{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "## 基础知识" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 正则表达式分割文本" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "import openpyxl\n", "import re\n", "\n", "file_name = 'data/药食材性味归经.xlsx'\n", "wb = openpyxl.load_workbook(file_name)\n", "sheet = wb.active\n", "#sheets = wb.sheetnames\n", "\n", "list1 = []\n", "dict1 = {}\n", "mo =r'[。入归].+经$'\n", "mo1 = r'[二]'\n", "mo2 = r'[，、；]'\n", "for n in range(2,sheet.max_row):\n", " name = sheet.cell(n,1).value\n", " content = re.findall(mo,sheet.cell(n,2).value)\n", " if len(content) > 0:\n", " l = len(content[0])\n", " gj = re.sub(mo1, '', content[0][1:l-1]) \n", " list_gj = re.split(mo2,gj)\n", " dict1[sheet.cell(n,1).value ] = list_gj\n", " #dict1['guijing'] = list_gj\n", " \n", "filename = './data/药食材归经.json'\n", "with open(filename,'w') as fl:\n", " json.dump(dict1, fl,ensure_ascii=False) \n", "\n", "#print(list1)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "import re\n", "\n", "s = '消化不良、胃下垂、急性胃炎、慢性胃炎、萎缩性胃炎、神经性呕吐、胆囊炎、胆石症、胆道蛔虫症、胸胁痛等'\n", "ss = '健中和胃，消食止呕，理气疏郁，清热利胆。'\n", "mo = '等$'\n", "mo2 = r'[，、；。]'\n", "s1 = re.sub(mo, '', s) \n", "list1 = re.split(mo2,s1)\n", "if '' in list1:\n", " list1.remove('')\n", "print(list1)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "import re\n", "t = '5小时10分48秒'\n", "m = re.match(r'(.*)小时(.*)分(.*)秒', t)\n", "m.groups()" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "import re\n", "t = '10分48秒'\n", "list1 = []\n", "if '小时' in t and '分' in t:\n", " m = re.match(r'(.*)小时(.*)分(.*)秒', t)\n", " list1 = [m[1],m[2],m[3]]\n", "elif '小时' in t:\n", " m = re.match(r'(.*)小时(.*)秒', t)\n", " list1 = [m[1],0,m[2]]\n", "elif '分' in t:\n", " m = re.match(r'(.*)分(.*)秒', t)\n", " list1 = [0,m[1],m[2]]\n", "print(list1)\n", "#m.group()" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "import re\n", "\n", "s = '2022-09-28-《气郁组》-视频学习详情_155229'\n", "m = re.findall(r'《(.+)》',s)\n", "print(m)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 日期计算" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "import time\n", "\n", "birth = '1989-01-25'\n", "t_birth = time.strptime(birth,'%Y-%m-%d')\n", "days = (time.time() -time.mktime(t_birth))//(365*24*60*60)\n", "print(int(days))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 字符串转换" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "import binascii\n", "\n", "gbs = 'D4C0CDAF'\n", "bs = binascii.a2b_hex(gbs)\n", "print('bs', bs)\n", "print('decode-bs:', bs.decode('gbk'))\n", "\n", "s = '马立亚'\n", "gbcode = s.encode('gbk') # 先转成 bytes格式\n", "print('gbcode:', gbcode)\n", "gbs = \"\".join([hex(ch)[2:] for ch in gbcode]) #\n", "print('gbs:', gbs)" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "## 医药体测" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 药膳归经明细文件生成" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "\n", "filename = 'data/药膳210927.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "filename = 'data/药食材归经.json'\n", "with open(filename,'r') as fl:\n", " dict2 = json.load(fl)\n", "k_zy = dict2.keys()\n", "dict3 = {}\n", "list1 = []\n", "for item in dict1:\n", " print(item['name'])\n", " list1 = []\n", " #print(i,item['zy'])\n", " for m_zy in item['zy']:\n", " if m_zy in k_zy:\n", " dict4 = {}\n", " print(m_zy,dict2[m_zy])\n", " dict4[m_zy] = dict2[m_zy]\n", " list1.append(dict4)\n", " dict3[item['name']] = list1\n", "filename = './data/药膳药食材.json'\n", "with open(filename,'w') as fl:\n", " json.dump(dict3, fl,ensure_ascii=False) \n", " \n" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "### 药膳归经权重生成" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "import openpyxl\n", "import os,sys,shutil\n", "\n", "filename = './data/药膳药食材.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "list1 = []\n", "for k, v in dict1.items():\n", " if len(v) > 0 :\n", " dict2 = {}\n", " #print(k,v)\n", " ys_name = k\n", " dict2.setdefault(ys_name,{})\n", " for item in v:\n", " for k1, v1 in item.items():\n", " for item1 in v1:\n", " dict2[ys_name].setdefault(item1,0)\n", " dict2[ys_name][item1] += 1\n", " list1.append(dict2) \n", " \n", "dict_qz = {}\n", "for item in list1:\n", " for k, v in item.items():\n", " qz = sorted(v.items(), key = lambda kv:(kv[1], kv[0]),reverse=True)\n", " dict_qz[k] = qz\n", "#print(dict_qz)\n", "qz_key = dict_qz.keys()\n", "filename = 'data/药膳210927.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "#print(dict1)\n", "wb = openpyxl.Workbook()\n", "sheet = wb.active\n", "sheet['A1'] = '药膳名称'\n", "sheet['B1'] = '来源'\n", "sheet['C1'] = '配方'\n", "sheet['D1'] = '做法'\n", "sheet['E1'] = '功效'\n", "sheet['F1'] = '中药成分'\n", "sheet['G1'] = '归经权重'\n", "\n", "i =2\n", "for item in dict1:\n", " sheet[f'A{i}'] = item['name']\n", " sheet[f'B{i}'] = item['source']\n", " sheet[f'C{i}'] = item['pf']\n", " sheet[f'D{i}'] = item['zf']\n", " sheet[f'E{i}'] = item['gx']\n", " sheet[f'F{i}'] = ','.join(item['zy'])\n", " if item['name'] in qz_key:\n", " s = ''\n", " for m_gj in dict_qz[item['name']]:\n", " s = s+ m_gj[0] +'('+str(m_gj[1])+')'\n", " sheet[f'G{i}'] = s\n", " else:\n", " sheet[f'G{i}'] = '暂无归经'\n", " i += 1\n", "\n", "wb.save('data/test4.xlsx') \n", "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 体质数据处理" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### 体质对应数据导入" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "\n", "filename = 'data/tijianbingzheng.txt'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "m_key = set()\n", "for k, v in dict1.items():\n", " for item in v.keys():\n", " m_key.add(item)\n", "print(dict1)" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "### 穴位数据导入" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "#### 简单导出简介、内容" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "import re\n", "dict1 = {}\n", "filename = 'file/zhongyi/xuewei.json'\n", "with open(filename,'r',encoding='utf-8') as fl:\n", " for line in fl:\n", " line1 = json.loads(re.sub(r'\\xa0','',line))\n", " list1 = line1['tables']\n", " list2 = line1['contents']\n", " dict2 = dict(zip(list1, list2))\n", " #print(line1['title'],dict1)\n", " #print(dict1.keys())\n", " #print(line1)\n", " dict1.setdefault(line1['title'][0],{})\n", " dict1[line1['title'][0]]['简介'] = line1['jj'] \n", " dict1[line1['title'][0]]['内容'] = dict2\n", "filename = './file/穴位1.json'\n", "with open(filename,'w') as fl:\n", " json.dump(dict1, fl) " ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "#### 数据导入文件中" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "import re\n", "\n", "dict1 = {}\n", "filename = 'file/zhongyi/xuewei.json'\n", "with open(filename,'r',encoding='utf-8') as fl:\n", " for line in fl:\n", " line1 = json.loads(re.sub(r'\\xa0','',line))\n", " list1 = line1['tables']\n", " list2 = line1['contents']\n", " list3 = line1['jj']\n", " dict2 = dict(zip(list1, list2))\n", " dict1.setdefault(line1['title'][0],{})\n", " if len(list3) > 0:\n", " \n", " dict1[line1['title'][0]]['about'] = list3\n", " dict1[line1['title'][0]].setdefault('content',{})\n", " for k, v in dict2.items():\n", " dict1[line1['title'][0]]['content'][k] = v \n", " #dict1[line1['title'][0]]['内容'] = dict2\n", "filename = './file/穴位1.json'\n", "with open(filename,'w') as fl:\n", " json.dump(dict1, fl) " ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "#### 穴位数据导入数据库中" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "import re\n", "import pymongo\n", "\n", "myclient = pymongo.MongoClient('mongodb://10.147.17.6:27017/')\n", "#dblist = myclient.list_database_names()\n", "mydb = myclient['dayi']\n", "mycol = mydb[\"xuewei\"]\n", "db_list = []\n", "filename = 'file/zhongyi/xuewei.json'\n", "with open(filename,'r',encoding='utf-8') as fl:\n", " for line in fl:\n", " dict1 = {}\n", " line1 = json.loads(re.sub(r'\\xa0','',line))\n", " list1 = line1['tables']\n", " list2 = line1['contents']\n", " list3 = line1['jj']\n", " dict2 = dict(zip(list1, list2))\n", " dict1['name'] = line1['title'][0]\n", " if len(list3) > 0:\n", " dict1.setdefault('about',{})\n", " for s in list3:\n", " item = s.strip().split(':')\n", " dict1['about'][item[0].strip()] = item[1].strip()\n", " dict1.setdefault('content',{})\n", " for k, v in dict2.items():\n", " dict1['content'][k] = v \n", " #dict1[line1['title'][0]]['内容'] = dict2\n", " db_list.append(dict1)\n", "x = mycol.insert_many(db_list)\n", "print('ok!')" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "#### 中医症状数据导入数据库中" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "import re\n", "import pymongo\n", "\n", "myclient = pymongo.MongoClient('mongodb://10.147.17.6:27017/')\n", "mydb = myclient['dayi']\n", "mycol = mydb[\"zhongyizhengzhuang\"]\n", "db_list = []\n", "filename = 'file/zhongyi/zhongyizhengzhuang.json'\n", "with open(filename,'r',encoding='utf-8') as fl:\n", " for line in fl:\n", " dict1 = {}\n", " line1 = json.loads(re.sub(r'\\xa0','',line))\n", " list1 = line1['tables']\n", " list2 = line1['contents']\n", " list3 = line1['jj']\n", " dict2 = dict(zip(list1, list2))\n", " dict1['name'] = line1['title'][0]\n", " if len(list3) > 0:\n", " dict1.setdefault('about',{})\n", " for i in range(0,int(len(list3)/2)):\n", " dict1['about'][list3[2*i]] = list3[2*i+1]\n", " dict1.setdefault('content',{})\n", " for k, v in dict2.items():\n", " dict1['content'][k] = v \n", " #dict1[line1['title'][0]]['内容'] = dict2\n", " db_list.append(dict1)\n", "x = mycol.insert_many(db_list)\n", "print('ok!')" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "#### 疾病数据导入数据库中" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "import re\n", "import pymongo\n", "\n", "myclient = pymongo.MongoClient('mongodb://10.147.17.6:27017/')\n", "mydb = myclient['dayi']\n", "mycol = mydb[\"jibing\"]\n", "db_list = []\n", "filename = 'file/zhongyi/jibing.json'\n", "with open(filename,'r',encoding='utf-8') as fl:\n", " for line in fl:\n", " dict1 = {}\n", " line1 = json.loads(re.sub(r'\\xa0','',line))\n", " list1 = line1['tables']\n", " list2 = line1['contents']\n", " list3 = line1['jj']\n", " dict2 = dict(zip(list1, list2))\n", " dict1['name'] = line1['title'][0]\n", " if len(list3) > 0:\n", " dict1.setdefault('about',{})\n", " for i in range(0,int(len(list3)/2)):\n", " dict1['about'][list3[2*i]] = list3[2*i+1]\n", " dict1.setdefault('content',{})\n", " for k, v in dict2.items():\n", " dict1['content'][k] = v \n", " #dict1[line1['title'][0]]['内容'] = dict2\n", " db_list.append(dict1)\n", "x = mycol.insert_many(db_list)\n", "print('ok!')" ] }, { "cell_type": "markdown", "metadata": { "jp-MarkdownHeadingCollapsed": true, "tags": [] }, "source": [ "#### 术语数据导入数据库中" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "import json\n", "import re\n", "import pymongo\n", "\n", "myclient = pymongo.MongoClient('mongodb://10.147.17.6:27017/')\n", "#dblist = myclient.list_database_names()\n", "mydb = myclient['dayi']\n", "mycol = mydb[\"shuyu\"]\n", "db_list = []\n", "filename = 'file/zhongyi/shuyu.json'\n", "with open(filename,'r',encoding='utf-8') as fl:\n", " for line in fl:\n", " dict1 = {}\n", " line1 = json.loads(re.sub(r'\\xa0','',line))\n", " list1 = line1['tables']\n", " list2 = line1['contents']\n", " list3 = line1['jj']\n", " dict2 = dict(zip(list1, list2))\n", " dict1['name'] = line1['title'][0]\n", " if len(list3) > 0:\n", " dict1.setdefault('about',{})\n", " for s in list3:\n", " item = s.strip().split(':')\n", " dict1['about'][item[0]] = item[1]\n", " dict1.setdefault('content',{})\n", " for k, v in dict2.items():\n", " dict1['content'][k] = v \n", " #dict1[line1['title'][0]]['内容'] = dict2\n", " db_list.append(dict1)\n", "x = mycol.insert_many(db_list)\n", "print('ok!')" ] }, { "cell_type": "markdown", "metadata": { "execution": { "iopub.execute_input": "2021-12-15T10:01:32.917184Z", "iopub.status.busy": "2021-12-15T10:01:32.917184Z", "iopub.status.idle": "2021-12-15T10:01:32.921185Z", "shell.execute_reply": "2021-12-15T10:01:32.921185Z", "shell.execute_reply.started": "2021-12-15T10:01:32.917184Z" }, "jp-MarkdownHeadingCollapsed": true, "tags": [] }, "source": [ "#### 西医症状数据导入数据库中" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "import re\n", "import pymongo\n", "\n", "myclient = pymongo.MongoClient('mongodb://10.147.17.6:27017/')\n", "mydb = myclient['dayi']\n", "mycol = mydb[\"xiyizhengzhuang\"]\n", "db_list = []\n", "filename = 'file/zhongyi/xiyizhengzhuang.json'\n", "with open(filename,'r',encoding='utf-8') as fl:\n", " for line in fl:\n", " dict1 = {}\n", " line1 = json.loads(re.sub(r'\\xa0','',line))\n", " list1 = line1['tables']\n", " list2 = line1['contents']\n", " list3 = line1['jj']\n", " dict2 = dict(zip(list1, list2))\n", " dict1['name'] = line1['title'][0]\n", " if len(list3) > 0:\n", " dict1.setdefault('about',{})\n", " for i in range(0,int(len(list3)/2)):\n", " dict1['about'][list3[2*i]] = list3[2*i+1]\n", " dict1.setdefault('content',{})\n", " for k, v in dict2.items():\n", " dict1['content'][k] = v \n", " #dict1[line1['title'][0]]['内容'] = dict2\n", " db_list.append(dict1)\n", "x = mycol.insert_many(db_list)\n", "print('ok!')" ] }, { "cell_type": "markdown", "metadata": { "jp-MarkdownHeadingCollapsed": true, "tags": [] }, "source": [ "#### 药剂数据导入数据库中" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "import json\n", "import re\n", "import pymongo\n", "\n", "myclient = pymongo.MongoClient('mongodb://10.147.17.6:27017/')\n", "#dblist = myclient.list_database_names()\n", "mydb = myclient['dayi']\n", "mycol = mydb[\"yaoji\"]\n", "db_list = []\n", "filename = 'file/zhongyi/yaoji.json'\n", "with open(filename,'r',encoding='utf-8') as fl:\n", " for line in fl:\n", " dict1 = {}\n", " line1 = json.loads(re.sub(r'\\xa0','',line))\n", " list1 = line1['tables']\n", " list2 = line1['contents']\n", " list3 = line1['jj'] \n", " dict2 = dict(zip(list1, list2)) \n", " if len(list3) > 0: \n", " jj = {}\n", " for s in list3:\n", " item = s.strip().split(':')\n", " jj[item[0]] = item[1] \n", " dict1['name'] = jj['名称']\n", " dict1['about'] = jj\n", " dict1.setdefault('content',{})\n", " for k, v in dict2.items():\n", " dict1['content'][k] = v \n", " #dict1[line1['title'][0]]['内容'] = dict2\n", " db_list.append(dict1)\n", "x = mycol.insert_many(db_list)\n", "print('ok!')" