第八章 使用matplotlib绘制高级图表

第八章 使用matplotlib绘制高级图表

这节课主要学习了如何使用matplotlib绘制一些高级的图表，还介绍了这些高级图表的一些特点和一些基本函数，主要学习了一些高线图、矢量磁场流线图、棉棒图、哑铃图、甘特图、人口金字塔图、漏斗图、桑基图、树状图、华夫饼图等等。
接下来是课堂上练习的一些实例图形：

import numpy as np
import matplotlib.pyplot as plt
def calcu_elevation(x1,y1):
    h=(1-x1/2+x1*5+y1**3)*np.exp(-x1**2-y1**2)
    return h
n=256
x=np.linspace(-2,2,n)
y=np.linspace(-2,2,n)
x_grid,y_grid=np.meshgrid(x,y)
fig=plt.figure()
ax=fig.add_subplot(111)
con=ax.contour(x_grid,y_grid,calcu_elevation(x_grid,y_grid),8,colors='black')
ax.contourf(x_grid,y_grid,calcu_elevation(x_grid,y_grid),8,alpha=0.75,cmap=plt.cm.copper)
ax.clabel(con,inline=True,fmt='%1.1f',fontsize=10)
ax.set_xticks([])
ax.set_yticks([])
plt.title("陈明江48")
plt.show()

import numpy as np
import matplotlib.pyplot as plt
y,x=np.mgrid[0:5:50j,0:5:50j]
u=x
v=y
fig=plt.figure()
ax=fig.add_subplot(111)
ax.streamplot(x,y,u,v)
plt.title("陈明江48")
plt.show()

import numpy as np
import matplotlib.pyplot as plt
plt.rcParams['font.family']='simHei'
plt.rcParams['axes.unicode_minus']=False
x = np.arange(1, 16)
y = np.array([5.9, 6.2,6.7,7.0,7.0,7.1,7.2,7.4,
                7.5,7.6,7.7,7.7,7.7,7.8,7.91])
labels = np.array(['宝骏310','宝马i3','致享','焕驰',' 力帆530',
'派力奥','悦翔v3','乐风RV',' 奥迪A1','威驰ES','夏利N7','启辰R30','和悦A13RS','1致炫5','赛欧'])
fig = plt.figure(figsize=(10, 6),dpi= 80)
ax = fig.add_subplot(111)
markerline,stemlines,baseline = ax.stem(x,y,linefmt='--',
markerfmt='o',label= 'TestStem',use_line_collection=True)
plt.setp(stemlines, lw=1)
ax.set_title ('陈明江48 不同品牌轿车的燃料消耗量',fontdict={'size':18})
ax.set_ylabel(' 燃料消耗量(L/kxm) ')
ax.set_xticks (x)
ax.set_xticklabels(labels,rotation=60)
ax.set_ylim([0,10])
for temp_x,temp_y in zip(x,y):
    ax.text(temp_x,temp_y+0.5,s='{}'.format(temp_y),ha='center',va='bottom',fontsize=14)
plt.show()

import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.lines as mlines
plt.rcParams['font.sans-serif']='SimHei'
plt.rcParams['axes.unicode_minus']=False
df=pd.read_excel(r"C:\Users\Administrator\Desktop\素材\health.xlsx")
df.sort_values('pct_2014',inplace=True)
df.reset_index(inplace=True)
df=df.sort_values(by="index")
def newline(p1,p2,color='black'):
    ax=plt.gca()
    l=mlines.Line2D([p1[0],p2[0]],[p1[1],p2[1]],color='skyblue')
    ax.add_line(l)
    return l
fig,ax=plt.subplots(1,1,figsize=(8,6))
ax.scatter(y=df['index'],x=df['pct_2013'],s=50,
          color='#0e668b',alpha=0.7)
ax.scatter(y=df['index'],x=df['pct_2014'],s=50,
          color='#a3c4dc',alpha=0.7)
for i,p1,p2 in zip(df['index'],df['pct_2013'],df['pct_2014']):
    newline([p1,i],[p2,i])
ax.set_title('陈明江48 2013与2014PCT指标变化率',fontdict={'size':12})
ax.set_xlim(0,.25)
ax.set_xticks([.05,.1,.15,.20])
ax.set_xticklabels(['%5','%10','%15','%20'])
ax.set_xlabel('变化率')
ax.set_yticks(df['index'])
ax.set_yticklabels(df['city'])
ax.grid(alpha=0.5,axis='x')
plt.show()

import numpy as np
import matplotlib.pyplot as plt
ticks=np.array(['报告提交','数据分析','数据录入','实地执行',
                '问卷确定','试访','问卷设计','项目确定'])
y_data=np.arange(1,9)
x_data=np.array([0.5,1.5,1,3,0.5,1,1,2])
fig,ax=plt.subplots(1,1)
ax.barh(y_data,x_data,tick_label=ticks,
       left=[7.5,6,5.5,3,3,2,1.5,0],color='skyblue')
[ax.spines[i].set_visible(False) for i in ['top','right']]
ax.set_title("陈明江48 任务甘特图")
ax.set_xlabel("日期")
ax.grid(alpha=0.5,axis='x')
plt.show()

