[学习笔记]matplotlib.pyplot

本文记录matpltlib库中主要的绘图命令，列出各类型绘图的简单案例。

1.各类型绘图命令

1.1 绘图类型总览及查看方法

图形	函数
曲线图	.plot(data)
灰度图	.hist(data)
散点图	.scatter(data)
箱式图	.boxplot(data)
直方图	.bar(data)
饼状图	.pie(data)
热图	.imshow(data)
等高线图	.contourf(data)
雷达图	p.olar(data)

查看函数可用参数的方法

import matplotlib.pyplot as plt
help(plt.plot)

1.2 汇总案例

import numpy as np
import matplotlib.pyplot as plt
#申请一块画布
fig=plt.figure(figsize=(20,15))
#画三张图
ax1=fig.add_subplot(4,3,1)
ax2=fig.add_subplot(4,3,2)
ax3=fig.add_subplot(4,3,3)
ax4=fig.add_subplot(4,3,4)
ax5=fig.add_subplot(4,3,5)
ax6=fig.add_subplot(4,3,6)
ax7=fig.add_subplot(4,3,7)
ax8=fig.add_subplot(4,3,8)
ax9=fig.add_subplot(4,3,9)
ax10=fig.add_subplot(4,3,10)
ax11=fig.add_subplot(4,3,11,projection='polar')
ax12=fig.add_subplot(4,3,12)
#折线图
ax1.plot(np.random.randn(10))
#曲线图
x2=np.arange(-10,10,0.1)
y2=x2**2
ax2.plot(x2,y2)
#灰度图
ax3.hist(np.random.normal(size=1000),bins=100,alpha=0.3)
#散点图
ax4.scatter(np.random.normal(size=1000),2*np.random.normal(size=1000)) 
#直方图
ax5.bar(np.arange(10),np.random.randn(10))
#直方图
ax6.barh(np.arange(10),np.random.randn(10))
#饼状图
ax7.pie(np.random.randint(1,15,5),explode=[0.05,0.25,0.20,0.30,0.20])
#热图
import pandas as pd
from pandas import Series,DataFrame
df=DataFrame(np.random.randn(10,10))
ax8.imshow(df.values,interpolation='nearest')
#多图种混合
x9=np.arange(10)
y9=np.random.randn(10)
ax9.plot(x9,y9,color='red')
ax9.bar(x9,y9,color='green')
#等高线图
x10=np.linspace(-3,3,256)
y10=np.linspace(-3,3,256)
x10,y10=np.meshgrid(x10,y10)
z10=(1-x10/2+x10**5+y10**3)*np.exp(-x10**2-y10**2)
ax10.contourf(x10,y10,z10,8,alpha=.75,cmap=plt.cm.cool)
#雷达图
attribute=['Attack','Defence','Stamina','Agility','Magicka']
theta=np.linspace(0,2*np.pi,len(attribute),endpoint=False)
value=np.random.randint(50,100,size=5)
theta = np.concatenate((theta,[theta[0]]))
value = np.concatenate((value,[value[0]]))
#ax11=polar(theta,value,lw=2)
#箱体图
x12=np.random.randn(10,10)
ax12=plt.boxplot(x12)
#3D曲面图
from mpl_toolkits.mplot3d import Axes3D
x21=np.arange(-2,2,0.1)
y21=np.arange(-2,2,0.1)
x21,y21=np.meshgrid(x21,y21)
bx1=plt.figure()
pk1=Axes3D(bx1)
pk1.plot_surface(x21,y21,(1-y21**5+x21**5)*np.exp(-x21**2-y21**2), rstride=1, cstride=1, color='red', alpha=.4)
#3D散点图
x22=np.random.randint(30,40,100)
y22=np.random.randint(20,25,100)
z22=np.random.randint(0,5,100)
x23=np.random.randint(55,60,100)
y23=np.random.randint(10,20,100)
z23=np.random.randint(35,40,100)
bx2=plt.figure()
pk2=Axes3D(bx2)
pk2.scatter(x22,y22,z22,c='r',marker='^',zdir='z')
pk2.scatter(x23,y23,z23,c='g',marker='*',zdir='z')

输出结果：

1.3 一般绘图(折线图/函数图形等) - plot()

·函数格式
plt.plot(x,y,format_string,**kwargs)
x,y - 分别为自变量和因变量
Format_string – 绘图格式，如点型，线型，颜色(参数见附录1)
**kwargs – 绘制多条曲线；设置 label / linewidth等参数

·属性设置

用样式	函数
标题	pyplot.title()
坐标轴标签	pyplot.xlabel()
图注	pyplot.legend()
网格	pyplot.grid()
字符	.rcParams()
绘图区域	pyplot.subplot2grid()

