python可视化：pyplot各种图形样例

1.使用 plt.plot() 画 折线图

函数格式： 

格式1：plt.plot([x], y, [fmt], data=None, **kwargs)

格式2：plt.plot([x], y, [fmt], [x2], y2, [fmt2], ..., **kwargs)

参数说明：

fmt = '[color][marker][line]'**kwargs:

In  [78]:

import numpy as np

import matplotlib.pyplot as plt

x = np.arange(20)

y = x**2

fmt = 'r-'

plt.plot(x,y,fmt,label='y=x^2')

plt.xlabel('x') #x轴的名字

plt.ylabel('y') #y轴的名字

plt.legend() #在图区显示label

plt.show()

In  [77]:

import numpy as np

import matplotlib.pyplot as plt

x = np.arange(20)

plt.plot(x,x**2,'o',

x,2*x,'-',

x,3*x,'+'

)

plt.show()

In  [76]:

import numpy as np

import matplotlib.pyplot as plt

x = np.arange(20)

y1 = x**2

y2 = x*2

y3 = x*3

plt.plot(x, y1, '^', label='y=x^2')

plt.plot(x, y2, '1', label='y=x*2')

plt.plot(x, y3, '*', label='y=x*3')

plt.legend()

plt.show()

2. 使用 plt.bar() 画 条形图

函数格式： plt.bar( ['x', 'height', 'width=0.8', 'bottom=None', '', "align='center'", 'data=None', '*kwargs'], )

In  [75]:

import numpy as np

import matplotlib.pyplot as plt

x = np.arange(20)

y = 2*x

plt.bar(x,y,label="y=2*x")

plt.legend()

Out[75]:

<matplotlib.legend.Legend at 0x120dac88>

3. 使用 plt.hist() 画 直方图

函数格式：plt.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'], )

In  [74]:

import matplotlib.pyplot as plt

x = [1,2,2,3,3,3,4]

plt.hist(x,label='hist',color='g')

plt.legend()

plt.show()

4. 使用 plt.scatter() 画 散点图

函数格式：plt.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', '', 'data=None', '*kwargs'], )

说明 ：

s : scalar or array_like, shape (n, ), optional The marker size in points*2. Default is rcParams['lines.markersize'] * 2.

c : color, sequence, or sequence of color, optional

In  [73]:

import numpy as np

import matplotlib.pyplot as plt

x = np.arange(10)

y=2*x

scalar = x**2

color = x

plt.scatter(x, y, scalar , color , 'o', label="y = 2*x")

plt.legend()

plt.show()

In  [72]:

import numpy as np

import matplotlib.pyplot as plt

N=300

x = np.random.randn(N)

y1 = np.random.randn(N)

y2 = y1*2

plt.scatter(x,y1,label="random")

plt.scatter(x,y2,label="random2")

plt.legend()

plt.show()

5. 使用 plt.pie() 画 饼状图

函数格式：plt.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'], )

explode：(每一块)离开中心距离，数据格式。

In  [70]:

import matplotlib.pyplot as plt

x = [0.2,0.4,0.1,0.3]

explode=(0,0.1,0,0)

labels = ['apple1','apple2','apple3','apple4']

colors= ['c','r','m','b']

plt.pie(x,explode,labels=labels,colors=colors)

plt.legend()

plt.show()

6. 使用 plt.stackplot() 画 堆叠图

函数格式：plt.stackplot(x, args, data=None, *kwargs)

格式1：stackplot(x, y) # where y is MxN

格式2：stackplot(x, y1, y2, y3, y4) # where y1, y2, y3, y4, are all 1xNm

*args:

x : 1d array of dimension N

y : 2d array (dimension MxN), or sequence of 1d arrays (each dimension 1xN)

baseline : {'zero', 'sym', 'wiggle', 'weighted_wiggle'}

labels : Length N sequence of strings

colors : Length N sequence of colors

In  [71]:

import matplotlib.pyplot as plt

days = [1,2,3,4,5]

sleeping = [7,8,6,11,7]

eating = [2,3,4,3,2]

working = [7,8,7,2,2]

playing = [8,5,7,8,13]

color = ['m','c','r','k']

labels = ['Sleeping','Eating','Working','Playing']

plt.stackplot(days, sleeping,eating,working,playing, colors=color ,labels=labels)

plt.xlabel('x')

plt.ylabel('y')

plt.title('a day')

plt.legend()

plt.show()