matplotlib 模塊 07

時間 2020-05-11

標籤 matplotlib 模塊简体版

原文原文鏈接

matplotlib 模塊

matplotlib 模塊

1.條形圖

import matplotlib.pyplot as plt
from matplotlib.font_manager import  FontProperties  # 修改字體
font=FontProperties(fname='C:\Windows\Fonts\simfang.ttf')

plt.style.use('ggplot')  # 設置條形圖的背景
classes=['3班','4班','5班','6班']
students = [66, 55, 45, 70]
classes_index=range(len(classes))
plt.bar(classes_index,students,color='darkgreen')

plt.xlabel('學生',fontproperties=font,fontsize=15)
plt.ylabel('學生人數',fontproperties=font,fontsize=15)
plt.title('班級-學生人數',fontproperties=font,fontsize=20)
plt.xticks(classes_index,classes,fontproperties=font)
plt.show()

2.直方圖

import numpy as np
import matplotlib.pyplot as plt
from matplotlib.font_manager import  FontProperties  # 修改字體
font=FontProperties(fname='C:\Windows\Fonts\simhei.ttf')
plt.style.use('ggplot')
x1=np.random.randn(10000) # 隨機生成10000個小數
x2=np.random.randn(10000)

fig = plt.figure() # 生成一張畫布
ax1 = fig.add_subplot(1,2,1) # 表示一行兩列取第一個
ax2 = fig.add_subplot(1,2,2) # 表示一行兩列取第二個

ax1.hist(x1,bins=50,color='green')  # 表示10000個小數分到50個柱子上
ax2.hist(x2,bins=50,color='blue')
ax1.set_title('x1的正太分佈',fontproperties=font) # 加子標題
ax2.set_title('x2的正太分佈',fontproperties=font) # 加子標題
fig.suptitle('兩個正太分佈',fontproperties=font,fontsize=20) # 父標題
plt.show()

3.折線圖

import numpy as np
import matplotlib.pyplot as plt
from matplotlib.font_manager import  FontProperties  # 修改字體
font=FontProperties(fname='C:\Windows\Fonts\simhei.ttf')
plt.style.use('ggplot')

x1=np.random.randn(40).cumsum()  # cumsum是講生成的隨機數一個個累加起來，做爲對應位置的新元素
x2=np.random.randn(40).cumsum()
x3=np.random.randn(40).cumsum()
x4=np.random.randn(40).cumsum()

plt.plot(x1,color='r',linestyle='-',marker='o',label='紅圓線')
plt.plot(x2,color='b',linestyle='--',marker='*',label='藍虛線')
plt.plot(x3,color='black',linestyle='-.',marker='s',label='黑方線')
plt.plot(x4,color='y',linestyle=':',marker='s',label='黃方線')
plt.legend(loc='best',prop=font) # 顯示label,loc不指定默認在最佳位置顯示label，指定right就是將label在右邊顯示
plt.show()

4.散點圖+直線圖

# 生成一個對稱軸爲x=1的二次函數
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.font_manager import  FontProperties  # 修改字體
font=FontProperties(fname='C:\Windows\Fonts\simhei.ttf')  # 
plt.style.use('ggplot')

x=np.arange(-20,21)
# y = np.random.randn(20).cumsum()
y=(x**2)+2*x+1
plt.scatter(x,y)
plt.show()

import numpy as np
import matplotlib.pyplot as plt
from matplotlib.font_manager import FontProperties
font=FontProperties(fname='C:\Windows\Fonts\simhei.ttf')


plt.style.use('ggplot')
x=np.arange(1,20,1)
print(x)

# 擬合一條水平散點線
np.random.seed(1)
y_linear=x+10*np.random.randn(19)
print(y_linear)

# 擬合一條x**2 的散點線
y_quad=x**2+10*np.random.randn(19)
print(y_quad)

# s是散點大小
fig = plt.figure()
ax1 = fig.add_subplot(121)
plt.scatter(x,y_linear,s=30,color='r',label='藍點')
plt.scatter(x,y_quad,s=100,color='b',label='紅點')

ax2= fig.add_subplot(122)
plt.plot(x,y_linear,color='r')
plt.plot(x,y_quad,color='b')