基本功能-多条曲线绘制

import matplotlib.pyplot as plt
import numpy as np
#设置变量和自变量
x=np.arange(-5,5,0.2)
y1=x**2/20
y2=np.exp(-1-x**2)
y3=np.cos(x/np.pi)
y4=np.sin(x/np.pi)
#绘制曲线
plt.figure()
plt.subplot2grid((2,2),(0,0),colspan=2)
plt.plot(x,y1,color='green', marker='*', linestyle='--', linewidth=1, markersize=6,label='y1')
plt.plot(x,y2,color='blue',marker='+',linestyle='-',label='y2')
plt.plot(x,y3,'ro',linestyle=':',label='y3')
#设置pyplot属性
plt.ylabel('Y value')
plt.title('Example of plot')
plt.legend(loc='best') 
#另设两个小区域
plt.subplot2grid((2,2),(1,0))
x2=(3,5,7,9)
y5=(6,11,8,7)
plt.plot(x2,y5)
plt.subplot2grid((2,2),(1,1))
plt.plot(x,y3,'ro',linestyle=':',label='y3')
plt.show()

输出结果：

1.4 灰度图 - hist()

hist(x, bins=None, range=None, density=None, weights=None, cumulative=False, bottom=None, histtype='bar', align='mid', orientation='vertical', rwidth=None, log=False, color=None, label=None, stacked=False, normed=None, *, data=None, **kwargs)

常用参数：
x：输入值，需要为一个序列。唯一必选参数
bins：区间数量，可以指定为整数或者列出全部区间。
range：配合bins，只在range制定范围内划分bins区间
desity：默认输出为频数直方图，将density设为True后变为频率直方图
stack:是否允许堆叠。stack=True 则允许数据堆叠

