python中matplotlib的颜色以及形状实例详解_Python

绘制折线图

命令形如：

# 常用
plt.plot(x, y, linewidth = "1", label = "test", color=" red ", linestyle=":", marker="|")

# 所有可选参数
plt.plot(x,y,color,linestyle=,linewidth,marker,markeredgecolor,markeredgwidth,markerfacecolor,markersize,label)

plt.legend(loc="upper left")
plt.show()

主要参数详解：

线条形式（linestyle）：

标记字符	还可使用	说明
‘-’	“solid”	实线
‘–’	“dashed”	破折线
‘-.’	“dashdot”	点划线
‘:’	“dotted”	虚线
’ ’	‘none’	无线条

标注形状（marker）：

标记字符	还可使用	说明
‘.’	point marker	点标记
‘,’	pixel marker	像素标记（极小点）
‘o’	circle marker	实心圈标记
‘v’	triangle_down marker	倒三角标记
‘^’	triangle_up marker	上三角标记
‘<’	triangle_left marker	左三角标记
‘>’	triangle_right marker	右三角标记
‘1’	tri_down marker	下花三角标记
‘2’	tri_up marker	上花三角标记
‘3’	tri_left marker	左花三角标记
‘4’	tri_right marker	右花三角标记
‘s’	square marker	实心方形标记
‘p’	pentagon marker	实心五角标记
‘*’	star marker	星形标记
‘h’	hexagon1 marker	竖六边形标记
‘H’	hexagon2 marker	横六边形标记
‘+’	plus marker	十字标记
‘x’	x marker	x标记
‘D’	diamond marker	菱形标记
‘d’	thin_diamond marker	受菱形标记
‘\|’	vline marker	垂直线标记
‘_’	hline marker	水平线标记

颜色（color），可用十六进制形式，每两个十六进制数分别代表R、G、B分量，可用如下代码展示所有：

import matplotlib
for name, hex in matplotlib.colors.cnames.items():
    print(name, hex)

得所有支持颜色：

 cnames = {
    "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",
    "darkkhaki":            "#BDB76B",
    "darkmagenta":          "#8B008B",
    "darkolivegreen":       "#556B2F",
    "darkorange":           "#FF8C00",
    "darkorchid":           "#9932CC",
    "darkred":              "#8B0000",
    "darksalmon":           "#E9967A",
    "darkseagreen":         "#8FBC8F",
    "darkslateblue":        "#483D8B",
    "darkslategray":        "#2F4F4F",
    "darkturquoise":        "#00CED1",
    "darkviolet":           "#9400D3",
    "deeppink":             "#FF1493",
    "deepskyblue":          "#00BFFF",
    "dimgray":              "#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",
    "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",
    "lightgreen":           "#90EE90",
    "lightgray":            "#D3D3D3",
    "lightpink":            "#FFB6C1",
    "lightsalmon":          "#FFA07A",
    "lightseagreen":        "#20B2AA",
    "lightskyblue":         "#87CEFA",
    "lightslategray":       "#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",
    "red":                  "#FF0000",
    "rosybrown":            "#BC8F8F",
    "royalblue":            "#4169E1",
    "saddlebrown":          "#8B4513",
    "salmon":               "#FA8072",
    "sandybrown":           "#FAA460",
    "seagreen":             "#2E8B57",
    "seashell":             "#FFF5EE",
    "sienna":               "#A0522D",
    "silver":               "#C0C0C0",
    "skyblue":              "#87CEEB",
    "slateblue":            "#6A5ACD",
    "slategray":            "#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"}

可用如下代码展示具体颜色：

import matplotlib.pyplot as plt
import matplotlib.patches as patches
import matplotlib.colors as colors
import math

fig = plt.figure()
ax = fig.add_subplot(111)

ratio = 1.0 / 3.0
count = math.ceil(math.sqrt(len(colors.cnames)))
x_count = count * ratio
y_count = count / ratio
x = 0
y = 0
w = 1 / x_count
h = 1 / y_count

for c in colors.cnames:
    pos = (x / x_count, y / y_count)
    ax.add_patch(patches.Rectangle(pos, w, h, color=c))
    ax.annotate(c, xy=pos)
    if y >= y_count-1:
        x += 1
        y = 0
    else:
        y += 1

plt.show()

得下图

python中matplotlib的颜色以及形状实例详解

绘制柱形图

plot.bar(x,height,width=0.8,bottom=None,align="center",color,edgecolor)

参数	说明
x	表示在什么位置显示柱形图
height	柱子高度
width	每根柱子的宽度，可各不相同
bottom	每根柱子的底部位置，可各不相同
align	柱子的位置与x值的关系，可选center、edge两个参数，center表示柱子位于x值的中心位置，edge表示边缘位置
color	柱子颜色
edgecolor	柱子边缘的颜色

例：

plt.subplot(1,1,1)

x = np.array(["东区","西区","南区","北区"])
y = np.array([8566,6482,5335,7310])

plt.bar(x,y,width=0.5,align="center",label="任务量")

plt.title("全国各分区任务量",loc="center")

