基於matplotlib的數據可視化
- matplotlib.pyplot基於Python語言的繪圖函數
  - 基本圖形繪製

基於matplotlib的數據可視化

matplotlib.pyplot基於Python語言的繪圖函數

基本圖形繪製

缺省樣式


# -*- coding:utf-8 -*-


from __future__ import unicode_literals
import numpy as np 
import matplotlib.pyplot as mp 

#生成曲線上各點的水平座標

x=np.linspace(-np.pi,np.pi,1000)

cos_y=np.cos(x)/2
sin_y=np.sin(x)

h_y=x/2

#用直線鏈接曲線上的各點

mp.plot(x,cos_y)
mp.plot(x,sin_y)
mp.plot(x,h_y)

#顯示圖形

mp.show()

設置線型、線寬和顏色

代碼：


# -*- coding: utf-8 -*-

from __future__ import unicode_literals
import numpy as np
import matplotlib.pyplot as mp

# 生成曲線上各點的水平座標

x = np.linspace(-np.pi, np.pi, 1000)

# 根據曲線函數計算其上各點的垂直座標

cos_y = np.cos(x) / 2
sin_y = np.sin(x)

# 用直線連接曲線上各點

mp.plot(x, cos_y, linestyle='-', linewidth=1,
        color='dodgerblue')
mp.plot(x, sin_y, linestyle='-', linewidth=1,
        color='orangered')

# 顯示圖形

mp.show()

設置座標範圍

設置水平座標範圍：mp.xlim(最小值, 最大值)
設置垂直座標範圍：mp.ylim(最小值, 最大值)

代碼：


# -*- coding:utf-8 -*-

from __future__ import unicode_literals
import matplotlib.pyplot as mp 

#   plotting 測繪 library 

import numpy as np 

#生成曲線上各點的水平座標

x=np.linspace(-np.pi,np.pi,2000)

#根據曲線函數計算其上各點的垂直座標

cos_y=np.cos(x)/2
sin_y=np.sin(x)

#設置座標範圍

mp.xlim(x.min()*1.1,x.max()*1.1)
mp.ylim(min(cos_y.min(),sin_y.min())*1.1,
        max(cos_y.max(),sin_y.max())*1.1)

#用直線連接曲線上各點

mp.plot(x,cos_y,linestyle='-',linewidth=1,
    color='dodgerblue')
mp.plot(x,sin_y,linestyle='-',linewidth=1,
    color='orangered')

#顯示圖形

mp.show()

設置座標軸刻度標籤

mp.xticks(刻度標籤位置, 刻度標籤文本)
mp.yticks(刻度標籤位置, 刻度標籤文本)

代碼：


# -*- coding:utf-8 -*-

from __future__ import unicode_literals
import matplotlib.pyplot as mp 

#   plotting 測繪 library 

import numpy as np 

#生成曲線上各點的水平座標

x=np.linspace(-np.pi,np.pi,2000)

#根據曲線函數計算其上各點的垂直座標

cos_y=np.cos(x)/2
sin_y=np.sin(x)

#設置座標範圍

mp.xlim(x.min()*1.1,x.max()*1.1)
mp.ylim(min(cos_y.min(),sin_y.min())*1.1,
        max(cos_y.max(),sin_y.max())*1.1)

mp.xticks([-np.pi,-np.pi/2,np.pi/2,np.pi*3/4,np.pi],
    [r'$-\pi$',r'$-\frac{\pi}{2}$',r'$0$',
    r'$\frac{\pi}{2}$',r'$\frac{3\pi}{4}$',r'$\pi$'])
mp.yticks([-1,-0.5,0.5,1])

#用直線連接曲線上各點

mp.plot(x,cos_y,linestyle='-',linewidth=1,
    color='dodgerblue')
mp.plot(x,sin_y,linestyle='-',linewidth=1,
    color='orangered')

#顯示圖形

mp.show()

將矩形座標軸改成十字座標軸

代碼：


# -*- coding: utf-8 -*-

from __future__ import unicode_literals
import numpy as np
import matplotlib.pyplot as mp

# 生成曲線上各點的水平座標

x = np.linspace(-np.pi, np.pi, 1000)

