Python之Matplotlib（1）

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
In [5]:

x = np.random.rand(10)
y = np.random.rand(10)
plt.scatter(x,y)
#显示的方法
plt.show()
x = np.random.rand(10)
y = np.random.rand(10)
plt.scatter(x,y)
#显示的方法
plt.show()

In [8]:

plt.plot(np.random.rand(100))
#显示的方法
plt.show()

In [7]:

% matplotlib inline
x = np.random.rand(10)
y = np.random.rand(10)
plt.scatter(x,y)
#显示的方法
#加入 % matplotlib inline 就不用plt.show()
Out[7]:
<matplotlib.collections.PathCollection at 0x7454908>

In [ ]:


import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
% matplotlib inline
In [60]:

#图名  图例   轴标签    轴边界    轴刻度    轴刻度标签
df = pd.DataFrame(np.random.rand(10,2),columns=['A','B'])
flg = df.plot(figsize=(6,4))
#图名
plt.title("Kobe")
#xy的标签
plt.xlabel('x')
plt.ylabel('y')
#图例
'''
    best
    lower right
    right
    upper center
    center left
    upper right
    lower left
    center right
    lower center
    upper left
    center
'''
plt.legend(loc = "center")
​
#轴边界
plt.xlim([0,9])
plt.ylim([0,1])
​
#刻度
plt.xticks(range(10))
plt.yticks([0.0,0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9])
​
#轴刻度标签
flg.set_xticklabels("%.1f" %i for i in (range(10)))
flg.set_yticklabels("%.2f" %i for i in [0.0,0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9])
​
#网格
#axis x，y只显示xy  ，不填都显示
plt.grid(True,linestyle='--',color = 'red',linewidth='1',axis='x')
​
#刻度的显示
plt.tick_params(bottom = 'on',top = 'on',left='on',right = 'on')
​
#刻度在里面还是外面 in out inout
import matplotlib
matplotlib.rcParams['xtick.direction'] = 'out'
matplotlib.rcParams['ytick.direction'] = 'in'
​
#关闭坐标轴
#plt.axis('off')
​
#关闭xy坐标轴的显示
frame = plt.gca()
frame.axes.get_xaxis().set_visible(True)
frame.axes.get_yaxis().set_visible(True)
​
#注解
plt.text(3.5,0.6,'kobe',fontsize=10)
​
#保存
#dpi分辨率   
plt.savefig("G:/pic.jpeg",dpi=400,bbox_inches='tight',facecolor='g',edgecolor='b')
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
% matplotlib inline
In [60]:

#图名  图例   轴标签    轴边界    轴刻度    轴刻度标签
df = pd.DataFrame(np.random.rand(10,2),columns=['A','B'])
flg = df.plot(figsize=(6,4))
#图名
plt.title("Kobe")
#xy的标签
plt.xlabel('x')
plt.ylabel('y')
#图例
'''
    best
    lower right
    right
    upper center
    center left
    upper right
    lower left
    center right
    lower center
    upper left
    center
'''
plt.legend(loc = "center")
​
#轴边界
plt.xlim([0,9])
plt.ylim([0,1])
​
#刻度
plt.xticks(range(10))
plt.yticks([0.0,0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9])
​
#轴刻度标签
flg.set_xticklabels("%.1f" %i for i in (range(10)))
flg.set_yticklabels("%.2f" %i for i in [0.0,0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9])
​
#网格
#axis x，y只显示xy  ，不填都显示
plt.grid(True,linestyle='--',color = 'red',linewidth='1',axis='x')
​
#刻度的显示
plt.tick_params(bottom = 'on',top = 'on',left='on',right = 'on')
​
#刻度在里面还是外面 in out inout
import matplotlib
matplotlib.rcParams['xtick.direction'] = 'out'
matplotlib.rcParams['ytick.direction'] = 'in'
​
#关闭坐标轴
#plt.axis('off')
​
#关闭xy坐标轴的显示
frame = plt.gca()
frame.axes.get_xaxis().set_visible(True)
frame.axes.get_yaxis().set_visible(True)
​
#注解
plt.text(3.5,0.6,'kobe',fontsize=10)
​
#保存
#dpi分辨率   
plt.savefig("G:/pic.jpeg",dpi=400,bbox_inches='tight',facecolor='g',edgecolor='b')

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
In [5]:

x = np.random.rand(10)
y = np.random.rand(10)
plt.scatter(x,y)
#显示的方法
plt.show()
x = np.random.rand(10)
y = np.random.rand(10)
plt.scatter(x,y)
#显示的方法
plt.show()

In [8]:

plt.plot(np.random.rand(100))
#显示的方法
plt.show()

In [7]:

% matplotlib inline
x = np.random.rand(10)
y = np.random.rand(10)
plt.scatter(x,y)
#显示的方法
#加入 % matplotlib inline 就不用plt.show()
Out[7]:
<matplotlib.collections.PathCollection at 0x7454908>

In [ ]: