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512song committed 2023-11-14 10:49:31 +00:00
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commit 2185fd37aa
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体测单位/北海炼化.ipynb
+110 -17
View File
@@ -650,7 +650,6 @@
"cell_type": "markdown", "cell_type": "markdown",
"id": "1ab2aa22-5cc2-4f53-a28d-b30b1ecab15f", "id": "1ab2aa22-5cc2-4f53-a28d-b30b1ecab15f",
"metadata": { "metadata": {
"jp-MarkdownHeadingCollapsed": true,
"tags": [] "tags": []
}, },
"source": [ "source": [
@@ -1109,15 +1108,15 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 104, "execution_count": 106,
"id": "0bafbf66-c909-413e-a9c1-c1a5f9c22953", "id": "0bafbf66-c909-413e-a9c1-c1a5f9c22953",
"metadata": { "metadata": {
"execution": { "execution": {
"iopub.execute_input": "2023-11-08T01:55:15.141433Z", "iopub.execute_input": "2023-11-14T05:55:33.805333Z",
"iopub.status.busy": "2023-11-08T01:55:15.141150Z", "iopub.status.busy": "2023-11-14T05:55:33.804539Z",
"iopub.status.idle": "2023-11-08T01:55:15.238893Z", "iopub.status.idle": "2023-11-14T05:55:33.957265Z",
"shell.execute_reply": "2023-11-08T01:55:15.238339Z", "shell.execute_reply": "2023-11-14T05:55:33.956626Z",
"shell.execute_reply.started": "2023-11-08T01:55:15.141408Z" "shell.execute_reply.started": "2023-11-14T05:55:33.805258Z"
}, },
"tags": [] "tags": []
}, },
@@ -1220,15 +1219,15 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 17, "execution_count": 107,
"id": "1aa45b35-7376-4c50-8275-79b090a6c758", "id": "1aa45b35-7376-4c50-8275-79b090a6c758",
"metadata": { "metadata": {
"execution": { "execution": {
"iopub.execute_input": "2023-11-11T02:58:46.399097Z", "iopub.execute_input": "2023-11-14T06:00:16.626017Z",
"iopub.status.busy": "2023-11-11T02:58:46.398632Z", "iopub.status.busy": "2023-11-14T06:00:16.625735Z",
"iopub.status.idle": "2023-11-11T02:58:46.503284Z", "iopub.status.idle": "2023-11-14T06:00:16.685336Z",
"shell.execute_reply": "2023-11-11T02:58:46.502753Z", "shell.execute_reply": "2023-11-14T06:00:16.684762Z",
"shell.execute_reply.started": "2023-11-11T02:58:46.399061Z" "shell.execute_reply.started": "2023-11-14T06:00:16.625993Z"
}, },
"tags": [] "tags": []
}, },
@@ -1237,8 +1236,8 @@
"name": "stdout", "name": "stdout",
"output_type": "stream", "output_type": "stream",
"text": [ "text": [
"607\n", "697\n",
"607\n" "697\n"
] ]
} }
], ],
@@ -1261,7 +1260,7 @@
"with open(filename,'r') as fl:\n", "with open(filename,'r') as fl:\n",
" dict1 = json.load(fl) \n", " dict1 = json.load(fl) \n",
"\n", "\n",
"filename = 'data/places_result_20231111.csv'\n", "filename = 'data/places_result_20231114.csv'\n",
"with open(filename,'r',newline='') as csv_file:\n", "with open(filename,'r',newline='') as csv_file:\n",
" fl = csv.reader(csv_file,delimiter=',')\n", " fl = csv.reader(csv_file,delimiter=',')\n",
" header = next(fl) \n", " header = next(fl) \n",
