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红橙黄绿青蓝紫

color = ['red', 'orange', 'yellow', 'green', 'cyan', 'blue', 'purple'] # 红橙黄绿青蓝紫
color = {'red': '#FF0000', 'orange': '#FFA500', 'yellow': '#FFFF00', 'green': '#008000', 'cyan': '#00FFFF', 'blue': '#0000FF', 'purple': '#800080'} # 红橙黄绿青蓝紫

PS:此处紫色为purpleviolet也为紫色不过偏粉

import matplotlib.colors as colors
for name, hsv in colors.cnames.items():
    print(name, hsv)
import matplotlib.pyplot as plt
import matplotlib.colors as mcolors
colors = dict(mcolors.BASE_COLORS, **mcolors.CSS4_COLORS)
by_hsv = sorted((tuple(mcolors.rgb_to_hsv(mcolors.to_rgba(color)[:3])), name)
                for name, color in colors.items())  # 根据色调、饱和度、值和名称对颜色进行排序
sorted_names = [name for hsv, name in by_hsv]
n = len(sorted_names)
ncols = 4
nrows = n // ncols
fig, ax = plt.subplots(figsize=(12, 10))
X, Y = fig.get_dpi() * fig.get_size_inches()
h = Y / (nrows + 1)  # 高
w = X / ncols  # 宽
for i, name in enumerate(sorted_names):
    row = i % nrows
    col = i // nrows
    y = Y - (row * h) - h
    xi_line = w * (col + 0.05)
    xf_line = w * (col + 0.25)
    xi_text = w * (col + 0.3)
    ax.text(xi_text, y, name, fontsize=(h * 0.8), horizontalalignment='left', verticalalignment='center')
    ax.hlines(y + h * 0.1, xi_line, xf_line, color=colors[name], linewidth=(h * 0.8))
ax.set_xlim(0, X)
ax.set_ylim(0, Y)
ax.set_axis_off()
fig.subplots_adjust(left=0, right=1, top=1, bottom=0, hspace=0, wspace=0)
plt.show()
aliceblue #F0F8FF
antiquewhite #FAEBD7
aqua #00FFFF
aquamarine #7FFFD4
azure #F0FFFF
beige #F5F5DC
bisque #FFE4C4
black #000000
blanchedalmond #FFEBCD
blue #0000FF
blueviolet #8A2BE2
brown #A52A2A
burlywood #DEB887
cadetblue #5F9EA0
chartreuse #7FFF00
chocolate #D2691E
coral #FF7F50
cornflowerblue #6495ED
cornsilk #FFF8DC
crimson #DC143C
cyan #00FFFF
darkblue #00008B
darkcyan #008B8B
darkgoldenrod #B8860B
darkgray #A9A9A9
darkgreen #006400
darkgrey #A9A9A9
darkkhaki #BDB76B
darkmagenta #8B008B
darkolivegreen #556B2F
darkorange #FF8C00
darkorchid #9932CC
darkred #8B0000
darksalmon #E9967A
darkseagreen #8FBC8F
darkslateblue #483D8B
darkslategray #2F4F4F
darkslategrey #2F4F4F
darkturquoise #00CED1
darkviolet #9400D3
deeppink #FF1493
deepskyblue #00BFFF
dimgray #696969
dimgrey #696969
dodgerblue #1E90FF
firebrick #B22222
floralwhite #FFFAF0
forestgreen #228B22
fuchsia #FF00FF
gainsboro #DCDCDC
ghostwhite #F8F8FF
gold #FFD700
goldenrod #DAA520
gray #808080
green #008000
greenyellow #ADFF2F
grey #808080
honeydew #F0FFF0
hotpink #FF69B4
indianred #CD5C5C
indigo #4B0082
ivory #FFFFF0
khaki #F0E68C
lavender #E6E6FA
