in pure python, which brings together a large number of colorbars from well-known visualization software (such as Tableau color system, matplotlib partial color system, etc.). There are a total of 1587 colorbar (Colormap) categories that can be used. There are tens of thousands of single colors. This article details how to use palettable.
  
  
  

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Contents of this article

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1. Quick installation of palettable

pip install palettable -i https://pypi.tuna.tsinghua.edu.cn/simple

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2. Quick use of palettable color bar (Colormap)

Import palettable package

import palettable
from palettable.cartocolors.qualitative import Bold_9

#为了描述方便，此处直接倒入palettable.cartocolors.qualitative大类下的Bold_9小类，
#实际使用时可直接用palettable.cartocolors.qualitative.Bold_9

palettable important properties-visualized chroma bar

Bold_9.show_discrete_image()#Bold_9各种颜色条图片

palettable important attribute-the number of single colors in the output chroma bar

print(Bold_9.number)#Bold_9这种colormap中单颜色的数目

9That is, the above picture has 9 cells

palettable important attributes-output the color number value of a single color in the chroma bar

print(Bold_9.colors)#Bold_9 colormap中每种颜色的RGB格式色号

print(Bold_9.hex_colors)#Bold_9 colormap中每种颜色的hex格式色号
print(Bold_9.mpl_colors)#RGB tuples in the range 0-1 as used by matplotlib

[[127, 60, 141], [17, 165, 121], [57 , 105, 172], [242, 183, 1], [231, 63, 116], [128, 186, 90], [230, 131, 16], [0, 134, 149], [207, 28 , 144]]

['#7F3C8D', '#11A579', '#3969AC', '#F2B701', '#E73F74', '#80BA5A', '#E68310', '#008695' . 0.003 92156862745098), (0.9058823529411765, 0.24705882352941178, 0.4549019607843137), (0.5019607843137255, 0.7294117647058823, 0.35294117647058826), (0.9019607843137255, 0.5137254901960784, 0.06274509803921569), (0.0, 0.5254901960784314, 0.5843137254901961), (0.8117647058823529, 0.10980392156862745, 0.56470588235294 12)]

Matplotlib中使用palettable

例子来自matplotlib-饼图（pie）

import matplotlib.pyplot as plt
import matplotlib as mpl
import palettable

mpl.rc_file_defaults()
my_dpi = 96
plt.figure(figsize=(580 / my_dpi, 580 / my_dpi), dpi=my_dpi)
plt.subplot(221)
patches, texts, autotexts = plt.pie(
    x=[1, 2, 3],
    labels=['A', 'B', 'C'],
    #使用palettable.tableau.BlueRed_6
    colors=palettable.tableau.BlueRed_6.mpl_colors[0:3],
    autopct='%.2f%%',
    explode=(0.1, 0, 0))

patches[0].set_alpha(0.3)
patches[2].set_hatch('|')
patches[1].set_hatch('x')
plt.title('tableau.BlueRed_6', size=12)

mpl.rc_file_defaults()
plt.subplot(222)

patches, texts, autotexts = plt.pie(
    x=[1, 2, 3],
    labels=['A', 'B', 'C'],
    #使用palettable.cartocolors.qualitative.Bold_9
    colors=palettable.cartocolors.qualitative.Bold_9.mpl_colors[0:3],
    autopct='%.2f%%',
    explode=(0.1, 0, 0))

patches[0].set_alpha(0.3)
patches[2].set_hatch('|')
patches[1].set_hatch('x')
plt.title('cartocolors.qualitative.Bold_9', size=12)

mpl.rc_file_defaults()
plt.subplot(223)

patches, texts, autotexts = plt.pie(
    x=[1, 2, 3],
    labels=['A', 'B', 'C'],
    #使用palettable.cartocolors.qualitative.Bold_9
    colors=palettable.cartocolors.qualitative.Bold_9.mpl_colors[0:3],
    autopct='%.2f%%',
    explode=(0.1, 0, 0))

patches[0].set_alpha(0.3)
patches[2].set_hatch('|')
patches[1].set_hatch('x')
plt.title('cartocolors.qualitative.Bold_9', size=12)

plt.subplot(223)

patches, texts, autotexts = plt.pie(
    x=[1, 2, 3],
    labels=['A', 'B', 'C'],
    #使用palettable.lightbartlein.sequential.Blues10_5
    colors=palettable.lightbartlein.sequential.Blues10_5.mpl_colors[0:3],
    autopct='%.2f%%',
    explode=(0.1, 0, 0))

#matplotlib.patches.Wedge
patches[0].set_alpha(0.3)
patches[2].set_hatch('|')
patches[1].set_hatch('x')
plt.title('lightbartlein.sequential.Blues10_5', size=12)

plt.subplot(224)

patches, texts, autotexts = plt.pie(
    x=[1, 2, 3],
    labels=['A', 'B', 'C'],
    colors=palettable.wesanderson.Moonrise5_6.mpl_colors[0:3],
    autopct='%.2f%%',
    explode=(0.1, 0, 0))

patches[0].set_alpha(0.3)
patches[2].set_hatch('|')
patches[1].set_hatch('x')
plt.title('wesanderson.Moonrise5_6', size=12)
plt.show()

Seaborn中使用palettable

例子来自几行代码绘制靓丽矩阵图
使用palettable.tableau.TrafficLight_9

import seaborn as sns
iris_sns = sns.load_dataset("iris")

import palettable

g = sns.pairplot(
    iris_sns,
    hue='species',
    palette=palettable.tableau.TrafficLight_9.mpl_colors,  #Matplotlib颜色
)
sns.set(style='whitegrid')
g.fig.set_size_inches(10, 8)
sns.set(style='whitegrid', font_scale=1.5)

使用palettable.tableau.BlueRed_6
使用palettable.cartocolors.qualitative.Bold_9使用palettable.wesanderson.Moonrise5_6使用palettable.cartocolors.diverging.ArmyRose_7_r

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3、palettable包含那些颜色条(Colormap)

palettable下面有16大类Colormap，共计1587小类Colormap，合计上万种单颜色可供使用，已经整理为pdf格式，感兴趣的可以
包含以下16大类

palettable.cartocolors.diverging
palettable.cartocolors.qualitative
palettable.cartocolors.sequential
palettable.cmocean.diverging
palettable.cmocean.sequential
palettable.colorbrewer.diverging
palettable.colorbrewer.qualitative
palettable.colorbrewer.sequential
palettable.lightbartlein.diverging
palettable.lightbartlein.sequential
palettable.scientific.diverging
palettable.scientific.sequential
palettable.matplotlib
palettable.mycarta
palettable.tableau
palettable.wesanderson

共计1587小类【每个小类还有逆类，名称后面加“_r”即可】上面16大类下面有数个小类，例如，著名BI软件Tableau的配色条palettable.tableau这一大类，下面有palettable.tableau.BlueRed_12，palettable.tableau.GreenOrange_12等等数个小类：

palettable.tableau.BlueRed_12
palettable.tableau.BlueRed_6
palettable.tableau.ColorBlind_10
palettable.tableau.Gray_5
palettable.tableau.GreenOrange_12
palettable.tableau.GreenOrange_6
palettable.tableau.PurpleGray_12
palettable.tableau.PurpleGray_6
palettable.tableau.TableauLight_10
palettable.tableau.TableauMedium_10
palettable.tableau.Tableau_10
palettable.tableau.Tableau_20
palettable.tableau.TrafficLight_9

也就是类似上面的这种有1587行。

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