@@ -1344,10 +1343,104 @@
"wb.save(filename)" "wb.save(filename)"
] ]
}, },
{
"cell_type": "markdown",
"id": "c410f403-5c93-4a03-a06b-900ecd08a1b4",
"metadata": {},
"source": [
"## 导入问卷信息"
]
},
{
"cell_type": "code",
"execution_count": 113,
"id": "63d5bccf-7351-4a08-863d-b1ca3b263eca",
"metadata": {
"execution": {
"iopub.execute_input": "2023-11-14T06:14:23.732763Z",
"iopub.status.busy": "2023-11-14T06:14:23.732454Z",
"iopub.status.idle": "2023-11-14T06:14:23.789472Z",
"shell.execute_reply": "2023-11-14T06:14:23.788550Z",
"shell.execute_reply.started": "2023-11-14T06:14:23.732734Z"
},
"tags": []
},
"outputs": [
{
"ename": "ValueError",
"evalue": "invalid literal for int() with base 10: 'ender'",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)",
"Cell \u001b[0;32mIn[113], line 38\u001b[0m\n\u001b[1;32m 36\u001b[0m list2\u001b[38;5;241m.\u001b[39mappend(\u001b[38;5;241m0\u001b[39m)\n\u001b[1;32m 37\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m k, v \u001b[38;5;129;01min\u001b[39;00m content\u001b[38;5;241m.\u001b[39mitems():\n\u001b[0;32m---> 38\u001b[0m i \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mint\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mk\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 39\u001b[0m list2[i\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m] \u001b[38;5;241m=\u001b[39m v\n\u001b[1;32m 40\u001b[0m dict2[item[\u001b[38;5;241m2\u001b[39m]] \u001b[38;5;241m=\u001b[39m list2\n",
"\u001b[0;31mValueError\u001b[0m: invalid literal for int() with base 10: 'ender'"
]
}
],
"source": [
"import json\n",
"import csv\n",
"import openpyxl\n",
"import time\n",
"from datetime import date\n",
"\n",
"filename = 'data/result_北海炼化2023.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl) \n",
"\n",
"filename = 'data/北海炼化2023年.json'\n",
"with open(filename,'r') as fl:\n",
" dict3 = json.load(fl)\n",
"\n",
"phone = set()\n",
"phone1 = set()\n",
"for k,v in dict3.items():\n",
" if 'phone' in v.keys():\n",
" phone.add(v['phone'])\n",
"list1 = []\n",
"filename = 'data/Survey_20231114.csv'\n",
"with open(filename,'r',newline='') as csv_file:\n",
" fl = csv.reader(csv_file,delimiter=',')\n",
" header = next(fl) \n",
" for line in fl:\n",
" #line = re.sub('[\\r\\n\\f ]{1,}', '', line)\n",
" list1.append(line)\n",
"dict2 = {}\n",
"m_rq = '2023-11-14'\n",
"rq= date.fromisoformat(m_rq.replace('/','-'))\n",
"for item in list1:\n",
" if item[2] in phone: \n",
" content = json.loads(item[5])\n",
" list2 = []\n",
" for i in range(0,60):\n",
" list2.append(0)\n",
" for k, v in content.items():\n",
" i = int(k[1:])\n",
" list2[i-1] = v\n",
" dict2[item[2]] = list2\n",
"print(dict2) \n",
"for k, v in dict3.items():\n",
" if 'phone' in v.keys() and v['phone'] in dict2.keys():\n",
" if k not in dict1.keys():\n",
" dict1.setdefault(k,{})\n",
" dict1[k] = dict3[k]\n",
" days = (rq-birth).days \n",
