Python双轴组合图表-柱状图+折线图

Python绘制双轴组合的关键在plt库的twinx()函数,具体流程:

1.先建立坐标系,然后绘制主坐标轴上的图表;

2.再调用plt.twinx()方法;

3.最后绘制次坐标轴图表。

import cx_Oracle
import xlrd
import xlwt
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.ticker import FuncFormatter

plt.rcParams['font.sans-serif']=['SimHei']
plt.rcParams['axes.unicode_minus']=False
#设置坐标轴数值以百分比(%)显示函数
def to_percent(temp, position):
  return '%1.0f'%(1*temp) + '%'
#字体设置
font2 = {'family' : 'Times New Roman',
'weight' : 'normal',
'size'   : 25,
}

conn=cx_Oracle.connect('用户名/密码@IP:端口/数据库')
c=conn.cursor()
#sql查询语句,多行用()括起来
sql_detail=("select substr(date1,6,10)date1,round(avg(r_qty))r_qty,round(avg(e_qty))e_qty,"
"round(avg(r_qty)/avg(e_qty),2)*100 userate,round(avg(uptime),2)*100 uptime from 表tp
" "tp where 条件 " "group by date1 order by date1 ") x=c.execute(sql_detail) #获取sql查询数据 data=x.fetchall() #print(data) #新建Excel保存数据 xl=xlwt.Workbook() ws=xl.add_sheet("ROBOT 30 DAYS MOVE ") #ws.write_merge(0,1,0,4,"ROBOT_30_DAYS_MOVE") for i,item in enumerate(data): for j,val in enumerate(item): ws.write(i,j,val) xl.save("E:\ROBOT_30_DAYS_MOVE.xls") #读取Excel数据 data1 = xlrd.open_workbook( "E:\ROBOT_30_DAYS_MOVE.xls") sheet1=data1.sheet_by_index(0) date1=sheet1.col_values(0) r_qty=sheet1.col_values(1) e_qty=sheet1.col_values(2) userate=sheet1.col_values(3) uptime=sheet1.col_values(4) #空值处理 for a in r_qty: if a=='': a=0 for a in e_qty: if a=='': a=0 for a in userate: if a=='': a=0 for a in uptime: if a=='': a=0 #将list元素str转int类型 r_qty = list(map(int, r_qty)) e_qty = list(map(int, e_qty)) userate = list(map(int, userate)) uptime = list(map(int, uptime)) #添加平均值mean求平均 r_qty.append(int(np.mean(r_qty))) e_qty.append(int(np.mean(e_qty))) userate.append(int(np.mean(userate))) uptime.append(int(np.mean(uptime))) date1.append('AVG') #x轴坐标 x=np.arange(len(date1)) bar_width=0.35 plt.figure(1,figsize=(19,10)) #绘制主坐标轴-柱状图 plt.bar(np.arange(len(date1)),r_qty,label='RBT_MOVE',align='center',alpha=0.8,color='Blue',width=bar_width) plt.bar(np.arange(len(date1))+bar_width,e_qty,label='EQP_MOVE',align='center',alpha=0.8,color='orange',width=bar_width) #设置主坐标轴参数 plt.xlabel('') plt.ylabel('Move',fontsize=18) plt.legend(loc=1, bbox_to_anchor=(0,0.97),borderaxespad = 0.) #plt.legend(loc='upper left') for x,y in enumerate(r_qty): plt.text(x,y+100,'%s' % y,ha='center',va='bottom') for x,y in enumerate(e_qty): plt.text(x+bar_width,y+100,'%s' % y,ha='left',va='top') plt.ylim([0,8000]) #调用plt.twinx()后可绘制次坐标轴 plt.twinx() #次坐标轴参考线 target1=[90]*len(date1) target2=[80]*len(date1) x=list(range(len(date1))) plt.xticks(x,date1,rotation=45) #绘制次坐标轴-折线图 plt.plot(np.arange(len(date1)),userate,label='USE_RATE',color='green',linewidth=1,linestyle='solid',marker='o',markersize=3) plt.plot(np.arange(len(date1)),uptime,label='UPTIME',color='red',linewidth=1,linestyle='--',marker='o',markersize=3) plt.plot(np.arange(len(date1)),target1,label='90%target',color='black',linewidth=1,linestyle='dashdot') plt.plot(np.arange(len(date1)),target2,label='80%target',color='black',linewidth=1,linestyle='dashdot') #次坐标轴刻度百分比显示 plt.gca().yaxis.set_major_formatter(FuncFormatter(to_percent)) plt.xlabel('') plt.ylabel('Rate',fontsize=18) #图列 plt.legend(loc=2, bbox_to_anchor=(1.01,0.97),borderaxespad = 0.) plt.ylim([0,100]) for x,y in enumerate(userate): plt.text(x,y-1,'%s' % y,ha='right',va='bottom',fontsize=14) for x,y in enumerate(uptime): plt.text(x,y+1,'%s' % y,ha='left',va='top',fontsize=14) plt.title("ROBOT 30 DAYS MOVE") #图表Table显示plt.table() listdata=[r_qty]+[e_qty]+[userate]+[uptime]#数据 table_row=['RBT_MOVE','EQP_MOVE','USE_RATE(%)','UPTIME(%)']#行标签 table_col=date1#列标签 print(listdata) print(table_row) print(table_col) the_table=plt.table(cellText=listdata,cellLoc='center',rowLabels=table_row,colLabels=table_col,rowLoc='center',colLoc='center') #Table参数设置-字体大小太小,自己设置 the_table.auto_set_font_size(False) the_table.set_fontsize(12) #Table参数设置-改变表内字体显示比例,没有会溢出到表格线外面 the_table.scale(1,3) #plt.show() plt.savefig(r"E:\ROBOT_30_DAYS_MOVE.png",bbox_inches='tight') #关闭SQL连接 c.close() conn.close()

结果显示:

原文地址:https://www.cnblogs.com/bellin124/p/14610744.html