# 根據曲線函數計算其上各點的垂直座標

cos_y = np.cos(x) / 2
sin_y = np.sin(x)

# 設置座標範圍

mp.xlim(x.min() * 1.1, x.max() * 1.1)
mp.ylim(min(cos_y.min(), sin_y.min()) * 1.1,
        max(cos_y.max(), sin_y.max()) * 1.1)

# 設置座標軸刻度標籤

mp.xticks([
    -np.pi, -np.pi / 2, 0, np.pi / 2, np.pi * 3 / 4, np.pi], [
    r'$-\pi$', r'$-\frac{\pi}{2}$', r'$0$',
    r'$\frac{\pi}{2}$', r'$\frac{3\pi}{4}$', r'$\pi$'])
mp.yticks([-1, -0.5, 0.5, 1])

# 將矩形座標軸改成十字座標軸


# 獲取當前座標軸對象

ax = mp.gca()

# 將垂直座標刻度置於左邊框

ax.yaxis.set_ticks_position('left')

# 將左邊框置於數據座標原點

ax.spines['left'].set_position(('data', 0))

# 將水平座標刻度置於底邊框

ax.xaxis.set_ticks_position('bottom')

# 將底邊框置於數據座標原點

ax.spines['bottom'].set_position(('data', 0))

# 將右邊框和頂邊框設置成無色

ax.spines['right'].set_color('none')
ax.spines['top'].set_color('none')

# 用直線連接曲線上各點

mp.plot(x, cos_y, linestyle='-', linewidth=1,
        color='dodgerblue')
mp.plot(x, sin_y, linestyle='-', linewidth=1,
        color='orangered')

# 顯示圖形

mp.show()

顯示圖例

mp.plot(…, label=圖例文本)
mp.legend(loc=圖例位置)

代碼：


# -*- coding: utf-8 -*-

from __future__ import unicode_literals
import numpy as np
import matplotlib.pyplot as mp

# 生成曲線上各點的水平座標

x = np.linspace(-np.pi, np.pi, 1000)

# 根據曲線函數計算其上各點的垂直座標

cos_y = np.cos(x) / 2
sin_y = np.sin(x)

# 設置座標範圍

mp.xlim(x.min() * 1.1, x.max() * 1.1)
mp.ylim(min(cos_y.min(), sin_y.min()) * 1.1,
        max(cos_y.max(), sin_y.max()) * 1.1)

# 設置座標軸刻度標籤

mp.xticks([
    -np.pi, -np.pi / 2, 0, np.pi / 2, np.pi * 3 / 4, np.pi], [
    r'$-\pi$', r'$-\frac{\pi}{2}$', r'$0$',
    r'$\frac{\pi}{2}$', r'$\frac{3\pi}{4}$', r'$\pi$'])
mp.yticks([-1, -0.5, 0.5, 1])

# 將矩形座標軸改成十字座標軸


# 獲取當前座標軸對象

ax = mp.gca()

# 將垂直座標刻度置於左邊框

ax.yaxis.set_ticks_position('left')

# 將左邊框置於數據座標原點

ax.spines['left'].set_position(('data', 0))

# 將水平座標刻度置於底邊框

ax.xaxis.set_ticks_position('bottom')

# 將底邊框置於數據座標原點

ax.spines['bottom'].set_position(('data', 0))

# 將右邊框和頂邊框設置成無色

ax.spines['right'].set_color('none')
ax.spines['top'].set_color('none')

# 用直線連接曲線上各點

mp.plot(x, cos_y, linestyle='-', linewidth=1,
        color='dodgerblue', label=r'$y=\frac{1}{2}cos(x)$')
mp.plot(x, sin_y, linestyle='-', linewidth=1,
        color='orangered', label=r'$y=sin(x)$')
mp.legend(loc='upper left')

# 顯示圖形

mp.show()

添加特殊點

mp.scatter(點集水平座標數組，點集垂直座標數組，…)

代碼：


# -*- coding: utf-8 -*-

from __future__ import unicode_literals
import numpy as np
import matplotlib.pyplot as mp

# 生成曲線上各點的水平座標

x = np.linspace(-np.pi, np.pi, 1000)

# 根據曲線函數計算其上各點的垂直座標

cos_y = np.cos(x) / 2
sin_y = np.sin(x)