" dict1[k]['age'] = int(days/365)\n",
" dict1[k]['month'] = int(days/365*12)\n",
" \n",
" dict1[k]['tcm'] = dict2[str(v['phone'])]\n",
" \n",
"filename = 'data/result_北海炼化new.json'\n",
"\n",
"with open(filename,'w') as fl:\n",
" json.dump(dict1, fl, ensure_ascii=False) "
]
},
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": null,
"id": "7111dc19-387c-4e4d-bfed-0273cf0809fb", "id": "c0128f52-8697-4258-aba0-89a522fb9cc0",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [] "source": []
体测单位/天津石化.ipynb
+228 -24
View File
@@ -2308,7 +2308,7 @@
"for fn in fls:\n", "for fn in fls:\n",
" fi_name =Path(fn).stem.split('-')[0]\n", " fi_name =Path(fn).stem.split('-')[0]\n",
" code = int(fi_name)\n", " code = int(fi_name)\n",
" if dict1[str(code)]['sex'] =='女': \n", " if dict1[str(code)]['sex'] =='男': \n",
" unit_path = Path(new_path,dict1[str(code)]['unit'])\n", " unit_path = Path(new_path,dict1[str(code)]['unit'])\n",
" unit_path.mkdir(parents = True, exist_ok = True)\n", " unit_path.mkdir(parents = True, exist_ok = True)\n",
" n_name = Path(unit_path,Path(fn).stem+'.pdf')\n", " n_name = Path(unit_path,Path(fn).stem+'.pdf')\n",
@@ -2369,12 +2369,28 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": 92,
"id": "91fbc553-da7c-4c1e-bcf3-944dc59204b6", "id": "91fbc553-da7c-4c1e-bcf3-944dc59204b6",
"metadata": { "metadata": {
"execution": {
"iopub.execute_input": "2023-11-14T06:24:29.017502Z",
"iopub.status.busy": "2023-11-14T06:24:29.016683Z",
"iopub.status.idle": "2023-11-14T06:24:29.082247Z",
"shell.execute_reply": "2023-11-14T06:24:29.081478Z",
"shell.execute_reply.started": "2023-11-14T06:24:29.017425Z"
},
"tags": [] "tags": []
}, },
"outputs": [], "outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[]\n",
"ok\n"
]
}
],
"source": [ "source": [
"import os,sys,shutil\n", "import os,sys,shutil\n",
"import json\n", "import json\n",
@@ -2393,13 +2409,13 @@
" list2 = []\n", " list2 = []\n",
" fi_name =Path(fn).stem.split('-')[0] \n", " fi_name =Path(fn).stem.split('-')[0] \n",
" code = int(fi_name)\n", " code = int(fi_name)\n",
" if dict1[str(code)]['sex'] =='女':\n", " if dict1[str(code)]['sex'] =='男':\n",
" unit = dict1[str(code)]['unit']\n", " unit = dict1[str(code)]['unit']\n",
" list2 = [fi_name,Path(fn).stem.split('-')[1],unit]\n", " list2 = [fi_name,Path(fn).stem.split('-')[1],unit]\n",
" \n", " \n",
" list1.append(list2)\n", " list1.append(list2)\n",
"print(list1)\n", "print(list1)\n",
"filename = 'data/天津石化体测报告打印明细表(修改).xlsx'\n", "filename = 'data/天津石化体测报告打印明细表(第一批).xlsx'\n",
"wb = openpyxl.Workbook()\n", "wb = openpyxl.Workbook()\n",
"sheet = wb.active\n", "sheet = wb.active\n",
"sheet.append(title)\n", "sheet.append(title)\n",
@@ -2631,18 +2647,37 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": 87,
"id": "006afc6c-2b1f-4edf-be1b-5f60e2029ee8", "id": "006afc6c-2b1f-4edf-be1b-5f60e2029ee8",
"metadata": { "metadata": {
"execution": {
