数据分析--数据可视化(Matplotlib)

数据可视化(Matplotlib)
1.基本绘图

plot(水平坐标, 垂直坐标)
numpy.linspace（start，stop，num = 50，endpoint = True，retstep = False，
dtype = None ）
在指定的间隔内返回均匀间隔的数字。返回num均匀间隔的样本，在[ start，stop ] 区间内计算。
可以选择排除间隔的终点。
参数：	
	start(开始)： 标量  序列的起始值。
	end(停止) ： 标量序列的结束值，除非端点设置为False。在这种情况下，序列由除均匀间隔的
	样本之外的所有样本组成，因此不包括停止。请注意，当端点为False 时，步长会发生变化。num
    + 1
	num ： int，可选,   要生成的样本数。默认值为50.必须为非负数。
	endpoint(端点) ： bool，可选如果为True，则stop是最后一个样本。否则，它不包括在内。
   	默认为True。
	retstep ： bool，可选如果为True，则返回（samples，step），其中step是样本之间的
	间距。
	dtype ： dtype，可选
	输出数组的类型。如果dtype未给出，则从其他输入参数推断数据类型。
返回：	
	样品 ： ndarray
	有NUM同样在闭区间隔开的样品 或半开间隔 （取决于是否端点是真或假）。[start, stop]
	[start, stop)

步骤：浮动，可选
	仅在retstep为True 时才返回
	样本之间的间距大小。

代码：

	# -*- coding: utf-8 -*-
	
	import numpy as np
	import matplotlib.pyplot as mp
	x = np.linspace(-np.pi, np.pi, 1000) # 范围从-π到π，生成1000个点
	cos_y = np.cos(x)
	sin_y = np.sin(x)
	mp.plot(x, cos_y)
	mp.plot(x, sin_y)
	mp.show()   # 必须有np.show()否则生成的图像保存在内存中，展示不出来

2.线型、线宽和颜色

plot(..., linestyle=线型, linewidth=线宽, color=颜色, ...)
线型：[-]/--/:/-./o/o-/...
线宽：0-oo
color：dodgerblue/orangered/limegreen/red/blue/...

代码：

	# -*- 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.plot(x, cos_y, linestyle='--', linewidth=1,
	        color='dodgerblue')
	mp.plot(x, sin_y, linestyle='-.', linewidth=3,
	        color='orangered')
	mp.show()

3.设置坐标范围

xlim(水平坐标最小值，水平坐标最大值)
ylim(垂直坐标最小值，垂直坐标最大值)
坐标范围越大，图形越小，反而反之。

代码：

	# -*- 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)
	#　设置横纵坐标范围
	mp.xlim(x.min() * 1.1, x.max() * 1.1)
	mp.ylim(sin_y.min() * 1.1, sin_y.max() * 1.1)
	mp.plot(x, cos_y, linestyle='--', linewidth=1,
	        color='dodgerblue')
	mp.plot(x, sin_y, linestyle='-.', linewidth=3,
	        color='orangered')
	mp.show()

4.设置坐标刻度

xticks(水平轴刻度位置[, 水平轴刻度文本])
yticks(垂直轴刻度位置[, 垂直轴刻度文本])

代码：

	# -*- 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.xlim(x.min() * 1.1, x.max() * 1.1)
	mp.ylim(sin_y.min() * 1.1, sin_y.max() * 1.1)
	#　设置横纵坐标刻度
	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])
	
	mp.plot(x, cos_y, linestyle='--', linewidth=1,
	        color='dodgerblue')
	mp.plot(x, sin_y, linestyle='-.', linewidth=3,
	        color='orangered')
	mp.show()

5.设置坐标轴属性

ax = gca() # 获取当前坐标轴图
ax.spines['left'] -> 左纵轴
ax.spines['right'] -> 右纵轴
ax.spines['top'] -> 上横轴
ax.spines['bottom'] -> 下横轴
XX轴.set_position((坐标系, 位置值)) # 设置位置
XX轴.set_color(颜色) # 设置颜色

代码：

	# -*- 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.xlim(x.min() * 1.1, x.max() * 1.1)
	mp.ylim(sin_y.min() * 1.1, sin_y.max() * 1.1)
	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])
	# 设置横纵坐标(0,0),将图像放在坐标的中间
	ax = mp.gca()
	ax.spines['left'].set_position(('data', 0))
	ax.spines['bottom'].set_position(('data', 0))
	ax.spines['right'].set_color('none')
	ax.spines['top'].set_color('none')
	
	mp.plot(x, cos_y, linestyle='--', linewidth=1,
	        color='dodgerblue')
	mp.plot(x, sin_y, linestyle='-.', linewidth=3,
	        color='orangered')
	mp.show()

6.图例

plot(..., label=图例标签, ...)
legend([loc=显示位置])

代码：

	# -*- 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.xlim(x.min() * 1.1, x.max() * 1.1)
	mp.ylim(sin_y.min() * 1.1, sin_y.max() * 1.1)
	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])
	ax = mp.gca()
	ax.spines['left'].set_position(('data', 0))
	ax.spines['bottom'].set_position(('data', 0))
	ax.spines['right'].set_color('none')
	ax.spines['top'].set_color('none')
	
	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=3,
	        color='orangered',
	        label=r'$y=sin(x)$')
	mp.legend()
	mp.show()

7.添加特殊点

scatter(水平坐标, 垂直坐标, s=大小, marker=点形,
edgecolor=边缘色, facecolor=填充色,
zorder=Z顺序)