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "#### 药膳数据导入数据库中" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "import re\n", "import pymongo\n", "\n", "myclient = pymongo.MongoClient('mongodb://10.147.17.6:27017/')\n", "#dblist = myclient.list_database_names()\n", "mydb = myclient['dayi']\n", "mycol = mydb[\"yaoshan\"]\n", "db_list = []\n", "filename = 'file/zhongyi/yaoshan.json'\n", "with open(filename,'r',encoding='utf-8') as fl:\n", " for line in fl:\n", " dict1 = {}\n", " line1 = json.loads(re.sub(r'\\xa0','',line))\n", " list1 = line1['tables']\n", " list2 = line1['contents']\n", " list3 = line1['jj']\n", " dict2 = dict(zip(list1, list2))\n", " dict1['name'] = line1['title'][0]\n", " if len(list3) > 0:\n", " dict1.setdefault('about',{})\n", " for s in list3:\n", " item = s.strip().split(':')\n", " dict1['about'][item[0]] = item[1]\n", " dict1.setdefault('content',{})\n", " for k, v in dict2.items():\n", " dict1['content'][k] = v \n", " #dict1[line1['title'][0]]['内容'] = dict2\n", " db_list.append(dict1)\n", "x = mycol.insert_many(db_list)\n", "print('ok!')" ] }, { "cell_type": "markdown", "metadata": { "jp-MarkdownHeadingCollapsed": true, "tags": [] }, "source": [ "#### 中草药数据导入数据库中" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "import json\n", "import re\n", "import pymongo\n", "\n", "myclient = pymongo.MongoClient('mongodb://10.147.17.6:27017/')\n", "mydb = myclient['dayi']\n", "mycol = mydb[\"zhongcaoyao\"]\n", "db_list = []\n", "filename = 'file/zhongyi/zhongcaoyao.json'\n", "with open(filename,'r',encoding='utf-8') as fl:\n", " for line in fl:\n", " dict1 = {}\n", " line1 = json.loads(re.sub(r'\\xa0','',line))\n", " list1 = line1['tables']\n", " list2 = line1['contents']\n", " list3 = line1['jj']\n", " dict2 = dict(zip(list1, list2))\n", " dict1['name'] = line1['title'][0]\n", " if len(list3) > 0:\n", " dict1.setdefault('about',{})\n", " for i in range(0,int(len(list3)/2)):\n", " dict1['about'][list3[2*i]] = list3[2*i+1]\n", " dict1.setdefault('content',{})\n", " for k, v in dict2.items():\n", " dict1['content'][k] = v \n", " #dict1[line1['title'][0]]['内容'] = dict2\n", " db_list.append(dict1)\n", "x = mycol.insert_many(db_list)\n", "print('ok!')" ] }, { "cell_type": "markdown", "metadata": { "jp-MarkdownHeadingCollapsed": true, "tags": [] }, "source": [ "### 穴位隶属整理" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "import re\n", "import pymongo\n", "\n", "myclient = pymongo.MongoClient('mongodb://10.147.17.6:27017/')\n", "mydb = myclient['dayi']\n", "mycol = mydb[\"xuewei\"]\n", "dict1 = {}\n", "list1 = []\n", "for x in mycol.find({},{ \"_id\": 0,\"name\":1,\"about.隶属\":1 }):\n", " if 'about' in x.keys():\n", " m_ls = x['about']['隶属']\n", " dict1.setdefault(m_ls,[])\n", " dict1[m_ls].append(x['name'])\n", "'''\n", "filename = './file/穴位隶属.json'\n", "with open(filename,'w') as fl:\n", " json.dump(dict1, fl) \n", "'''\n", "for item in dict1.keys():\n", " print(item)" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "### 穴位功能、主治统计" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "import re\n", "import pymongo\n", "\n", "myclient = pymongo.MongoClient('mongodb://10.147.17.6:27017/')\n", "mydb = myclient['dayi']\n", "mycol = mydb[\"xuewei\"]\n", "\n", "dict1 = {}\n", "mo = '等$'\n", "mo2 = r'[，、；。]'\n", "\n", "for x in mycol.find({},{ \"_id\": 0,\"name\":1,\"about\":1 }):\n", " dict1.setdefault(x['name'],{})\n", " if '主治' in x['about'].keys():\n", " #dict1[x['name']].setdefault('主治',[])\n", " s = x['about']['主治']\n", " s1 = re.sub(mo, '', s)\n", " list1 = re.split(mo2,s1)\n", " if '' in list1:\n", " list1.remove('')\n", " dict1[x['name']]['主治'] = list1\n", " if '功能' in x['about'].keys():\n", " #dict1[x['name']].setdefault('主治',[])\n", " s = x['about']['功能']\n", " s1 = re.sub(mo, '', s)\n", " list1 = re.split(mo2,s1)\n", " if '' in list1:\n", " list1.remove('')\n", " dict1[x['name']]['功能'] = list1\n", " \n", "\n", "filename = './file/穴位主治功能统计.json'\n", "with open(filename,'w') as fl:\n", " json.dump(dict1, fl) \n", "\n" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "### 穴位数据导出Excel表" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "import openpyxl\n", "\n", "filename = 'file/穴位.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "filename = 'file/穴位简要情况表.xlsx'\n", "wb = openpyxl.Workbook()\n", "sheet = wb.active\n", "sheet['A1'] = '穴位名称'\n", "sheet['B1'] = '隶属'\n", "sheet['C1'] = '位置'\n", "sheet['D1'] = '主治'\n", "sheet['E1'] = '功能'\n", "sheet['F1'] = '操作'\n", "sheet['G1'] = '主要配伍'\n", "i = 2\n", "for k, v in dict1.items():\n", " sheet[f'A{i}'] = k\n", " sheet[f'B{i}'] = v['简介'][0].split(':')[1]\n", " sheet[f'C{i}'] = v['简介'][1].split(':')[1]\n", " sheet[f'D{i}'] = v['简介'][2].split(':')[1]\n", " sheet[f'E{i}'] = v['简介'][3].split(':')[1]\n", " sheet[f'F{i}'] = v['简介'][4].split(':')[1]\n", " sheet[f'G{i}'] = v['简介'][5].split(':')[1] \n", " i += 1\n", "wb.save(filename) \n", "print('ok!')\n", "\n", "\n" ] }, { "cell_type": "markdown", "metadata": { "jp-MarkdownHeadingCollapsed": true, "tags": [] }, "source": [ "### 术语数据处理" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "import re\n", "import pymongo\n", "\n", "myclient = pymongo.MongoClient('mongodb://10.147.17.6:27017/')\n", "mydb = myclient['dayi']\n", "mycol = mydb[\"shuyu\"]\n", "dict1 = {}\n", "list1 = []\n", "for x in mycol.find({},{ \"_id\": 0,\"name\":1,\"about\":1 }):\n", " if '类别' in x['about'].keys():\n", " m_lb = x['about']['类别'].replace(' ','')\n", " else:\n", " m_lb = '无类别'\n", " dict1.setdefault(re.sub('\\xa0+','',m_lb),[])\n", " dict1[m_lb].append(x['name'])\n", "filename = './file/术语类别.json'\n", "with open(filename,'w') as fl:\n", " json.dump(dict1, fl) \n" ] }, { "cell_type": "markdown", "metadata": { "jp-MarkdownHeadingCollapsed": true, "tags": [] }, "source": [ "### 疾病数据处理" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "import re\n", "import pymongo\n", "\n", "myclient = pymongo.MongoClient('mongodb://10.147.17.6:27017/')\n", "mydb = myclient['dayi']\n", "mycol = mydb[\"jibing\"]\n", "dict1 = {}\n", "list1 = []\n", "for x in mycol.find({},{ \"_id\": 0,\"name\":1,\"about\":1 }):\n", " if '疾病分类' in x['about'].keys():\n", " m_lb = x['about']['疾病分类'].replace(' ','')\n", " else:\n", " m_lb = '无类别'\n", " dict1.setdefault(re.sub('\\xa0+','',m_lb),[])\n", " dict1[m_lb].append(x['name'])\n", "filename = './file/疾病类别.json'\n", "with open(filename,'w') as fl:\n", " json.dump(dict1, fl) " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 中草药数据处理" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "import re\n", "import pymongo\n", "\n", "myclient = pymongo.MongoClient('mongodb://10.147.17.6:27017/')\n", "mydb = myclient['dayi']\n", "mycol = mydb[\"zhongcaoyao\"]\n", "\n", "dict1 = {}\n", "mo = '等$'\n", "mo2 = r'[，、；。]'