这里会整理些matplotlib绘图的小知识点，可能比较杂。

1. subplot

前面，我们有简单的说过subplot，通过他，我们可以在一个figure上，分割多个区域分别去绘图，
这里说一个最常用的方法

matplotlib.pyplot.subplots(nrows=1, ncols=1, sharex=False, sharey=False, squeeze=True, subplot_kw=None, gridspec_kw=None, **fig_kw)

Create a figure and a set of subplots
This utility wrapper makes it convenient to create common layouts of subplots, including the enclosing figure object, in a single call

import numpy as np
import matplotlib.pyplot as plt

#初始化2行2列的figure
f,axes = plt.subplots(2,2)

#这样通过下标可以快速的获取axes
axes[0,1].hist(np.random.randn(100),bins=20)

plt.show()

我们还可以设置，是否共享x轴y轴

调整subplot周围的间距

matplotlib.pyplot.subplots_adjust(*args, **kwargs)

subplots_adjust(left=None, bottom=None, right=None, top=None,
                wspace=None, hspace=None)

left  = 0.125  # the left side of the subplots of the figure
right = 0.9    # the right side of the subplots of the figure
bottom = 0.1   # the bottom of the subplots of the figure
top = 0.9      # the top of the subplots of the figure
wspace = 0.2   # the amount of width reserved for blank space between subplots,
               # expressed as a fraction of the average axis width
hspace = 0.2   # the amount of height reserved for white space between subplots,
               # expressed as a fraction of the average axis height

import numpy as np
import matplotlib.pyplot as plt

#初始化2行2列的figure
f,axes = plt.subplots(2,2)

data=np.random.randn(10).cumsum()

axes[0,0].plot(data,marker='o')
axes[0,0].set_title('default')

#drawstyle 
[‘default’ | ‘steps’ | ‘steps-pre’ | ‘steps-mid’ | ‘steps-post’]

axes[0,1].plot(data,drawstyle='steps-pre',marker='o')
axes[0,1].set_title('steps-pre')

axes[1,0].plot(data,drawstyle='steps-mid',marker='o')
axes[1,0].set_title('steps-mid')

axes[1,1].plot(data,drawstyle='steps-post',marker='o')
axes[1,1].set_title('steps-post')

#plt.subplots_adjust(hspace=0)

plt.show()

我们这里，可以设置轴要显示的刻度
比如，上面显示的是0，2，4，6，8

#设置显示的x轴的值
axes[0,0].set_xticks([0,5,10])
#将上面的值，替换为标签
axes[0,0].set_xticklabels(['one','two','three'])

好了，这里先补充这些，后面有的话继续，下一篇整理下pandas中绘图的方法