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
plt.rcParams['font.sans-serif'] = 'SimHei'
plt.rcParams['axes.unicode_minus'] = False
df = pd.read_excel(r"C:\Users\Administrator\Desktop\素材\population.xlsx")
df_male = df.groupby(by='Gender').get_group('Male')
list_male = df_male['Number'].values.tolist()    
df_female = df.groupby(by='Gender').get_group('Female')
list_female = df_female['Number'].values.tolist() 
df_age = df.groupby('AgeGroup').sum()
count = df_age.shape[0]
y = np.arange(1, 11)
labels = []
for i in range(count):
    age = df_age.index[i]
    labels.append(age)
fig = plt.figure()
ax = fig.add_subplot(111)
ax.barh(y, list_male, tick_label=labels, label=' 男', color='#6699FF') 
ax.barh(y, list_female, tick_label=labels, label=' 女', color='#CC6699')
ax.set_ylabel("年龄段（岁）")
ax.set_xticks([-100000, -75000, -50000, -25000, 0, 25000, 50000, 75000, 100000])
ax.set_xticklabels(['100000', '75000', '50000', '25000', 
                    '0', '25000', '50000', '75000', '100000'])
ax.set_xlabel("人数（个）")
ax.set_title('陈明江48 某城市人口金字塔')
ax.legend()
plt.show()

import numpy as np
import matplotlib.pyplot as plt
plt.rcParams['font.sans-serif']='SimHei'
plt.rcParams['axes.unicode_minus']=False
num=5
height=0.5
x1=np.array([1000,500,300,200,150])
x2=np.array((x1.max()-x1)/2)
x3=[i+j for i,j in zip(x1,x2)]
x3=np.array(x3)
y=-np.sort(-np.arange(num))
labels=['访问商店','加购物车','生成订单','支付订单','完成交易']
fig=plt.figure(figsize=(10,8))
ax=fig.add_subplot(111)
rects1=ax.barh(y,x3,height,tick_label=labels,color='g',alpha=0.5)
rects2=ax.barh(y,x2,height,color='w',alpha=1)
ax.plot(x3,y,'black',alpha=0.7)
ax.plot(x2,y,'black',alpha=0.7)
notes=[]
for i in range(0,len(x1)):
    notes.append('%.2f%%'%((x1[i]/x1[0])*100))
for rect_one,rect_two,note in zip(rects1,rects2,notes):
    text_x=rect_two.get_width()+(rect_one.get_width()
                                -rect_two.get_width())/2-30
    
    text_y=rect_one.get_y()+height/2
    ax.text(text_x,text_y,note,fontsize=12)
ax.set_xticks([])
for direction in ['top','left','bottom','right']:
    ax.spines[direction].set_color('none')
ax.yaxis.set_ticks_position('none')
plt.title('陈明江48')
plt.show()

import matplotlib.pyplot as plt
from matplotlib.sankey import Sankey
plt.rcParams['font.sans-serif']='SimHei'
plt.rcParams['axes.unicode_minus']=False
flows=[0.7,0.3,-0.3,-0.1,-0.3,-0.1,-0.1,-0.1]
labels=["工资","副业","生活","购物","深造","运动","其他"," 买书"]
orientations=[1,1,0,-1,1,-1,1,0]
sankey=Sankey()
sankey.add(flows=flows,labels=labels,orientations=orientations,
           color='black',fc="lightgreen",patchlabel="生活消费",alpha=0.7)
diagrams=sankey.finish()
diagrams[0].texts[4].set_color("r")
diagrams[0].texts[4].set_weight("bold")
diagrams[0].text.set_fontsize(20)
diagrams[0].text.set_fontweight("bold")
plt.title("陈明江48 日常生活开支的桑基图")
plt.show()

import pandas as pd
import matplotlib.pyplot as plt
import scipy.cluster.hierarchy as shc
plt.rcParams['font.sans-serif'] = ['SimHei']
plt.rcParams['axes.unicode_minus'] = False
df = pd.read_excel(r"C:\Users\Administrator\Desktop\素材\USArrests.xlsx")
plt.figure(figsize=(10, 6), dpi= 80)
plt.title("陈明江48 美国各州犯罪案件的树状图", fontsize=12)
dend = shc.dendrogram(shc.linkage(df[['Murder', 'Assault', 'UrbanPop']], method='ward'), 
                      labels=df.State.values, color_threshold=100)
plt.xticks(fontsize=10.5)
plt.ylabel('案例数量(个)')
plt.show()

import matplotlib.pyplot as plt
from pywaffle import Waffle
plt.rcParams['font.family']='simHei'
plt.rcParams['axes.unicode_minus']=False
plt.figure(FigureClass=Waffle,rows=10,columns=10,
          values=[95,5],vertical=True,colors=['#20B2AA','#D3D3D3'],
          title={'label':'陈明江48 电影《少年的你》上座率'},
          legend={'loc':'upper right','labels':['占座','空座']})
plt.show()