matpb画图_折线图.ipynb

In [1]:

import numpy as np
import matplotlib.pyplot as plt
from matplotlib import font_manager
y = [np.random.randint(10) for x in range(20)]
z = np.random.randint(1,10,size=10)
x = range(5,25)
print(x,y,z,sep='\n')
plt.plot(x,y)

Out [1]:

range(5, 25)
[3, 1, 3, 9, 9, 1, 7, 9, 5, 1, 7, 7, 2, 9, 7, 9, 2, 5, 1, 9]
[6 6 6 2 9 1 1 2 9 8]

Out [1]:

[<matplotlib.lines.Line2D at 0x2167dac1780>]

In [2]:

import pandas as pd
arr = pd.DataFrame(np.random.randint(0,10,size=(10,2)))
arr

Out [2]:

	0	1
0	1	4
1	2	9
2	0	3
3	6	4
4	0	1
5	9	5
6	8	8
7	1	3
8	3	7
9	9	4

In [3]:

plt.plot(arr,'')

Out [3]:

[<matplotlib.lines.Line2D at 0x2167e813b38>,
 <matplotlib.lines.Line2D at 0x2167e813ba8>]

In [4]:

plt.plot(arr,'^',color=(0.1,0.9,0.9,0.6))

Out [4]:

[<matplotlib.lines.Line2D at 0x2167e882400>,
 <matplotlib.lines.Line2D at 0x2167e882390>]

总结：

plt.plot(【x】,y,'',data = arr,color=(0.1,0.9,0.9,0.6))

【x】:可选项
y：必选项，
''：控制条形图的形状，
data = arr：传入一个datefram的数据
color=(0.1,0.9,0.9,0.6)：控制线条颜色，由四个数的元组构成。

设置线条样式

In [5]:

font = font_manager.FontProperties(fname=r"C:\Windows\Fonts\Dengb.ttf",size=10)
plt.plot(arr)
plt.title("折线图",fontproperties =font)

Out [5]:

Text(0.5, 1.0, '折线图')

设置坐标轴、标题的样式

In [6]:

font = font_manager.FontProperties(fname=r"C:\Windows\Fonts\Dengb.ttf",size=10)
avg = [37974.4,50918.4,30303.0,40329.5,45215,36258,86325,62154,75614,25648,25648,65824]
#avg = np.sort(avg)
plt.figure(figsize=(10,5))
plt.plot(avg,marker="o")
plt.xticks(range(12),["第%d天"%x for x in range(1,13)],fontproperties =font)
font.set_size(20)
plt.xlabel("天数",fontproperties =font)
plt.ylabel("票房(单位：万)",fontproperties =font)
font.set_size(30)
plt.title("长津湖前20天票房数据",fontproperties =font)
#plt.grid(True)
plt.show()

out [6]:

设置坐标点的样式

markerfacecolor：坐标点的颜色
markersize：坐标点的大小
markeredgecolor：坐标点的边界颜色

In [12]:

plt.style.use("ggplot")
x = np.linspace(0,20,150)
y = np.sin(x)
plt.plot(x,y,marker="o",markerfacecolor='g',markersize=10,markeredgecolor='b')
font.set_size(30)
plt.title("sin图像显示",fontproperties =font)

Out [12]:

Text(0.5, 1.0, 'sin图像显示')

设置数据标签

annotate是用来注释文本的：

In [8]:

y = np.sin(np.arange(20))
plt.plot(y,marker = 'o',color = 'g',markerfacecolor='r')
#plt.grid()
for index,value in enumerate(y):
    plt.annotate("(%d,%.1f)"%(index,value),xy=(index,value),xytext=(index-0.1,value-0.2))

out [8]:

设置画板的样式

figsize：画板大小,(宽度，高度)
facecolor:画板颜色
dpi：分辨率,默认为100
edgecolor：边框颜色，默认宽度是0，如果想要看到边框，则需要设置linewidth=2

In [9]:

plt.figure(figsize=(10,5),facecolor=(0.8,0.3,0.4),dpi=200,edgecolor=(0.2,0.2,0.8),linewidth=2)
plt.plot(np.sin(np.linspace(0,20,150)),marker = '^',color = 'g',markerfacecolor='y',markersize=10)
plt.savefig("G:\matlib文件\保存用例.png")
plt.show()

out [9]:

绘制多个图像

plt.subplot(221):几行几列，最后一个数是代表你当前绘制的是哪一个图
plt.style.use("ggplot")设置样式

In [10]:

plt.figure(figsize=(10,5),facecolor=(0.5,0.3,0.4),dpi=200)
plt.subplot(221)
plt.plot(np.sin(np.linspace(0,20,150)),color = 'g')
plt.subplot(222)
plt.plot(np.cos(np.linspace(0,20,150)),color = 'g')
plt.subplot(223)
plt.plot(np.tan(np.linspace(0,20,150)),color = 'r')
plt.subplot(224)
plt.plot(np.linspace(0,20,150),color = 'g')
plt.plot(np.linspace(0,20,150)**2,color = 'r')
plt.savefig("G:\matlib文件\subplot用例.png")

out [10]:

In [11]:

plt.figure(figsize=(10,5),facecolor=(0.5,0.3,0.4),dpi=200)
value = np.linspace(0,20,150)
plt.style.use("ggplot")
fig,axes = plt.subplots(2,2)
axe1 = axes[0,0]
axe1.plot(value)
axe2 = axes[0,1]
axe2.plot(np.sin(value),color = 'g')
axe3 = axes[1,0]
axe3.plot(np.cos(value),color = 'r')
axe4 = axes[1,1]
axe4.plot(np.tan(value),color = 'b')

Out [11]:

[<matplotlib.lines.Line2D at 0x216080dec18>]