# 計算特殊點的座標

xo = np.pi * 3 / 4
yo_cos = np.cos(xo) / 2
yo_sin = np.sin(xo)

# 設置座標範圍

mp.xlim(x.min() * 1.1, x.max() * 1.1)
mp.ylim(min(cos_y.min(), sin_y.min()) * 1.1,
        max(cos_y.max(), sin_y.max()) * 1.1)

# 設置座標軸刻度標籤

mp.xticks([
    -np.pi, -np.pi / 2, 0, np.pi / 2, np.pi * 3 / 4, np.pi], [
    r'$-\pi$', r'$-\frac{\pi}{2}$', r'$0$',
    r'$\frac{\pi}{2}$', r'$\frac{3\pi}{4}$', r'$\pi$'])
mp.yticks([-1, -0.5, 0.5, 1])

# 將矩形座標軸改成十字座標軸


# 獲取當前座標軸對象

ax = mp.gca()

# 將垂直座標刻度置於左邊框

ax.yaxis.set_ticks_position('left')

# 將左邊框置於數據座標原點

ax.spines['left'].set_position(('data', 0))

# 將水平座標刻度置於底邊框

ax.xaxis.set_ticks_position('bottom')

# 將底邊框置於數據座標原點

ax.spines['bottom'].set_position(('data', 0))

# 將右邊框和頂邊框設置成無色

ax.spines['right'].set_color('none')
ax.spines['top'].set_color('none')

# 用直線連接曲線上各點

mp.plot(x, cos_y, linestyle='-', linewidth=1,
        color='dodgerblue', label=r'$y=\frac{1}{2}cos(x)$')
mp.plot(x, sin_y, linestyle='-', linewidth=1,
        color='orangered', label=r'$y=sin(x)$')

# 繪製特殊點

mp.plot([xo, xo], [yo_cos, yo_sin], linestyle='--',
        linewidth=1, color='limegreen')
mp.scatter([xo, xo], [yo_cos, yo_sin], s=60,
           edgecolor='limegreen', facecolor='white',
           zorder=3)
mp.legend(loc='upper left')

# 顯示圖形

mp.show()

添加註釋

mp.annotate(
註釋文本,
xy=目標位置，
xytext=文本位置，
textcoords=座標屬性，
fontsize=字體大小，
arrowprops=箭頭屬性)

代碼：


# -*- coding: utf-8 -*-

from __future__ import unicode_literals
import numpy as np
import matplotlib.pyplot as mp

# 生成曲線上各點的水平座標

x = np.linspace(-np.pi, np.pi, 1000)

# 根據曲線函數計算其上各點的垂直座標

cos_y = np.cos(x) / 2
sin_y = np.sin(x)

# 計算特殊點的座標

xo = np.pi * 3 / 4
yo_cos = np.cos(xo) / 2
yo_sin = np.sin(xo)

# 設置座標範圍

mp.xlim(x.min() * 1.1, x.max() * 1.1)
mp.ylim(min(cos_y.min(), sin_y.min()) * 1.1,
        max(cos_y.max(), sin_y.max()) * 1.1)

# 設置座標軸刻度標籤

mp.xticks([
    -np.pi, -np.pi / 2, 0, np.pi / 2, np.pi * 3 / 4, np.pi], [
    r'$-\pi$', r'$-\frac{\pi}{2}$', r'$0$',
    r'$\frac{\pi}{2}$', r'$\frac{3\pi}{4}$', r'$\pi$'])
mp.yticks([-1, -0.5, 0.5, 1])

# 將矩形座標軸改成十字座標軸


# 獲取當前座標軸對象

ax = mp.gca()

# 將垂直座標刻度置於左邊框

ax.yaxis.set_ticks_position('left')

# 將左邊框置於數據座標原點

ax.spines['left'].set_position(('data', 0))

# 將水平座標刻度置於底邊框

ax.xaxis.set_ticks_position('bottom')

# 將底邊框置於數據座標原點

ax.spines['bottom'].set_position(('data', 0))

# 將右邊框和頂邊框設置成無色

ax.spines['right'].set_color('none')
ax.spines['top'].set_color('none')