lavenderblush #FFF0F5
lawngreen #7CFC00
lemonchiffon #FFFACD
lightblue #ADD8E6
lightcoral #F08080
lightcyan #E0FFFF
lightgoldenrodyellow #FAFAD2
lightgray #D3D3D3
lightgreen #90EE90
lightgrey #D3D3D3
lightpink #FFB6C1
lightsalmon #FFA07A
lightseagreen #20B2AA
lightskyblue #87CEFA
lightslategray #778899
lightslategrey #778899
lightsteelblue #B0C4DE
lightyellow #FFFFE0
lime #00FF00
limegreen #32CD32
linen #FAF0E6
magenta #FF00FF
maroon #800000
mediumaquamarine #66CDAA
mediumblue #0000CD
mediumorchid #BA55D3
mediumpurple #9370DB
mediumseagreen #3CB371
mediumslateblue #7B68EE
mediumspringgreen #00FA9A
mediumturquoise #48D1CC
mediumvioletred #C71585
midnightblue #191970
mintcream #F5FFFA
mistyrose #FFE4E1
moccasin #FFE4B5
navajowhite #FFDEAD
navy #000080
oldlace #FDF5E6
olive #808000
olivedrab #6B8E23
orange #FFA500
orangered #FF4500
orchid #DA70D6
palegoldenrod #EEE8AA
palegreen #98FB98
paleturquoise #AFEEEE
palevioletred #DB7093
papayawhip #FFEFD5
peachpuff #FFDAB9
peru #CD853F
pink #FFC0CB
plum #DDA0DD
powderblue #B0E0E6
purple #800080
rebeccapurple #663399
red #FF0000
rosybrown #BC8F8F
royalblue #4169E1
saddlebrown #8B4513
salmon #FA8072
sandybrown #F4A460
seagreen #2E8B57
seashell #FFF5EE
sienna #A0522D
silver #C0C0C0
skyblue #87CEEB
slateblue #6A5ACD
slategray #708090
slategrey #708090
snow #FFFAFA
springgreen #00FF7F
steelblue #4682B4
tan #D2B48C
teal #008080
thistle #D8BFD8
tomato #FF6347
turquoise #40E0D0
violet #EE82EE
wheat #F5DEB3
white #FFFFFF
whitesmoke #F5F5F5
yellow #FFFF00
yellowgreen #9ACD32
  1. Named colors in matplotlib
'aliceblue': '#F0F8FF', 'antiquewhite': '#FAEBD7', 'aqua': '#00FFFF', 'aquamarine': '#7FFFD4', 'azure': '#F0FFFF', 'beige': ...
要想把数据表示得生动的趣,往往需要使用多种颜色来配合,才可以让数据得已区分开来。那么就来学习一下matplotlib颜色。在matplotlib里主要使用一些简单的字母来表示颜色,比如: ‘k’表示黑色; ‘b’表示蓝色 ‘c’表示青色 ‘g’表示绿色 ‘m’表示洋红 ‘r’表示红色 ‘y’黄色 ‘gray’或’grey’代表灰色 ‘lightgray’或’lightgrey’代表浅灰 这些颜色都是常用的颜色,如果你想定义一些特别的颜色,上面这些颜色也许不会满足你的需求,那么怎么.
# 使用 bar 函数画出条形图 plt.bar(index_1, height=x1, width=bar_width, color='lightgrey', label='ALBERT-Uy') plt.bar(index_2, height=x2, width=bar_width, color='darkgrey', label='XLM-Uy') plt.bar(index_3, height=x3, width=bar_width, color='dimgrey', label='XLM-R...
Matplotlib是一种用于创建数据可视化图的Python库。淡紫色在Matplotlib中通常可以使用不同的颜色代码来表示,例如"#E8B2E9"或"#F7EED5"。你可以在Matplotlib的色轮中选择一个淡紫色,或者使用颜色代码来创建一个新的颜色。一旦你选择了颜色,你就可以在图表中使用它来绘制各种形状,线条,文本等。 例如,你可以使用以下代码创建一个简单的散点图,并使用淡紫色来绘制点: ```python import matplotlib.pyplot as plt x = [1, 2, 3, 4, 5] y = [2, 4, 6, 8, 10] plt.scatter(x, y, color='淡紫色') # 这里我们使用字符串'淡紫色'来表示颜色 plt.show() 请注意,不同的Matplotlib版本和操作系统可能对颜色的解释有所不同,因此最好查看Matplotlib的文档以获取准确的颜色代码。