基本功能-频数直方图/频率直方图

import matplotlib.pyplot as plt
import numpy as np
plt.figure()
plt.subplot2grid((2,2),(0,0))
data=np.random.normal(size=1000)
plt.hist(data)
#分为30个区间
plt.subplot2grid((2,2),(0,1))
plt.hist(data,30)
#仅在（-2，2）区分30个区间
plt.subplot2grid((2,2),(1,0))
plt.hist(data,30,(-2,2))
#改为频率直方图
plt.subplot2grid((2,2),(1,1))
plt.hist(data,30,(-2,2),density=True)
plt.show()
```python

输出结果：

进阶功能-多组数据放到一个直方图里，并列/重叠/堆叠排布

import matplotlib.pyplot as plt
import numpy as np
plt.figure(figsize=(15,10))
#多组数据放到一个直方图里，并列排布
plt.subplot2grid((2,2),(0,0))
data1=np.random.randint(0,5000,5000)
data2=500*np.random.normal(0,1,3000) +2250
data3=1000*np.random.normal(0,1,3000) +2250
labels = ['randint','normal-1','normal-2']
bins = [0, 500,1000, 1500,2000,2500,3000,3500,4000,4500,5000]
plt.hist([data1,data2,data3],bins=bins,label=labels,color=['r','g','b'])
plt.legend()
#多组数据放到一个直方图里，重叠排布
plt.subplot2grid((2,2),(0,1))
data4=500*np.random.normal(0,1,8000) +2250
plt.hist(data2,color='r',alpha=1,label='nomal-1')
plt.hist(data4,color='g',alpha=0.2,label='nomal-3')
plt.legend()
#多组数据放到一个直方图里，堆叠排布
plt.subplot2grid((2,2),(1,0))
data5=np.random.randn(10000)
data6=np.random.randn(10000) +2.5
data7=np.random.randn(10000) -1
plt.hist([data5,data6,data7],bins=100,stacked=True,density=True,label=['randn-1','randn-2','randn-3'])
plt.legend()

输出结果：

1.5 散点图 - scatter()

scatter(x, y, s=None, c=None, marker=None, cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, verts=None, edgecolors=None, *, plotnonfinite=False, data=None, **kwargs)

常用参数：
x,y：输入值，需要为一个序列。必选参数
s,c,marker：大小，颜色，点的标识
alpha:透明度
linewidth,edgecolors：边的宽度及颜色
cmap：点颜色渐变

基本功能 - 散点格式调整：

import matplotlib.pyplot as plt
import numpy as np
x=np.arange(10,20,2)
y=x**(0.5)+20/x
plt.figure()
#基本图形
plt.subplot2grid((2,2),(0,0))
plt.scatter(x,y)
#增加颜色等
plt.subplot2grid((2,2),(0,1))
plt.scatter(x,y,s=1000,c="r",marker="d")
#增加边
plt.subplot2grid((2,2),(1,0))
plt.scatter(x,y,s=1000,c="r",marker="d",linewidth=3,edgecolors="b")
#渐变
plt.subplot2grid((2,2),(1,1))
plt.scatter(x,y,c=y,cmap=plt.cm.Reds)
plt.show()

输出结果：

1.6 箱线图 - boxplot()

箱线图主要用于反应数据内部整体的分布状态。各定义见下图。

boxplot(x, notch=None, sym=None, vert=None, whis=None, positions=None, widths=None, patch_artist=None, bootstrap=None, usermedians=None, conf_intervals=None, meanline=None, showmeans=None, showcaps=None, showbox=None, showfliers=None, boxprops=None, labels=None, flierprops=None, medianprops=None, meanprops=None, capprops=None, whiskerprops=None, manage_ticks=True, autorange=False, zorder=None, *, data=None)

常用参数：
X：输入值。唯一必选参数。
Notch:是否是凹口形式
patch_artist：箱线颜色是否填充
medianprops：中位数线的属性
boxprops：箱体的属性
meanprops:均值的属性
whiskerprops:猫须属性
capprops:箱线图顶末端线条属性
sym:异常点形状

基本功能 -箱式图绘制

import matplotlib.pyplot as plt
import numpy as np
data1=np.random.normal(0,1,10) 
data2=np.random.normal(0,1,100) 
data3=np.random.normal(0,1,1000) 
plt.boxplot([data1, data2,data3], labels = ['10 sample','100 sample','1000 sample'])

输出结果：

进阶设置 - 均值/水平图/箱体形状/异常点形状

import matplotlib.pyplot as plt
import numpy as np
data1=np.random.normal(0,1,10) 
data2=np.random.normal(0,1,100) 
data3=np.random.normal(0,1,1000) 
plt.boxplot([data1, data2,data3], labels = ['10 sample','100 sample','1000 sample'],vert=False,showmeans=True,notch = True,sym = '*',patch_artist = True, boxprops = {
     'color':'orangered','facecolor':'pink'})

输出结果：

1.7 直方图 - bar()

bar(x, height, width=0.8, bottom=None, *, align='center', data=None, **kwargs)

常用参数：
x：输入值。必选参数。
height：输入值。必选参数。
width : 柱状图宽度(0~1)

基本功能 - 直方图绘制

import matplotlib.pyplot as plt
import numpy as np
X = np.arange(8)+1 
Y1 = np.random.uniform(0.5,1.0,8)
Y2 = np.random.uniform(0.3,1.0,8)
plt.bar(X, Y1, alpha=0.9, width = 0.35, facecolor = 'lightskyblue', edgecolor = 'white', label='one', linewidth =1)
plt.bar(X+0.35, Y2, alpha=0.9, width = 0.35, facecolor = 'yellowgreen', edgecolor = 'white', label='second', linewidth =1)

输出结果：

进阶设置 - 正负柱状图 / 标注

import matplotlib.pyplot as plt
import numpy as np
plt.figure(figsize=(10,4))
x = np.arange(10)
y1 = np.random.rand(10)
y2 = -np.random.rand(10)
#正负柱状图
plt.bar(x,y1,width = 1,facecolor = 'yellowgreen',edgecolor = 'white',yerr = y1*0.1)
plt.bar(x,y2,width = 1,facecolor = 'lightskyblue',edgecolor = 'white',yerr = y2*0.1)
#增加标注
for i,j in zip(x,y1):
    plt.text(i-0.15,j-0.15,'%.2f' % j, color = 'white')
for i,j in zip(x,y2):
    plt.text(i-0.15,j+0.05,'%.2f' % -j, color = 'white')

输出结果：

1.8 饼状图 – pie()

pie(x, explode=None, labels=None, colors=None, autopct=None, pctdistance=0.6, shadow=False, labeldistance=1.1, startangle=None, radius=None, counterclock=True, wedgeprops=None, textprops=None, center=(0, 0), frame=False, rotatelabels=False, *, data=None)