"iopub.execute_input": "2023-11-14T05:31:33.869705Z",
"iopub.status.busy": "2023-11-14T05:31:33.869187Z",
"iopub.status.idle": "2023-11-14T05:31:33.963951Z",
"shell.execute_reply": "2023-11-14T05:31:33.963038Z",
"shell.execute_reply.started": "2023-11-14T05:31:33.869655Z"
},
"tags": [] "tags": []
}, },
"outputs": [], "outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0~255分人数：1641人,男性：1334人,女性:307人\n",
"256~332分人数：1544人,男性：941人,女性:603人\n",
"333~367分人数：354人,男性：191人,女性:163人\n",
"368~500分人数：118人,男性：39人,女性:79人\n",
"3657\n"
]
}
],
"source": [ "source": [
"import json\n", "import json\n",
"\n", "\n",
"items = ['体重','肺活量','握力','坐位体前屈','纵跳','俯卧撑','一分钟仰卧起坐','单脚站立','选择反应时','台阶指数']\n", "items = ['体重','肺活量','握力','坐位体前屈','纵跳','俯卧撑','一分钟仰卧起坐','单脚站立','选择反应时','台阶指数']\n",
"\n", "\n",
"filename = 'data/data_天津231017.json'\n", "filename = 'data/data_天津231017_非倒班.json'\n",
"with open(filename,'r') as fl:\n", "with open(filename,'r') as fl:\n",
" dict1 = json.load(fl) \n", " dict1 = json.load(fl) \n",
"dict2 = {}\n", "dict2 = {}\n",
@@ -2679,12 +2714,34 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": 88,
"id": "949e4c3c-023d-44a4-b99e-c5460da61161", "id": "949e4c3c-023d-44a4-b99e-c5460da61161",
"metadata": { "metadata": {
"execution": {
"iopub.execute_input": "2023-11-14T05:32:00.827469Z",
"iopub.status.busy": "2023-11-14T05:32:00.826734Z",
"iopub.status.idle": "2023-11-14T05:32:00.923421Z",
"shell.execute_reply": "2023-11-14T05:32:00.922591Z",
"shell.execute_reply.started": "2023-11-14T05:32:00.827429Z"
},
"tags": [] "tags": []
}, },
"outputs": [], "outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"20~24岁平均成绩：2.45分，人数：581人,男性：384人\n",
"25~29岁平均成绩：2.56分，人数：369人,男性：252人\n",
"30~34岁平均成绩：2.56分，人数：211人,男性：144人\n",
"35~39岁平均成绩：2.67分，人数：414人,男性：281人\n",
"40~44岁平均成绩：2.7分，人数：318人,男性：188人\n",
"45~49岁平均成绩：2.71分，人数：563人,男性：310人\n",
"50~54岁平均成绩：2.63分，人数：849人,男性：594人\n",
"55~69岁平均成绩：2.46分，人数：352人,男性：352人\n"
]
}
],
"source": [ "source": [
"nld = [[20,24],[25,29],[30,34],[35,39],[40,44],[45,49],[50,54],[55,69]]\n", "nld = [[20,24],[25,29],[30,34],[35,39],[40,44],[45,49],[50,54],[55,69]]\n",
"\n", "\n",
@@ -2717,12 +2774,34 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": 86,
"id": "721977d3-5816-4bf6-82fc-26fd170e5454", "id": "721977d3-5816-4bf6-82fc-26fd170e5454",
"metadata": { "metadata": {
"execution": {
"iopub.execute_input": "2023-11-14T05:29:45.231085Z",
"iopub.status.busy": "2023-11-14T05:29:45.230706Z",
"iopub.status.idle": "2023-11-14T05:29:45.291777Z",
"shell.execute_reply": "2023-11-14T05:29:45.290397Z",
"shell.execute_reply.started": "2023-11-14T05:29:45.231052Z"
},
"tags": [] "tags": []
}, },
"outputs": [], "outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"20~24岁平均成绩：2.42分，人数：322人\n",
"25~29岁平均成绩：2.54分，人数：120人\n",
"30~34岁平均成绩：2.61分，人数：21人\n",
"35~39岁平均成绩：2.23分，人数：47人\n",
"40~44岁平均成绩：2.46分，人数：57人\n",
"45~49岁平均成绩：2.4分，人数：156人\n",