\n", "\n", "for x in mycol.find({},{ \"_id\": 0,\"name\":1,\"about\":1 }):\n", " dict1.setdefault(x['name'],{})\n", " if '别名' in x['about'].keys():\n", " #dict1[x['name']].setdefault('主治',[])\n", " s = x['about']['别名']\n", " s1 = re.sub(mo, '', s)\n", " list1 = re.split(mo2,s1)\n", " if '' in list1:\n", " list1.remove('')\n", " dict1[x['name']]['别名'] = list1\n", " if '功能' in x['about'].keys():\n", " #dict1[x['name']].setdefault('主治',[])\n", " s = x['about']['功能']\n", " s1 = re.sub(mo, '', s)\n", " list1 = re.split(mo2,s1)\n", " if '' in list1:\n", " list1.remove('')\n", " dict1[x['name']]['功能'] = list1\n", " if '主治' in x['about'].keys():\n", " #dict1[x['name']].setdefault('主治',[])\n", " dict1[x['name']]['主治'] = s = x['about']['主治']\n", " \n", "\n", "filename = './file/中草药主治功能统计.json'\n", "with open(filename,'w') as fl:\n", " json.dump(dict1, fl) " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 药剂数据处理" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "import re\n", "import pymongo\n", "\n", "myclient = pymongo.MongoClient('mongodb://10.147.17.6:27017/')\n", "mydb = myclient['dayi']\n", "mycol = mydb[\"yaoji\"]\n", "\n", "dict1 = {}\n", "mo = '等$'\n", "mo2 = r'[，、；。]'\n", "\n", "for x in mycol.find({},{ \"_id\": 0,\"name\":1,\"about\":1 }):\n", " dict1.setdefault(x['name'],{})\n", " if '功用' in x['about'].keys():\n", " #dict1[x['name']].setdefault('主治',[])\n", " s = x['about']['功用']\n", " s1 = re.sub(mo, '', s)\n", " list1 = re.split(mo2,s1)\n", " if '' in list1:\n", " list1.remove('')\n", " dict1[x['name']]['功用'] = list1\n", " if '主治' in x['about'].keys():\n", " #dict1[x['name']].setdefault('主治',[])\n", " dict1[x['name']]['主治'] = s = x['about']['主治']\n", " \n", "\n", "filename = './file/药剂主治功用统计.json'\n", "with open(filename,'w') as fl:\n", " json.dump(dict1, fl) " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 药膳数据处理" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "import re\n", "import pymongo\n", "\n", "myclient = pymongo.MongoClient('mongodb://10.147.17.6:27017/')\n", "mydb = myclient['dayi']\n", "mycol = mydb[\"yaoshan\"]\n", "\n", "dict1 = {}\n", "mo = '等$'\n", "mo2 = r'[，、；。]'\n", "\n", "for x in mycol.find({},{ \"_id\": 0,\"name\":1,\"about\":1 }):\n", " dict1.setdefault(x['name'],{})\n", " if '功效' in x['about'].keys():\n", " #dict1[x['name']].setdefault('主治',[])\n", " s = x['about']['功效']\n", " s1 = re.sub(mo, '', s)\n", " list1 = re.split(mo2,s1)\n", " if '' in list1:\n", " list1.remove('')\n", " dict1[x['name']]['功效'] = list1\n", " if '相关疾病' in x['about'].keys():\n", " #dict1[x['name']].setdefault('主治',[])\n", " s = x['about']['相关疾病']\n", " s1 = re.sub(mo, '', s)\n", " list1 = re.split(mo2,s1)\n", " if '' in list1:\n", " list1.remove('')\n", " dict1[x['name']]['相关疾病'] = list1 \n", " \n", "\n", "filename = './file/药膳功能统计.json'\n", "with open(filename,'w') as fl:\n", " json.dump(dict1, fl) " ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "### 北海炼化体检数据提取" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "import openpyxl\n", "import os,sys,shutil\n", "\n", "file_name = 'file/中石化北海炼化2020年团体体检报告.xlsx'\n", "wb = openpyxl.load_workbook(file_name)\n", "sheet = wb.active\n", "dict1 = {}\n", "for n in range(1,sheet.max_row+1):\n", " bh = sheet.cell(n,2).value\n", " name = sheet.cell(n,3).value\n", " xb = sheet.cell(n,4).value\n", " nl = sheet.cell(n,5).value\n", " bz = sheet.cell(n,7).value\n", " dict1.setdefault(bh,{})\n", " dict1[bh]['姓名'] = name\n", " dict1[bh]['性别'] = xb\n", " dict1[bh]['年龄'] = nl\n", " dict1[bh].setdefault('病症',[])\n", " dict1[bh]['病症'].append(bz.strip())\n", "wb.close()\n", "#print(dict1)\n", " \n", " \n", "filename = 'file/中石化北海炼化2020年体检人员情况表.xlsx'\n", "wb = openpyxl.Workbook()\n", "sheet = wb.active\n", "sheet['A1'] = '体检编号'\n", "sheet['B1'] = '姓名'\n", "sheet['C1'] = '性别'\n", "sheet['D1'] = '年龄'\n", "sheet['E1'] = '异常名称'\n", "\n", "i =2\n", "for k, v in dict1.items():\n", " sheet[f'A{i}'] = k\n", " sheet[f'B{i}'] = v['姓名']\n", " sheet[f'C{i}'] = v['性别']\n", " sheet[f'D{i}'] = v['年龄']\n", " sheet[f'E{i}'] = ','.join(v['病症']) \n", " i += 1\n", "wb.save(filename)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## excel数据读取" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "import openpyxl\n", "import json\n", "\n", "filename = 'data/长岭全成绩.xlsx'\n", "wb = openpyxl.load_workbook(filename)\n", "sheet = wb.active\n", "data1 =list(sheet.values)\n", "del data1[0]\n", "print(data1)\n", "#for data in data1:\n", "# print(data)\n", "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 图表生成" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 高考一分一段表生成" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "from pyecharts.globals import CurrentConfig, NotebookType\n", "CurrentConfig.NOTEBOOK_TYPE = NotebookType.JUPYTER_LAB\n", "from pyecharts import options as opts\n", "from pyecharts.charts import Bar,Line\n", "import pyecharts.options as opts\n", "from pyecharts.faker import Faker\n", "import json\n", "\n", "list_x = []\n", "list_y = []\n", "filename = 'data/17-21年一分一段表.json'\n", "with open(filename,'r') as fl:\n", " m_xx = json.load(fl)\n", "dict1 =m_xx['2020']['z']\n", "for i in sorted(dict1,reverse=True): #降序\n", " list_x.append(i)\n", " list_y.append(dict1[i]['num_person'])\n", " #print(i,dict1[i]['num_person'])\n", "bar = (\n", " Bar()\n", " .add_xaxis(list_x)\n", " .add_yaxis(\"2020年一分一段表\", list_y, category_gap=0, color=Faker.rand_color())\n", " .set_series_opts(label_opts=opts.LabelOpts(is_show=False))\n", " .set_global_opts(title_opts=opts.TitleOpts(title=\"Bar-直方图\"))\n", " .render(\"bar_histogram2020.html\")\n", "# .set_global_opts(title_opts=opts.TitleOpts(title=\"运动步幅及步频\", subtitle=\"户外运动\"),)\n", ")\n", "#bar.load_javascript()" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "bar.render_notebook()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "from pyecharts.globals import CurrentConfig, NotebookType\n", "CurrentConfig.NOTEBOOK_TYPE = NotebookType.JUPYTER_LAB\n", "from pyecharts import options as opts\n", "from pyecharts.charts import Bar,Line\n", "import pyecharts.options as opts\n", "from pyecharts.faker import Faker\n", "import json\n", "\n", "x_2021 = []\n", "y_2021 = []\n", "x_2020 = []\n", "y_2020 = []\n", "filename = 'data/17-21年一分一段表.json'\n", "with open(filename,'r') as fl:\n", " m_xx = json.load(fl)\n", "dict1 =m_xx['2021']['z']\n", "for