# 用直線連接曲線上各點

mp.plot(x, cos_y, linestyle='-', linewidth=1,
        color='dodgerblue', label=r'$y=\frac{1}{2}cos(x)$')
mp.plot(x, sin_y, linestyle='-', linewidth=1,
        color='orangered', label=r'$y=sin(x)$')

# 繪製特殊點

mp.plot([xo, xo], [yo_cos, yo_sin], linestyle='--',
        linewidth=1, color='limegreen')
mp.scatter([xo, xo], [yo_cos, yo_sin], s=60,
           edgecolor='limegreen', facecolor='white',
           zorder=3)

# 添加註釋

mp.annotate(
    r'$\frac{1}{2}cos(\frac{3\pi}{4})=-\frac{\sqrt{2}}{4}$',
    xy=(xo, yo_cos), xycoords='data',
    xytext=(-90, -40), textcoords='offset points',
    fontsize=14, arrowprops=dict(
        arrowstyle='->', connectionstyle='arc3, rad=0.2'))
mp.annotate(
    r'$sin(\frac{3\pi}{4})=\frac{\sqrt{2}}{2}$',
    xy=(xo, yo_sin), xycoords='data',
    xytext=(20, 20), textcoords='offset points',
    fontsize=14, arrowprops=dict(
        arrowstyle='->', connectionstyle='arc3, rad=0.2'))

# 顯示圖例

mp.legend(loc='upper left')

# 顯示圖形

mp.show()

圖形對象

說明：一個圖像對象實際上就可以被看做是一個顯示圖形的窗口，出了缺省創建的圖形窗口以外，也可以通過函數手動創建圖形窗口並設置特殊的屬性。
屬性：
1. mp.figure(對象名(標題文本), figsize=窗口大小,
  dpi=分辨率, facecolor=窗口顏色)
2. mp.title(標題文本, fontsize=字體大小)
3. mp.xlabel(水平軸標籤文本, fontsize=字體大小)
4. mp.ylabel(垂直軸標籤文本, fontsize=字體大小)
5. mp.tick_params(labelsize=刻度標籤字體大小)
6. mp.grid(linestyle=網格線風格)
7. 注意如果調用figure()函數時所指定的對象名並不存在，則新建一個圖形窗口，同時將其設置爲當前窗口，如果該對象名已經存在，則不再建新窗口，而只是將其所對應的圖形窗口設置爲當前窗口。調用該函數以後的所有繪圖都在當前窗口中完成。

代碼：


# -*- coding: utf-8 -*-

from __future__ import unicode_literals
import numpy as np
import matplotlib.pyplot as mp
x = np.linspace(-np.pi, np.pi, 1000)
cos_y = np.cos(x) / 2
sin_y = np.sin(x)
mp.figure('Figure Object 1', figsize=(8, 6), dpi=60,
          facecolor='lightgray')#打開窗口，設置分辨率
mp.title('Figure Object 1', fontsize=20)#設置標題
mp.xlabel('x', fontsize=14)#水平標籤文本，fontsize=字體大小
mp.ylabel('y', fontsize=14)#垂直標籤文件，fontsize字體大小
mp.tick_params(labelsize=10)#labelsize=刻度標籤字體大小
mp.grid(linestyle=':')#linestyle＝網格線風格

mp.figure('Figure Object 2', figsize=(8, 6), dpi=60,
          facecolor='lightgray')
mp.title('Figure Object 2', fontsize=20)
mp.xlabel('x', fontsize=14)
mp.ylabel('y', fontsize=14)
mp.tick_params(labelsize=10)
mp.grid(linestyle=':')

mp.figure('Figure Object 1')
mp.plot(x, cos_y, color='dodgerblue',
        label=r'$y=\frac{1}{2}cos(x)$')
mp.figure('Figure Object 2')
mp.plot(x, sin_y, color='orangered', label=r'$y=sin(x)$')
mp.legend()
mp.figure('Figure Object 1')
mp.legend()
mp.show()

子座標圖

mp.subplot(總行數, 總列數, 圖序號)

代碼：sub1.py、sub2.py、sub3.py


# -*- coding: utf-8 -*-

from __future__ import unicode_literals
import matplotlib.pyplot as mp
mp.figure(facecolor='lightgray')
mp.subplot(221)
mp.xticks(())
mp.yticks(())
mp.text(0.5, 0.5, '1', ha='center', va='center', size=36,
        alpha=0.5)
mp.subplot(222)
mp.xticks(())
mp.yticks(())
mp.text(0.5, 0.5, '2', ha='center', va='center', size=36,
        alpha=0.5)
mp.subplot(223)
mp.xticks(())
mp.yticks(())
mp.text(0.5, 0.5, '3', ha='center', va='center', size=36,
        alpha=0.5)
mp.subplot(224)
mp.xticks(())
mp.yticks(())
mp.text(0.5, 0.5, '4', ha='center', va='center', size=36,
        alpha=0.5)
mp.tight_layout()
mp.show()


# -*- coding: utf-8 -*-

from __future__ import unicode_literals
import matplotlib.pyplot as mp
import matplotlib.gridspec as mg
mp.figure(facecolor='lightgray')
gs = mg.GridSpec(3, 3)
mp.subplot(gs[0, :2])
mp.xticks(())
mp.yticks(())
mp.text(0.5, 0.5, '1', ha='center', va='center', size=36,
        alpha=0.5)
mp.subplot(gs[1:, 0])
mp.xticks(())
mp.yticks(())
mp.text(0.5, 0.5, '2', ha='center', va='center', size=36,
        alpha=0.5)
mp.subplot(gs[2, 1:])
mp.xticks(())
mp.yticks(())
mp.text(0.5, 0.5, '3', ha='center', va='center', size=36,
        alpha=0.5)
mp.subplot(gs[:2, 2])
mp.xticks(())
mp.yticks(())
mp.text(0.5, 0.5, '4', ha='center', va='center', size=36,
        alpha=0.5)
mp.subplot(gs[1, 1])
mp.xticks(())
mp.yticks(())
mp.text(0.5, 0.5, '5', ha='center', va='center', size=36,
        alpha=0.5)
mp.tight_layout()
mp.show()


# -*- coding: utf-8 -*-

from __future__ import unicode_literals
import matplotlib.pyplot as mp
mp.figure(facecolor='lightgray')
mp.axes([0.03, 0.038, 0.94, 0.924])
mp.xticks(())
mp.yticks(())
mp.text(0.5, 0.5, '1', ha='center', va='center', size=36,
        alpha=0.5)
mp.axes([0.63, 0.076, 0.31, 0.308])
mp.xticks(())
mp.yticks(())
mp.text(0.5, 0.5, '2', ha='center', va='center', size=36,
        alpha=0.5)
mp.show()

設置座標軸刻度定位器

怎麼設置：
ax = mp.gca()
ax.xaxis.set_major_locator(刻度定位器對象)
ax.xaxis.set_minor_locator(刻度定位器對象)
ax.yaxis.set_major_locator(刻度定位器對象)
ax.yaxis.set_minor_locator(刻度定位器對象)

代碼：


# -*- coding: utf-8 -*-

from __future__ import unicode_literals
import numpy as np
import matplotlib.pyplot as mp
mp.figure()
locators = [
    'mp.NullLocator()',
    'mp.MaxNLocator(nbins=3, steps=[1, 3, 5, 7, 9])',
    'mp.FixedLocator(locs=[0, 2.5, 7.5, 10])',
    'mp.AutoLocator()',
    'mp.IndexLocator(offset=0.5, base=1.5)',
    'mp.MultipleLocator()',
    'mp.LinearLocator(numticks=21)',
    'mp.LogLocator(base=2, subs=[1.0])']
n_locators = len(locators)
for i, locator in enumerate(locators):
    mp.subplot(n_locators, 1, i + 1)
    mp.xlim(0, 10)
    mp.ylim(-1, 1)
    mp.yticks(())
    ax = mp.gca()
    ax.spines['left'].set_color('none')
    ax.spines['top'].set_color('none')
    ax.spines['right'].set_color('none')
    ax.spines['bottom'].set_position(('data', 0))
    ax.xaxis.set_major_locator(eval(locator))
    ax.xaxis.set_minor_locator(mp.MultipleLocator(0.1))
    mp.plot(np.arange(11), np.zeros(11), color='none')
    mp.text(5, 0.3, locator[3:], ha='center', size=12)
mp.tight_layout()
mp.show()