"50~54岁平均成绩：2.39分，人数：335人\n",
"55~80岁平均成绩：2.5分，人数：225人\n"
]
}
],
"source": [ "source": [
"import json\n", "import json\n",
"\n", "\n",
@@ -2795,12 +2874,29 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": 90,
"id": "7155f2c2-0719-4558-aa3b-629fb70194d6", "id": "7155f2c2-0719-4558-aa3b-629fb70194d6",
"metadata": { "metadata": {
"execution": {
"iopub.execute_input": "2023-11-14T05:32:38.731026Z",
"iopub.status.busy": "2023-11-14T05:32:38.730664Z",
"iopub.status.idle": "2023-11-14T05:32:38.802327Z",
"shell.execute_reply": "2023-11-14T05:32:38.801563Z",
"shell.execute_reply.started": "2023-11-14T05:32:38.730994Z"
},
"tags": [] "tags": []
}, },
"outputs": [], "outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"平均成绩：2.4823分，男性：2505人\n",
"平均成绩：2.8604分，女性：1152人\n",
"平均成绩：2.6014分，总体：3657人\n"
]
}
],
"source": [ "source": [
"import json\n", "import json\n",
"\n", "\n",
@@ -2826,7 +2922,7 @@
" score = score+v['score']\n", " score = score+v['score']\n",
"print(f'平均成绩：{round(score/f,4)}分，女性：{f}人')\n", "print(f'平均成绩：{round(score/f,4)}分，女性：{f}人')\n",
"t_score = t_score + score\n", "t_score = t_score + score\n",
"print(f'平均成绩：{round(t_score/5383,4)}分，总体：5383人')" "print(f'平均成绩：{round(t_score/3657,4)}分，总体：3657人')"
] ]
}, },
{ {
@@ -2925,6 +3021,60 @@
"print('ok')" "print('ok')"
] ]
}, },
{
"cell_type": "markdown",
"id": "194217e0-f1cf-4945-ad5a-52304ed2f943",
"metadata": {},
"source": [
"## 计算各项目成绩"
]
},
{
"cell_type": "code",
"execution_count": 91,
"id": "5ed284c6-1a1c-43ab-92a8-b3c411cd77a1",
"metadata": {
"execution": {
"iopub.execute_input": "2023-11-14T05:34:30.789468Z",
"iopub.status.busy": "2023-11-14T05:34:30.789112Z",
"iopub.status.idle": "2023-11-14T05:34:30.903912Z",
"shell.execute_reply": "2023-11-14T05:34:30.903118Z",
"shell.execute_reply.started": "2023-11-14T05:34:30.789436Z"
},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"BMI 3.54 3634\n",
"肺活量 3.37 3569\n",
"握力 1.29 3592\n",
"坐位体前屈 2.85 3142\n",
"纵跳 2.0 3198\n",
"俯卧撑 2.57 2082\n",
"一分钟仰卧起坐 3.94 757\n",
"单脚站立 2.01 3523\n",
"选择反应时 2.97 3613\n",
"台阶指数 2.58 1496\n"
]
}
],
"source": [
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl) \n",
"items = ['BMI','肺活量','握力','坐位体前屈','纵跳','俯卧撑','一分钟仰卧起坐','单脚站立','选择反应时','台阶指数']\n",
"for item in items:\n",
" score = 0\n",
" n = 0\n",
" for k, v in dict1.items(): \n",
" if item in v['fits'].keys():\n",
" n = n + 1\n",
" score =score + int(v['fits'][item]['score'])\n",
" print(item,round(score/n,2),n)"
]
},
{ {
"cell_type": "markdown", "cell_type": "markdown",
"id": "5a130857-4dd1-4b5e-b21b-42fe32b367cf", "id": "5a130857-4dd1-4b5e-b21b-42fe32b367cf",
@@ -3101,15 +3251,15 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 253, "execution_count": 80,
"id": "518a1e40-d383-4d78-a4ea-224ddab49b79", "id": "518a1e40-d383-4d78-a4ea-224ddab49b79",
"metadata": { "metadata": {
"execution": { "execution": {