i in sorted(dict1,reverse=True): #降序\n", " x_2021.append(i)\n", " y_2021.append(dict1[i]['num_person'])\n", "dict1 =m_xx['2020']['z']\n", "for i in sorted(dict1,reverse=True): #降序\n", " x_2021.append(i)\n", " y_2021.append(dict1[i]['num_person'])\n", " #print(i,dict1[i]['num_person'])\n", "bar = (\n", " Bar()\n", " .add_xaxis(list_x)\n", " .add_yaxis(\"人数\", list_y, category_gap=0, color=Faker.rand_color())\n", " .set_series_opts(label_opts=opts.LabelOpts(is_show=False))\n", " .set_global_opts(title_opts=opts.TitleOpts(title=\"Bar-直方图\"))\n", " .render(\"bar_histogram.html\")\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 生成雷达图" ] }, { "cell_type": "code", "execution_count": 18, "metadata": { "execution": { "iopub.execute_input": "2023-10-08T02:00:19.557430Z", "iopub.status.busy": "2023-10-08T02:00:19.556961Z", "iopub.status.idle": "2023-10-08T02:00:19.571800Z", "shell.execute_reply": "2023-10-08T02:00:19.571393Z", "shell.execute_reply.started": "2023-10-08T02:00:19.557394Z" }, "tags": [] }, "outputs": [ { "data": { "application/javascript": [ "new Promise(function(resolve, reject) {\n", " var script = document.createElement(\"script\");\n", " script.onload = resolve;\n", " script.onerror = reject;\n", " script.src = \"https://assets.pyecharts.org/assets/v5/echarts.min.js\";\n", " document.head.appendChild(script);\n", "}).then(() => {\n", "\n", "});" ], "text/plain": [ "" ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from pyecharts.globals import CurrentConfig, NotebookType\n", "import pyecharts.options as opts\n", "CurrentConfig.NOTEBOOK_TYPE = NotebookType.JUPYTER_LAB\n", "from pyecharts.charts import Radar\n", "\n", "\n", "v1 = [[90, 100, 80, 76, 88, 95]]\n", "v2 = [[5000, 14000, 28000, 31000, 42000, 21000]]\n", "\n", "bar =(\n", " Radar(init_opts=opts.InitOpts())\n", " .add_schema(\n", " schema=[\n", " opts.RadarIndicatorItem(name=\"销售（sales）\", max_=100),\n", " opts.RadarIndicatorItem(name=\"管理（Administration）\", max_=100),\n", " opts.RadarIndicatorItem(name=\"信息技术（Information Technology）\", max_=100),\n", " opts.RadarIndicatorItem(name=\"客服（Customer Support）\", max_=100),\n", " opts.RadarIndicatorItem(name=\"研发（Development）\", max_=100),\n", " opts.RadarIndicatorItem(name=\"市场（Marketing）\", max_=100),\n", " ],\n", " splitarea_opt=opts.SplitAreaOpts(\n", " is_show=True, areastyle_opts=opts.AreaStyleOpts(opacity=1)\n", " ),\n", " textstyle_opts=opts.TextStyleOpts(color=\"#aaa\"),\n", " )\n", " .add(\n", " series_name=\"预算分配（Allocated Budget）\",\n", " data=v1,\n", " linestyle_opts=opts.LineStyleOpts(color=\"#CD0000\"),\n", " )\n", " \n", " .set_series_opts(label_opts=opts.LabelOpts(is_show=False))\n", " .set_global_opts(\n", " title_opts=opts.TitleOpts(title=\"基础雷达图\"), legend_opts=opts.LegendOpts()\n", " )\n", " #.render(\"basic_radar_chart.html\")\n", " \n", ")\n", "bar.load_javascript()" ] }, { "cell_type": "code", "execution_count": 19, "metadata": { "execution": { "iopub.execute_input": "2023-10-08T02:00:22.378306Z", "iopub.status.busy": "2023-10-08T02:00:22.377831Z", "iopub.status.idle": "2023-10-08T02:00:22.387577Z", "shell.execute_reply": "2023-10-08T02:00:22.386538Z", "shell.execute_reply.started": "2023-10-08T02:00:22.378268Z" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", " \n", "\n", "\n", "
\n", " \n", "\n", "\n" ], "text/plain": [ "" ] }, "execution_count": 19, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bar.render_notebook()" ] }, { "cell_type": "code", "execution_count": 21, "metadata": { "execution": { "iopub.execute_input": "2023-10-08T02:09:05.895554Z", "iopub.status.busy": "2023-10-08T02:09:05.895353Z", "iopub.status.idle": "2023-10-08T02:09:06.036187Z", "shell.execute_reply": "2023-10-08T02:09:06.035511Z", "shell.execute_reply.started": "2023-10-08T02:09:05.895538Z" }, "tags": [] }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "No phantomjs found in your PATH. Please install it!\n" ] }, { "ename": "AttributeError", "evalue": "'tuple' object has no attribute 'tb_frame'", "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mFileNotFoundError\u001b[0m Traceback (most recent call last)", "File \u001b[0;32m~/data/lib/python3.10/site-packages/snapshot_phantomjs/snapshot.py:44\u001b[0m, in \u001b[0;36mchk_phantomjs\u001b[0;34m()\u001b[0m\n\u001b[1;32m 43\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m---> 44\u001b[0m phantomjs_version \u001b[38;5;241m=\u001b[39m \u001b[43msubprocess\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcheck_output\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 45\u001b[0m \u001b[43m \u001b[49m\u001b[43m[\u001b[49m\u001b[43mPHANTOMJS_EXEC\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m--version\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mshell\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mget_shell_flag\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 46\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 47\u001b[0m phantomjs_version \u001b[38;5;241m=\u001b[39m phantomjs_version\u001b[38;5;241m.\u001b[39mdecode(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mutf-8\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n", "File \u001b[0;32m/usr/lib/python3.10/subprocess.py:421\u001b[0m, in \u001b[0;36mcheck_output\u001b[0;34m(timeout, *popenargs, **kwargs)\u001b[0m\n\u001b[1;32m 419\u001b[0m kwargs[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124minput\u001b[39m\u001b[38;5;124m'\u001b[39m] \u001b[38;5;241m=\u001b[39m empty\n\u001b[0;32m--> 421\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mrun\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mpopenargs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mstdout\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mPIPE\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtimeout\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtimeout\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcheck\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m 422\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241m.\u001b[39mstdout\n", "File \u001b[0;32m/usr/lib/python3.10/subprocess.py:503\u001b[0m, in \u001b[0;36mrun\u001b[0;34m(input, capture_output, timeout, check, *popenargs, **kwargs)\u001b[0m\n\u001b[1;32m 501\u001b[0m kwargs[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mstderr\u001b[39m\u001b[38;5;124m'\u001b[39m] \u001b[38;5;241m=\u001b[39m PIPE\n\u001b[0;32m--> 503\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m \u001b[43mPopen\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mpopenargs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;28;01mas\u001b[39;00m process:\n\u001b[1;32m 504\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n", "File \u001b[0;32m/usr/lib/python3.10/subprocess.py:971\u001b[0m, in \u001b[0;36mPopen.