散點圖

mp.scatter(水平座標數組, 垂直座標數組,
s=大小, c=顏色, cmap=顏色映射, alpha=透明度)

代碼：


# -*- coding: utf-8 -*-

from __future__ import unicode_literals
import numpy as np
import matplotlib.pyplot as mp
n = 1000
x = np.random.normal(0, 1, n)
y = np.random.normal(0, 1, n)
d = np.sqrt(x ** 2 + y ** 2)
mp.figure('Scatter', facecolor='lightgray')
mp.title('Scatter', fontsize=20)
mp.xlabel('x', fontsize=14)
mp.ylabel('y', fontsize=14)
mp.tick_params(labelsize=10)
mp.grid(linestyle=':')
mp.scatter(x, y, s=6, c=d, cmap='jet_r', alpha=0.5)
mp.show()

填充

mp.fill_between(掃描線水平座標,
掃描線起點垂直座標, 掃描線終點垂直座標,
color=顏色, alpha=透明度)

代碼：


# -*- coding: utf-8 -*-

from __future__ import unicode_literals
import numpy as np
import matplotlib.pyplot as mp
n = 1000
x = np.linspace(0, 8 * np.pi, n)
sin_y = np.sin(x)
cos_y = np.cos(x / 2) / 2
mp.figure('Fill', facecolor='lightgray')
mp.title('Fill', fontsize=20)
mp.xlabel('x', fontsize=14)
mp.ylabel('y', fontsize=14)
mp.tick_params(labelsize=10)
mp.grid(linestyle=':')
mp.plot(x, sin_y, c='dodgerblue', label=r'$y=sin(x)$')
mp.plot(x, cos_y, c='orangered',
        label=r'$y=\frac{1}{2}cos(\frac{x}{2})$')
mp.fill_between(x, cos_y, sin_y, cos_y < sin_y,
                color='dodgerblue', alpha=0.5)
mp.fill_between(x, cos_y, sin_y, cos_y > sin_y,
                color='orangered', alpha=0.5)
mp.legend()
mp.show()

條形圖

mp.bar(矩形條的水平座標, 矩形條的高度
ec=邊框色, fc=填充色, label=圖例標籤)

代碼：bar.py


# -*- coding: utf-8 -*-

from __future__ import unicode_literals
import numpy as np
import matplotlib.pyplot as mp
n = 12
x = np.arange(n)
y1 = np.random.uniform(0.5, 1.0, n) * (1 - x / n)
y2 = np.random.uniform(0.5, 1.0, n) * (1 - x / n)
mp.figure('Bar', facecolor='lightgray')
mp.title('Bar', fontsize=20)
mp.xlabel('x', fontsize=14)
mp.ylabel('y', fontsize=14)
mp.xticks(x, x + 1)
mp.ylim(-1.25, 1.25)
mp.tick_params(labelsize=10)
mp.grid(axis='y', linestyle=':')
mp.bar(x, y1, ec='white', fc='dodgerblue',
       label='Sample 1')
for _x, _y in zip(x, y1):
    mp.text(_x, _y, '%.2f' % _y, ha='center',
            va='bottom', size=8)
mp.bar(x, -y2, ec='white', fc='dodgerblue', alpha=0.5,
       label='Sample 2')
for _x, _y in zip(x, y2):
    mp.text(_x, -_y - 0.015, '%.2f' % _y, ha='center',
            va='top', size=8)
mp.legend()
mp.show()

等高線圖

mp.contour(x, y, z, 密度, colors=顏色,
linewidths=線寬)
mp.contourf(x, y, z, 密度, cmap=顏色映射)

代碼：


# -*- coding: utf-8 -*-

from __future__ import unicode_literals
import numpy as np
import matplotlib.pyplot as mp
n = 1000
x, y = np.meshgrid(np.linspace(-3, 3, n),
                   np.linspace(-3, 3, n))
z = (1 - x / 2 + x ** 5 + y ** 3) * np.exp(-x ** 2 - y ** 2)
mp.figure('Contour', facecolor='lightgray')
mp.title('Contour', fontsize=20)
mp.xlabel('x', fontsize=14)
mp.ylabel('y', fontsize=14)
mp.tick_params(labelsize=10)
mp.grid(linestyle=':')
mp.contourf(x, y, z, 8, cmap='jet')
cntr = mp.contour(x, y, z, 8, colors='black', linewidths=0.5)
mp.clabel(cntr, inline_spacing=1, fmt='%.1f', fontsize=8)
mp.show()