"iopub.execute_input": "2023-11-10T13:59:53.477003Z", "iopub.execute_input": "2023-11-14T04:54:34.744376Z",
"iopub.status.busy": "2023-11-10T13:59:53.476599Z", "iopub.status.busy": "2023-11-14T04:54:34.744069Z",
"iopub.status.idle": "2023-11-10T13:59:54.275449Z", "iopub.status.idle": "2023-11-14T04:54:36.013106Z",
"shell.execute_reply": "2023-11-10T13:59:54.274890Z", "shell.execute_reply": "2023-11-14T04:54:36.012373Z",
"shell.execute_reply.started": "2023-11-10T13:59:53.476972Z" "shell.execute_reply.started": "2023-11-14T04:54:34.744349Z"
}, },
"tags": [] "tags": []
}, },
@@ -3118,7 +3268,7 @@
"name": "stdout", "name": "stdout",
"output_type": "stream", "output_type": "stream",
"text": [ "text": [
"1726\n" "3657\n"
] ]
} }
], ],
@@ -3137,19 +3287,73 @@
"# sheets = wb.sheetnames\n", "# sheets = wb.sheetnames\n",
"dict2 = {}\n", "dict2 = {}\n",
"i = 1\n", "i = 1\n",
"for n in range(2, sheet.max_row+1):\n", "for n in range(4, sheet.max_row+1):\n",
" if sheet.cell(n, 1).value is not None:\n", " if sheet.cell(n, 1).value is not None:\n",
" code = int(sheet.cell(n, 1).value)\n", " code = int(sheet.cell(n, 1).value)\n",
" daoban = sheet.cell(n, 6).value\n", " daoban = sheet.cell(n, 6).value\n",
" if str(code) in dict1.keys() and daoban == '倒班':\n", " if str(code) in dict1.keys() and daoban == '倒班':\n",
" dict2[str(code)] = dict1[str(code)]\n", " dict2[str(code)] = dict1[str(code)]\n",
"print(len(dict2))" "filename = 'data/data_天津231017_倒班.json'\n",
"with open(filename,'w') as fl:\n",
" json.dump(dict2, fl) \n",
"dict3 = {}\n",
"for k, v in dict1.items():\n",
" if k not in dict2.keys():\n",
" dict3[k] = dict1[k]\n",
"print(len(dict3))\n",
" \n",
"filename = 'data/data_天津231017_非倒班.json'\n",
"with open(filename,'w') as fl:\n",
" json.dump(dict3, fl) \n"
]
},
{
"cell_type": "markdown",
"id": "cf45ba36-896d-4d28-ae4a-08c512ff1ddb",
"metadata": {},
"source": [
"### 核对倒班员工信息"
] ]
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": null,
"id": "08167b05-8719-41c9-a71d-57906a55eb63", "id": "08167b05-8719-41c9-a71d-57906a55eb63",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"import json\n",
"import openpyxl\n",
"\n",
"\n",
"filename = 'data/data_天津231017.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
"\n",
" \n",
"wb = openpyxl.load_workbook('data/员工个人基础信息-倒班.xlsx')\n",
"sheet = wb.active\n",
"# sheets = wb.sheetnames\n",
"dict2 = {}\n",
"i = 0\n",
"for n in range(4, sheet.max_row+1):\n",
" if sheet.cell(n, 1).value is not None:\n",
" code = int(sheet.cell(n, 1).value)\n",
" daoban = sheet.cell(n, 6).value\n",
" if str(code) in dict1.keys():# and daoban != '倒班':\n",
" dict2[str(code)] = dict1[str(code)]\n",
"for k,v in dict1.items():\n",
" if str(k) not in dict2.keys():\n",
" i+=1\n",
" print(i,k,v['name'])"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "54b2abad-9891-4e06-93b7-ca5c0659ea49",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [] "source": []