__init__\u001b[0;34m(self, args, bufsize, executable, stdin, stdout, stderr, preexec_fn, close_fds, shell, cwd, env, universal_newlines, startupinfo, creationflags, restore_signals, start_new_session, pass_fds, user, group, extra_groups, encoding, errors, text, umask, pipesize)\u001b[0m\n\u001b[1;32m 968\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mstderr \u001b[38;5;241m=\u001b[39m io\u001b[38;5;241m.\u001b[39mTextIOWrapper(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mstderr,\n\u001b[1;32m 969\u001b[0m encoding\u001b[38;5;241m=\u001b[39mencoding, errors\u001b[38;5;241m=\u001b[39merrors)\n\u001b[0;32m--> 971\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_execute_child\u001b[49m\u001b[43m(\u001b[49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mexecutable\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpreexec_fn\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mclose_fds\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 972\u001b[0m \u001b[43m \u001b[49m\u001b[43mpass_fds\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcwd\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43menv\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 973\u001b[0m \u001b[43m \u001b[49m\u001b[43mstartupinfo\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcreationflags\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mshell\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 974\u001b[0m \u001b[43m \u001b[49m\u001b[43mp2cread\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mp2cwrite\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 975\u001b[0m \u001b[43m \u001b[49m\u001b[43mc2pread\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mc2pwrite\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 976\u001b[0m \u001b[43m \u001b[49m\u001b[43merrread\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43merrwrite\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 977\u001b[0m \u001b[43m \u001b[49m\u001b[43mrestore_signals\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 978\u001b[0m \u001b[43m \u001b[49m\u001b[43mgid\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mgids\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43muid\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mumask\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 979\u001b[0m \u001b[43m \u001b[49m\u001b[43mstart_new_session\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 980\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m:\n\u001b[1;32m 981\u001b[0m \u001b[38;5;66;03m# Cleanup if the child failed starting.\u001b[39;00m\n", "File \u001b[0;32m/usr/lib/python3.10/subprocess.py:1863\u001b[0m, in \u001b[0;36mPopen._execute_child\u001b[0;34m(self, args, executable, preexec_fn, close_fds, pass_fds, cwd, env, startupinfo, creationflags, shell, p2cread, p2cwrite, c2pread, c2pwrite, errread, errwrite, restore_signals, gid, gids, uid, umask, start_new_session)\u001b[0m\n\u001b[1;32m 1862\u001b[0m err_msg \u001b[38;5;241m=\u001b[39m os\u001b[38;5;241m.\u001b[39mstrerror(errno_num)\n\u001b[0;32m-> 1863\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m child_exception_type(errno_num, err_msg, err_filename)\n\u001b[1;32m 1864\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m child_exception_type(err_msg)\n", "\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: 'phantomjs'", "\nDuring handling of the above exception, another exception occurred:\n", "\u001b[0;31mSystemExit\u001b[0m Traceback (most recent call last)", " \u001b[0;31m[... skipping hidden 1 frame]\u001b[0m\n", "Cell \u001b[0;32mIn[21], line 41\u001b[0m\n\u001b[1;32m 12\u001b[0m bar \u001b[38;5;241m=\u001b[39m(\n\u001b[1;32m 13\u001b[0m Radar(init_opts\u001b[38;5;241m=\u001b[39mopts\u001b[38;5;241m.\u001b[39mInitOpts())\n\u001b[1;32m 14\u001b[0m \u001b[38;5;241m.\u001b[39madd_schema(\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 39\u001b[0m \n\u001b[1;32m 40\u001b[0m )\n\u001b[0;32m---> 41\u001b[0m \u001b[43mmake_snapshot\u001b[49m\u001b[43m(\u001b[49m\u001b[43msnapshot\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbar\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrender\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mbar0.png\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n", "File \u001b[0;32m~/data/lib/python3.10/site-packages/pyecharts/render/snapshot.py:32\u001b[0m, in \u001b[0;36mmake_snapshot\u001b[0;34m(engine, file_name, output_name, delay, pixel_ratio, is_remove_html, **kwargs)\u001b[0m\n\u001b[1;32m 30\u001b[0m file_type \u001b[38;5;241m=\u001b[39m output_name\u001b[38;5;241m.\u001b[39msplit(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m.\u001b[39m\u001b[38;5;124m\"\u001b[39m)[\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m]\n\u001b[0;32m---> 32\u001b[0m content \u001b[38;5;241m=\u001b[39m \u001b[43mengine\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmake_snapshot\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 33\u001b[0m \u001b[43m \u001b[49m\u001b[43mhtml_path\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfile_name\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 34\u001b[0m \u001b[43m \u001b[49m\u001b[43mfile_type\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfile_type\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 35\u001b[0m \u001b[43m \u001b[49m\u001b[43mdelay\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdelay\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 36\u001b[0m \u001b[43m \u001b[49m\u001b[43mpixel_ratio\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mpixel_ratio\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 37\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 38\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 39\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m file_type \u001b[38;5;129;01min\u001b[39;00m [SVG_FORMAT, B64_FORMAT]:\n", "File \u001b[0;32m~/data/lib/python3.10/site-packages/snapshot_phantomjs/snapshot.py:15\u001b[0m, in \u001b[0;36mmake_snapshot\u001b[0;34m(html_path, file_type, delay, pixel_ratio, **_)\u001b[0m\n\u001b[1;32m 12\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mmake_snapshot\u001b[39m(\n\u001b[1;32m 13\u001b[0m html_path: \u001b[38;5;28mstr\u001b[39m, file_type: \u001b[38;5;28mstr\u001b[39m, delay: \u001b[38;5;28mint\u001b[39m \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m2\u001b[39m, pixel_ratio: \u001b[38;5;28mint\u001b[39m \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m2\u001b[39m, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39m_\n\u001b[1;32m 14\u001b[0m ):\n\u001b[0;32m---> 15\u001b[0m \u001b[43mchk_phantomjs\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 16\u001b[0m logger\u001b[38;5;241m.\u001b[39minfo(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mGenerating file ...\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n", "File \u001b[0;32m~/data/lib/python3.10/site-packages/snapshot_phantomjs/snapshot.py:51\u001b[0m, in \u001b[0;36mchk_phantomjs\u001b[0;34m()\u001b[0m\n\u001b[1;32m 50\u001b[0m logger\u001b[38;5;241m.\u001b[39mwarning(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mNo phantomjs found in your PATH. Please install it!\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m---> 51\u001b[0m \u001b[43msys\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mexit\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m)\u001b[49m\n", "\u001b[0;31mSystemExit\u001b[0m: 1", "\nDuring handling of the above exception, another exception occurred:\n", "\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)", " \u001b[0;31m[... skipping hidden 1 frame]\u001b[0m\n", "File \u001b[0;32m~/data/lib/python3.10/site-packages/IPython/core/interactiveshell.py:2097\u001b[0m, in \u001b[0;36mInteractiveShell.showtraceback\u001b[0;34m(self, exc_tuple, filename, tb_offset, exception_only, running_compiled_code)\u001b[0m\n\u001b[1;32m 2094\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m exception_only:\n\u001b[1;32m 2095\u001b[0m stb \u001b[38;5;241m=\u001b[39m [\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mAn exception has occurred, use \u001b[39m\u001b[38;5;124m%\u001b[39m\u001b[38;5;124mtb to see \u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m 2096\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mthe full traceback.\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m'\u001b[39m]\n\u001b[0;32m-> 2097\u001b[0m stb\u001b[38;5;241m.\u001b[39mextend(\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mInteractiveTB\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_exception_only\u001b[49m\u001b[43m(\u001b[49m\u001b[43metype\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 2098\u001b[0m \u001b[43m \u001b[49m\u001b[43mvalue\u001b[49m\u001b[43m)\u001b[49m)\n\u001b[1;32m 2099\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 2101\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mcontains_exceptiongroup\u001b[39m(val):\n", "File \u001b[0;32m~/data/lib/python3.10/site-packages/IPython/core/ultratb.py:710\u001b[0m, in \u001b[0;36mListTB.get_exception_only\u001b[0;34m(self, etype, value)\u001b[0m\n\u001b[1;32m 702\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mget_exception_only\u001b[39m(\u001b[38;5;28mself\u001b[39m, etype, value):\n\u001b[1;32m 703\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"Only print the exception type and message, without a traceback.\u001b[39;00m\n\u001b[1;32m 704\u001b[0m \n\u001b[1;32m 705\u001b[0m \u001b[38;5;124;03m Parameters\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 708\u001b[0m \u001b[38;5;124;03m value : exception value\u001b[39;00m\n\u001b[1;32m 709\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[0;32m--> 710\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mListTB\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mstructured_traceback\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43metype\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mvalue\u001b[49m\u001b[43m)\u001b[49m\n", "File \u001b[0;32m~/data/lib/python3.10/site-packages/IPython/core/ultratb.py:568\u001b[0m, in \u001b[0;36mListTB.structured_traceback\u001b[0;34m(self, etype, evalue, etb, tb_offset, context)\u001b[0m\n\u001b[1;32m 565\u001b[0m chained_exc_ids\u001b[38;5;241m.\u001b[39madd(\u001b[38;5;28mid\u001b[39m(exception[\u001b[38;5;241m1\u001b[39m]))\n\u001b[1;32m 566\u001b[0m chained_exceptions_tb_offset \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m0\u001b[39m\n\u001b[1;32m 567\u001b[0m out_list \u001b[38;5;241m=\u001b[39m (\n\u001b[0;32m--> 568\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mstructured_traceback\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 569\u001b[0m \u001b[43m \u001b[49m\u001b[43metype\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 570\u001b[0m \u001b[43m \u001b[49m\u001b[43mevalue\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 571\u001b[0m \u001b[43m \u001b[49m\u001b[43m(\u001b[49m\u001b[43metb\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mchained_exc_ids\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;66;43;03m# type: ignore\u001b[39;49;00m\n\u001b[1;32m 572\u001b[0m \u001b[43m \u001b[49m\u001b[43mchained_exceptions_tb_offset\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 573\u001b[0m \u001b[43m \u001b[49m\u001b[43mcontext\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 574\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 575\u001b[0m \u001b[38;5;241m+\u001b[39m chained_exception_message\n\u001b[1;32m 576\u001b[0m \u001b[38;5;241m+\u001b[39m out_list)\n\u001b[1;32m 578\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m out_list\n", "File \u001b[0;32m~/data/lib/python3.10/site-packages/IPython/core/ultratb.py:1435\u001b[0m, in \u001b[0;36mAutoFormattedTB.structured_traceback\u001b[0;34m(self, etype, evalue, etb, tb_offset, number_of_lines_of_context)\u001b[0m\n\u001b[1;32m 1433\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 1434\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mtb \u001b[38;5;241m=\u001b[39m etb\n\u001b[0;32m-> 1435\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mFormattedTB\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mstructured_traceback\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 1436\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43metype\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mevalue\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43metb\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtb_offset\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mnumber_of_lines_of_context\u001b[49m\n\u001b[1;32m 1437\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n", "File \u001b[0;32m~/data/lib/python3.10/site-packages/IPython/core/ultratb.py:1326\u001b[0m, in \u001b[0;36mFormattedTB.structured_traceback\u001b[0;34m(self, etype, value, tb, tb_offset, number_of_lines_of_context)\u001b[0m\n\u001b[1;32m 1323\u001b[0m mode \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmode\n\u001b[1;32m 1324\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m mode \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mverbose_modes:\n\u001b[1;32m 1325\u001b[0m \u001b[38;5;66;03m# Verbose modes need a full traceback\u001b[39;00m\n\u001b[0;32m-> 1326\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mVerboseTB\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mstructured_traceback\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 1327\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43metype\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mvalue\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtb\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtb_offset\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mnumber_of_lines_of_context\u001b[49m\n\u001b[1;32m 1328\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1329\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m mode \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mMinimal\u001b[39m\u001b[38;5;124m'\u001b[39m:\n\u001b[1;32m 1330\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m ListTB\u001b[38;5;241m.