熱力圖
1. mp.imshow(深度座標, cmap=顏色映射,
  origin=垂直軸向)
2. 代碼：hot.py

三維曲面/線框圖

怎麼做
from mpl_toolkits.mplot3d import axes3d
ax=mp.gca(projection=’3d’)
ax.plot_surface(x, y, z, rstride=垂直步長,
cstride=水平步長, cmap=顏色映射)
ax.plot_wireframe(x, y, z, rstride=垂直步長,
cstride=水平步長, color=顏色,
linewidth=線寬)

代碼：


# -*- coding: utf-8 -*-

from __future__ import unicode_literals
import numpy as np
import matplotlib.pyplot as mp
from mpl_toolkits.mplot3d import axes3d
n = 1000
x, y = np.meshgrid(np.linspace(-3, 3, n),
                   np.linspace(-3, 3, n))
z = (1 - x / 2 + x ** 5 + y ** 3) * np.exp(-x ** 2 - y ** 2)
mp.figure('3D Surface')
ax = mp.gca(projection='3d')
mp.title('3D Surface', fontsize=20)
ax.set_xlabel('x', fontsize=14)
ax.set_ylabel('y', fontsize=14)
ax.set_zlabel('z', fontsize=14)
mp.tick_params(labelsize=10)
ax.plot_surface(x, y, z, rstride=10, cstride=10, cmap='jet')
mp.figure('3D Wireframe')
ax = mp.gca(projection='3d')
mp.title('3D Wireframe', fontsize=20)
ax.set_xlabel('x', fontsize=14)
ax.set_ylabel('y', fontsize=14)
ax.set_zlabel('z', fontsize=14)
mp.tick_params(labelsize=10)
ax.plot_wireframe(x, y, z, rstride=20, cstride=20,
                  linewidth=0.5, color='orangered')
mp.show()

餅圖

mp.pie(值，空，標，色，格)

代碼：pie.py


# -*- coding: utf-8 -*-

from __future__ import unicode_literals
import matplotlib.pyplot as mp
values = [26, 17, 21, 29, 11]
spaces = [0.05, 0.01, 0.01, 0.01, 0.01]
labels = ['Python', 'JavaScript', 'C++', 'C', 'PHP']
colors = ['dodgerblue', 'orangered', 'limegreen', 'violet',
          'gold']
mp.figure('Pie', facecolor='lightgray')
mp.title('Pie', fontsize=20)
mp.pie(values, spaces, labels, colors, '%d%%', shadow=True,
       startangle=90)
mp.axis('equal')
mp.show()

座標格線

ax = mp.gca()
ax.grid(which=主次刻度, axis=橫縱軸,
linewidth=線寬, linestyle=線型, color=顏色)

代碼：grid.py


# -*- coding: utf-8 -*-

from __future__ import unicode_literals
import numpy as np
import matplotlib.pyplot as mp
x = np.linspace(-5, 5, 1000)
y = 8 * np.sinc(x)
mp.figure('Grid', facecolor='lightgray')
mp.title('Grid', fontsize=20)
mp.xlabel('x', fontsize=14)
mp.ylabel('y', fontsize=14)
ax = mp.gca()
ax.xaxis.set_major_locator(mp.MultipleLocator())
ax.xaxis.set_minor_locator(mp.MultipleLocator(.1))
ax.yaxis.set_major_locator(mp.MultipleLocator())
ax.yaxis.set_minor_locator(mp.MultipleLocator(.1))
mp.tick_params(labelsize=10)
ax.grid(which='major', axis='both', linewidth=0.75,
        linestyle='-', color='lightgray')
ax.grid(which='minor', axis='both', linewidth=0.25,
        linestyle='-', color='lightgray')
mp.plot(x, y, c='dodgerblue', label=r'$y=8sinc(x)$')
mp.legend()
mp.show()

極座標
1. ax = mp.gca(projection=’polar’)
2. mp.plot(極角, 極徑, …)

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