常用参数：
x：输入值。必选参数。
explode:各饼之间间距
colors:各饼的填充色
autopct：百分比显示格式
pctdistance:百分比标签与圆心距离
labeldistance:图例标签与圆心距离
startangle:初始摆放角度
radius：饼图半径
center:中心点位置

基本功能 - 饼状图绘制

from matplotlib import pyplot as plt 
plt.figure(figsize=(6,9))
labels = ['part 1','part 2','part 3']
sizes = [40,30,20]
colors = ['red','yellowgreen','lightskyblue']
textprops={
     'fontsize':18,'color':'black'}
plt.pie(sizes,explode=explode,labels=labels,colors=colors,labeldistance = 1.1,autopct = '%3.1f%%',shadow = False,startangle = 90,pctdistance = 0.6,textprops=textprops)
plt.axis('equal')
plt.legend()
plt.show()

输出结果：

进阶设置 - 环形饼图/空心饼图

from matplotlib import pyplot as plt 
plt.figure(figsize=(6,9))
#设定各pie标识
labels = ['part 1','part 2','part 3','part 4']
#设定各pie颜色
colors = ['red','yellowgreen','lightskyblue','hotpink']
#设定标注字体
textprops={
     'fontsize':12,'color':'black'}
#设定圆盘线宽
wedgeprops={
     'linewidth':1,'edgecolor':'black'}
#绘制外圈
sizes_1 = [40,30,20,10]
plt.pie(sizes_1,radius=1.0,labels=labels,colors=colors,labeldistance = 1.1,autopct = '%3.1f%%',shadow = False,startangle = 90,pctdistance = 0.85,textprops=textprops,wedgeprops=wedgeprops)
#绘制中圈，覆盖部分外圈
sizes_2 = [35,30,15,20]
plt.pie(sizes_2,radius=0.7,colors=colors,autopct = '%3.1f%%',shadow = False,startangle = 90,pctdistance = 0.75,textprops=textprops,wedgeprops=wedgeprops)
#绘制内圈，白色覆盖
sizes_3 = [1]
plt.pie(sizes_3, radius=0.4,colors = 'w',wedgeprops=wedgeprops)
plt.axis('equal')
plt.legend()
plt.show()

输出结果：

1.9 热图 - imshow()

imshow(X, cmap=None, norm=None, aspect=None, interpolation=None, alpha=None, vmin=None, vmax=None, origin=None, extent=None, shape=<deprecated parameter>, filternorm=1, filterrad=4.0, imlim=<deprecated parameter>, resample=None, url=None, *, data=None, **kwargs)

x：输入值。必选参数。
cmap:颜色图谱
interpolation:模糊度设置。

各颜色图谱测试

import matplotlib.pyplot as plt
import numpy as np
plt.figure(figsize=(20,12))
x=np.random.randn(10,10)
syscmap=['autumn','bone','cool','copper','flag','gray','hot','hsv','inferno','jet','magma','pink','plasma','prism','spring','summer','viridis','winter']
for i in range(3):
    for j in range(6):
        plt.subplot2grid((3,6),(i,j))
        plt.imshow(x,cmap=syscmap[6*i+j])

输出结果：

各透明度测试

import matplotlib.pyplot as plt
import numpy as np
plt.figure(figsize=(20,12))
sysinterpolation=['none','none','nearest','bilinear','bicubic','spline16','spline36','hanning','hamming','hermite','kaiser','quadric','catrom','gaussian','bessel','mitchell','sinc','lanczos']
for i in range(3):
	for j in range(6):
		plt.subplot2grid((3,6),(i,j))
		plt.imshow(x,cmap='hot',interpolation=sysinterpolation[6*i+j])

3. 附录

可用的Colors, Markers, Linestyles，这些内容可用help() 命令中看到。

Colors
The following color abbreviations are supported:

=============    ===============================
character        color
=============    ===============================
``'b'``          blue
``'g'``          green
``'r'``          red
``'c'``          cyan
``'m'``          magenta
``'y'``          yellow
``'k'``          black
``'w'``          white
=============    ==============================

**Markers**

=============    ===============================
character        description
=============    ===============================
``'.'``          point marker
``','``          pixel marker
``'o'``          circle marker
``'v'``          triangle_down marker
``'^'``          triangle_up marker
``'<'``          triangle_left marker
``'>'``          triangle_right marker
``'1'``          tri_down marker
``'2'``          tri_up marker
``'3'``          tri_left marker
``'4'``          tri_right marker
``'s'``          square marker
``'p'``          pentagon marker
``'*'``          star marker
``'h'``          hexagon1 marker
``'H'``          hexagon2 marker
``'+'``          plus marker
``'x'``          x marker
``'D'``          diamond marker
``'d'``          thin_diamond marker
``'|'``          vline marker
``'_'``          hline marker
=============    ==============================

**Line Styles**
=============    ===============================
character        description
=============    ===============================
``'-'``          solid line style
``'--'``         dashed line style
``'-.'``         dash-dot line style
``':'``          dotted line style
=============    ===============================
Example format strings::
    'b'    # blue markers with default shape
    'ro'   # red circles
    'g-'   # green solid line
    '--'   # dashed line with default color
    'k^:'  # black triangle_up markers connected by a dotted line