\u001b[39mget_exception_only(\u001b[38;5;28mself\u001b[39m, etype, value)\n", "File \u001b[0;32m~/data/lib/python3.10/site-packages/IPython/core/ultratb.py:1173\u001b[0m, in \u001b[0;36mVerboseTB.structured_traceback\u001b[0;34m(self, etype, evalue, etb, tb_offset, number_of_lines_of_context)\u001b[0m\n\u001b[1;32m 1164\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mstructured_traceback\u001b[39m(\n\u001b[1;32m 1165\u001b[0m \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m 1166\u001b[0m etype: \u001b[38;5;28mtype\u001b[39m,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 1170\u001b[0m number_of_lines_of_context: \u001b[38;5;28mint\u001b[39m \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m5\u001b[39m,\n\u001b[1;32m 1171\u001b[0m ):\n\u001b[1;32m 1172\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"Return a nice text document describing the traceback.\"\"\"\u001b[39;00m\n\u001b[0;32m-> 1173\u001b[0m formatted_exception \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mformat_exception_as_a_whole\u001b[49m\u001b[43m(\u001b[49m\u001b[43metype\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mevalue\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43metb\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mnumber_of_lines_of_context\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1174\u001b[0m \u001b[43m \u001b[49m\u001b[43mtb_offset\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1176\u001b[0m colors \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mColors \u001b[38;5;66;03m# just a shorthand + quicker name lookup\u001b[39;00m\n\u001b[1;32m 1177\u001b[0m colorsnormal \u001b[38;5;241m=\u001b[39m colors\u001b[38;5;241m.\u001b[39mNormal \u001b[38;5;66;03m# used a lot\u001b[39;00m\n", "File \u001b[0;32m~/data/lib/python3.10/site-packages/IPython/core/ultratb.py:1063\u001b[0m, in \u001b[0;36mVerboseTB.format_exception_as_a_whole\u001b[0;34m(self, etype, evalue, etb, number_of_lines_of_context, tb_offset)\u001b[0m\n\u001b[1;32m 1060\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(tb_offset, \u001b[38;5;28mint\u001b[39m)\n\u001b[1;32m 1061\u001b[0m head \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mprepare_header(\u001b[38;5;28mstr\u001b[39m(etype), \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mlong_header)\n\u001b[1;32m 1062\u001b[0m records \u001b[38;5;241m=\u001b[39m (\n\u001b[0;32m-> 1063\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_records\u001b[49m\u001b[43m(\u001b[49m\u001b[43metb\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mnumber_of_lines_of_context\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtb_offset\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;28;01mif\u001b[39;00m etb \u001b[38;5;28;01melse\u001b[39;00m []\n\u001b[1;32m 1064\u001b[0m )\n\u001b[1;32m 1066\u001b[0m frames \u001b[38;5;241m=\u001b[39m []\n\u001b[1;32m 1067\u001b[0m skipped \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m0\u001b[39m\n", "File \u001b[0;32m~/data/lib/python3.10/site-packages/IPython/core/ultratb.py:1131\u001b[0m, in \u001b[0;36mVerboseTB.get_records\u001b[0;34m(self, etb, number_of_lines_of_context, tb_offset)\u001b[0m\n\u001b[1;32m 1129\u001b[0m \u001b[38;5;28;01mwhile\u001b[39;00m cf \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 1130\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m-> 1131\u001b[0m mod \u001b[38;5;241m=\u001b[39m inspect\u001b[38;5;241m.\u001b[39mgetmodule(\u001b[43mcf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtb_frame\u001b[49m)\n\u001b[1;32m 1132\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m mod \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 1133\u001b[0m mod_name \u001b[38;5;241m=\u001b[39m mod\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m\n", "\u001b[0;31mAttributeError\u001b[0m: 'tuple' object has no attribute 'tb_frame'" ] } ], "source": [ "from pyecharts.globals import CurrentConfig, NotebookType\n", "import pyecharts.options as opts\n", "CurrentConfig.NOTEBOOK_TYPE = NotebookType.JUPYTER_LAB\n", "from pyecharts.charts import Radar\n", "from pyecharts.render import make_snapshot\n", "from snapshot_phantomjs import snapshot\n", "\n", "\n", "v1 = [[90, 100, 80, 76, 88, 95]]\n", "v2 = [[5000, 14000, 28000, 31000, 42000, 21000]]\n", "\n", "bar =(\n", " Radar(init_opts=opts.InitOpts())\n", " .add_schema(\n", " schema=[\n", " opts.RadarIndicatorItem(name=\"销售（sales）\", max_=100),\n", " opts.RadarIndicatorItem(name=\"管理（Administration）\", max_=100),\n", " opts.RadarIndicatorItem(name=\"信息技术（Information Technology）\", max_=100),\n", " opts.RadarIndicatorItem(name=\"客服（Customer Support）\", max_=100),\n", " opts.RadarIndicatorItem(name=\"研发（Development）\", max_=100),\n", " opts.RadarIndicatorItem(name=\"市场（Marketing）\", max_=100),\n", " ],\n", " splitarea_opt=opts.SplitAreaOpts(\n", " is_show=True, areastyle_opts=opts.AreaStyleOpts(opacity=1)\n", " ),\n", " textstyle_opts=opts.TextStyleOpts(color=\"#aaa\"),\n", " )\n", " .add(\n", " series_name=\"预算分配（Allocated Budget）\",\n", " data=v1,\n", " linestyle_opts=opts.LineStyleOpts(color=\"#CD0000\"),\n", " )\n", " \n", " .set_series_opts(label_opts=opts.LabelOpts(is_show=False))\n", " .set_global_opts(\n", " title_opts=opts.TitleOpts(title=\"基础雷达图\"), legend_opts=opts.LegendOpts()\n", " )\n", " #.render(\"basic_radar_chart.html\")\n", " \n", ")\n", "make_snapshot(snapshot, bar.render(), \"bar0.png\")" ] }, { "cell_type": "code", "execution_count": 27, "metadata": { "execution": { "iopub.execute_input": "2023-10-08T02:30:58.347196Z", "iopub.status.busy": "2023-10-08T02:30:58.346801Z", "iopub.status.idle": "2023-10-08T02:30:58.438868Z", "shell.execute_reply": "2023-10-08T02:30:58.438412Z", "shell.execute_reply.started": "2023-10-08T02:30:58.347165Z" }, "tags": [] }, "outputs": [], "source": [ "import pygal \n", "\n", "radar_chart = pygal.Radar()\n", "radar_chart.title = 'V8 benchmark results'\n", "radar_chart.x_labels = ['Richards', 'DeltaBlue', 'Crypto', 'RayTrace', 'EarleyBoyer', 'RegExp', 'Splay', 'NavierStokes']\n", "radar_chart.add('Chrome', [6395, 8212, 7520, 7218, 12464, 1660, 2123, 8607])\n", "\n", "radar_chart.render_to_png('chart.png')" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.10.12" } }, "nbformat": 4, "nbformat_minor": 4 }