代码：

	# -*- 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)
	# 自定义点的x轴位置
	xo = np.pi * 3 / 4
	yo_cos = np.cos(xo) / 2
	yo_sin = np.sin(xo)
	
	mp.xlim(x.min() * 1.1, x.max() * 1.1)
	mp.ylim(sin_y.min() * 1.1, sin_y.max() * 1.1)
	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])
	#　设置(0,0)点为坐标原点
	ax = mp.gca()
	ax.spines['left'].set_position(('data', 0))
	ax.spines['bottom'].set_position(('data', 0))
	ax.spines['right'].set_color('none')
	ax.spines['top'].set_color('none')
	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=3,
	        color='orangered',
	        label=r'$y=sin(x)$')
	mp.plot([xo, xo], [yo_cos, yo_sin], linewidth=0.5,
	        color='limegreen')
	# 添加特殊点
	mp.scatter([xo, xo], [yo_cos, yo_sin], s=60,
	           edgecolor='limegreen', facecolor='white',
	           marker='D', zorder=3)
	#　标注文本
	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=.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=.2'))
	mp.legend(loc='upper left')
	mp.show()

8.备注

annotate(
    备注文本,
    xy=目标坐标,
    xycoords=目标坐标系,
    xytext=文本坐标,
    textcoords=文本坐标系,
    fontsize=字体大小,
    arrowprops=箭头属性)

9.图形(窗口)对象

figure(窗口名(标题栏文本), figsize=大小, dpi=分辨率,
    facecolor=颜色)
如果与指定窗口名对应的图形对象不存在，那么就新建一个图形窗口，如果已存在，那么不会再新建图形
窗口，而是将已存在的那个图形窗口设置为当前窗口。
title(窗口标题, fontsize=字体大小)
xlabel(水平轴标签, fontsize=字体大小)
ylabel(垂直轴标签, fontsize=字体大小)
tick_params(labelsize=刻度标签字体大小)
grid(linestyle=网格线型)

代码：

	# -*- 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)
	# 窗口名
	mp.figure('Figure Object 1', figsize=(6, 4),
	          dpi=120, facecolor='lightgray')
	#　窗口标题
	mp.title('Figure Object 1', fontsize=20)
	#  水平轴标签
	mp.xlabel('x', fontsize=14)
	#  垂直轴标签
	mp.ylabel('y', fontsize=14)
	mp.tick_params(labelsize=10)
	mp.grid(linestyle=':')
	
	mp.figure('Figure Object 2', figsize=(6, 4),
	          dpi=120, 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.legend()
	
	mp.figure('Figure Object 2')
	mp.plot(x, sin_y, color='orangered',
	        label=r'$y=sin(x)$')
	mp.legend()
	
	mp.show()

10.子坐标图

1)矩阵布局
	1 2
	3 4
subplot(行数, 列数, 图号) # 创建子图
tight_layout() # 紧凑布局

代码：

# -*- coding: utf-8 -*-
	from __future__ import unicode_literals
	import matplotlib.pyplot as mp
	mp.figure('Matrix Layout', facecolor='lightgray')
	# 创建布局
	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)
	#　紧凑布局
	mp.tight_layout()
	mp.show()

2)栅格布局

import matplotlib.gridspec as mg
栅格定位器 = mg.GridSpec(行数, 列数)
subplot(栅格定位器[行, 列])

代码：

	# -*- coding: utf-8 -*-
	from __future__ import unicode_literals
	import matplotlib.pyplot as mp
	import matplotlib.gridspec as mg
	mp.figure('Grid Layout', facecolor='lightgray')
	# 栅格定位器
	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()

3)自由布局

axes([左, 底, 宽, 高]) # 归一化单位

代码：

	# -*- coding: utf-8 -*-
	from __future__ import unicode_literals
	import matplotlib.pyplot as mp
	mp.figure('Free Layout', 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()

11.刻度定位器

刻度定位器 = xxxLocator(定位规则)
ax = gca()
ax.xaxis -> 水平坐标轴
ax.yaxis -> 垂直坐标轴
坐标轴.set_major_locator(刻度定位器) # 主刻度
坐标轴.set_minor_locator(刻度定位器) # 次刻度

代码：

	# -*- 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, 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['right'].set_color('none')
	    ax.spines['top'].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), c='none')
	    mp.text(5, 0.3, locator[3:], ha='center', size=12)
	mp.tight_layout()
	mp.show()

12.区域填充

fill_between(
水平坐标, 起点垂直坐标, 终点垂直坐标, 填充条件,
color=颜色, alpha=透明度)

代码：

	# -*- coding: utf-8 -*-
	from __future__ import unicode_literals
	import numpy as np
	import matplotlib.pyplot as mp
	# 生成数据
	n = 1000
	x = np.linspace(0, 8 * np.pi, n)
	sin_y = np.sin(x)
	cos_y = np.cos(x / 2) / 2
	# 创建图形窗口
	mp.figure('Fill', facecolor='lightgray')
	# 设置窗口标题
	mp.title('Fill', fontsize=20)
	# 设置坐标轴标签
	mp.xlabel('x', fontsize=14)
	mp.ylabel('y', fontsize=14)
	# 设置刻度参数
	mp.tick_params(labelsize=10)
	# 设置网格线型
	mp.grid(linestyle=':')
	# 绘制曲线
	mp.plot(x, sin_y, c='dodgerblue',
	        label=r'$y=sin(x)$')
	mp.plot(x, cos_y, c='orangered',
	        label=r'$y=\frac{1}{2}cos(\frac{x}{2})$')
	# 绘制填充区域
	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)
	# 绘制图例
	mp.legend()
	# 显示图形
	mp.show()