# 添加数据标签
for a,b in zip(x,y):
    plt.text(a,b,b,ha="center",va="bottom",fontsize=12,color="r")
    
plt.xlabel("分区")
plt.ylabel("任务量")

plt.legend()     #显示图例

#保存到本地
#plt.savefig("C:/Users/.../1.jpg")

python中matplotlib的颜色以及形状实例详解

簇状柱形图

plt.subplot(1,1,1)

x = np.array([1,2,3,4])
y1 = np.array([8566,6482,5335,7310])
y2 = np.array([4283,2667,3655,3241])

plt.bar(x,y1,width=0.3,label="任务量")
plt.bar(x+0.3,y2,width=0.3,label="完成量")   #x+0.3相当于完成量的每个柱子右移0.3

plt.title("全国各分区任务量",loc="center")

# 添加数据标签
for a,b in zip(x,y1):
    plt.text(a,b,b,ha="center",va="bottom",fontsize=12,color="blue")
    
    
for a,b in zip(x,y2):
    plt.text(a,b,b,ha="center",va="bottom",fontsize=12,color="g")
    
plt.xlabel("区域")
plt.ylabel("任务情况")

#设置x轴刻度值
plt.xticks(x+0.15,["东区","西区","南区","北区"])

plt.grid(False)
plt.legend()     #显示图例

python中matplotlib的颜色以及形状实例详解

堆积柱形图

plt.subplot(1,1,1)

x = np.array(["东区","西区","南区","北区"])
y1 = np.array([8566,6482,5335,7310])
y2 = np.array([4283,2667,3655,3241])

plt.bar(x,y1,width=0.3,label="任务量")
plt.bar(x,y2,width=0.3,label="完成量")   

plt.title("全国各分区任务量",loc="center")

# 添加数据标签
for a,b in zip(x,y1):
    plt.text(a,b,b,ha="center",va="bottom",fontsize=12,color="blue")
    
    
for a,b in zip(x,y2):
    plt.text(a,b,b,ha="center",va="bottom",fontsize=12,color="g")
    
plt.xlabel("区域")
plt.ylabel("任务情况")


plt.grid(False)

plt.legend(loc = "upper center",ncol=2)

python中matplotlib的颜色以及形状实例详解

散点图

plt.scatter(x,y,s,c,marker,linewidths,edgecolors)

参数	说明
（x，y）	散点的位置
s	每个点的面积，即散点的大小。若只有一个具体值时，则所有点的大小都一样。也可呈现多个值，这样就成了气泡图
c	每个点的颜色，可多样
marker	标记，同折线图中marker
linewidths	散点线宽
edgecolors	散点外轮廓的颜色

colors = y*10
area = y*100        #根据y值的大小生成不同形状

plt.scatter(x,y,c=colors,marker="o",s=area)

plt.title("销量关系图",loc="center")

# 添加数据标签
for a,b in zip(x,y):
    plt.text(a,b,b,ha="center",va="center",fontsize=10,color="white")
    
plt.xlabel("气温")
plt.ylabel("啤酒销量")

plt.grid(False)

python中matplotlib的颜色以及形状实例详解

附：matplotlib实现区域颜色填充

"""
学习python
"""
import matplotlib.pyplot as plt
import numpy as np
  
x= np.linspace(0,5*np.pi, 1000)
  
y1 = np.sin(x)
y2 = np.sin(2*x)
  
#plt.plot(x,y1)
#plt.plot(x,y2)
  
plt.fill(x,y1,"b",alpha=0.5)
plt.fill(x,y2,"r",alpha=0.3)
  
plt.fill_between(x,y1,y2,facecolor="green")
plt.grid(True)
  
plt.show()
  
#########################################################
plt.plot(x,y1,"b",alpha=0.5)
plt.plot(x,y2,"r",alpha=0.3)
#添加条件
#如果数据点比较少的情况下，会有缝隙出现，使用interpolate可以填充缝隙
plt.fill_between(x,y1,y2,where=y1>=y2,facecolor="green",interpolate=True)
plt.fill_between(x,y1,y2,where=y2>y1,facecolor="yellow",interpolate=True)
plt.grid(True)
  
plt.show()
###########################################################
  
n = 256
X = np.linspace(-np.pi, np.pi, n, endpoint=True)
Y = np.sin(2 * X)
  
  
plt.plot(X, Y + 1, color="blue", alpha=1.00)
plt.fill_between(X, 1, Y + 1, color="blue", alpha=.25)
  
plt.plot(X, Y - 1, color="blue", alpha=1.00)
plt.fill_between(X, -1, Y - 1, (Y - 1) > -1, color="blue", alpha=.25)
plt.fill_between(X, -1, Y - 1, (Y - 1) < -1, color="red", alpha=.25)
  
plt.xlim(-np.pi, np.pi)
plt.xticks(())
plt.ylim(-2.5, 2.5)
plt.yticks(())