# 限制x軸和y軸的範圍取值
plt.xlim(min(x) -1,max(x) + 1)
plt.ylim(min(y_quad) - 10,max(y_quad) + 10)
fig.suptitle('散點圖+直線圖',fontproperties=font,fontsize=20)
ax1.set_title('散點圖',fontproperties=font)
ax1.legend(prop=font)  # 最佳位置顯示label
ax2.set_title('折線圖',fontproperties=font)
plt.show()

5.餅圖

import numpy as np
import  matplotlib.pyplot as plt
from pylab import mpl
from matplotlib.font_manager import FontProperties
font=FontProperties(fname='C:\Windows\Fonts\simhei.ttf')
mpl.rcParams['font.sans-serif'] = ['SimHei']

fig,ax = plt.subplots(subplot_kw=dict(aspect='equal'))

recipe = ['優','良','輕度污染','中度污染','重度污染','嚴重污染','缺']

data = [2,49,21,9,11,6,2]
colors = ['lime','yellow','darkorange','red','purple','maroon','grey',]
wedges,texts,texts2 = ax.pie(data,
                             wedgeprops=dict(width = 0.5),
                             startangle=40,
                             colors=colors,
                             autopct='%1.0f%%',
                             pctdistance=0.8)
# print(wedges)
'''
[<matplotlib.patches.Wedge object at 0x000000000EE46198>, <matplotlib.patches.Wedge object at 0x000000000EE46860>,
  <matplotlib.patches.Wedge object at 0x000000000EE46F28>, <matplotlib.patches.Wedge object at 0x000000000EE57630>,
  <matplotlib.patches.Wedge object at 0x000000000EE57CF8>, <matplotlib.patches.Wedge object at 0x000000000EE63400>, 
  <matplotlib.patches.Wedge object at 0x000000000EE63AC8>]
'''
# print(texts)
# print(texts2)
plt.setp(texts2,size=14,weight='bold')
bbox_props=dict(boxstyle='squre',pad='0.3',fc='w',ec='k',lw=0.72)
kw = dict(xycoords='data',
          textcoords='data',
          arrowprops=dict(arrowstyle='->'),
          bbox=None,
          zorder=0,
          va='center')
for i ,p in enumerate(wedges):
    # print(i,p)
    '''
     0 Wedge(center=(0, 0), r=1, theta1=40, theta2=47.2, width=0.5)
     1 Wedge(center=(0, 0), r=1, theta1=47.2, theta2=223.6, width=0.5)
     2 Wedge(center=(0, 0), r=1, theta1=223.6, theta2=299.2, width=0.5)
     3 Wedge(center=(0, 0), r=1, theta1=299.2, theta2=331.6, width=0.5)
     4 Wedge(center=(0, 0), r=1, theta1=331.6, theta2=371.2, width=0.5)
     5 Wedge(center=(0, 0), r=1, theta1=371.2, theta2=392.8, width=0.5)
     6 Wedge(center=(0, 0), r=1, theta1=392.8, theta2=400, width=0.5)
    '''
    ang=(p.theta2-p.theta1)/2. + p.theta1
    y=np.sin(np.deg2rad(ang))
    x = np.cos(np.deg2rad(ang))
    horizontalalignment = {-1:'right',1:'left'}[int(np.sign(x))]
    connectionstyle='angle,angleA=0,angleB={}'.format(ang)
    kw['arrowprops'].update({'connectionstyle':connectionstyle})
    ax.annotate(recipe[i],
                xy=(x,y),
                xytext=(1.25*np.sign(x),1.3*y),
                size=16,
                horizontalalignment=horizontalalignment,
                fontproperties=font,
                **kw)
ax.set_title('餅圖示例',fontproperties=font)
plt.show()