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512song committed 2023-11-29 20:16:24 +08:00
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体测单位/天津石化.ipynb
+488 -192
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@@ -4,8 +4,8 @@
"cell_type": "markdown",
"id": "e764be85-0ddf-4055-abd6-de2990e75db8",
"metadata": {
"jp-MarkdownHeadingCollapsed": true,
"tags": []
"tags": [],
"toc-hr-collapsed": true
},
"source": [
"# 第一次体测"
@@ -2369,28 +2369,12 @@
},
{
"cell_type": "code",
"execution_count": 92,
"execution_count": null,
"id": "91fbc553-da7c-4c1e-bcf3-944dc59204b6",
"metadata": {
"execution": {
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},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[]\n",
"ok\n"
]
}
],
"outputs": [],
"source": [
"import os,sys,shutil\n",
"import json\n",
@@ -2550,28 +2534,12 @@
},
{
"cell_type": "code",
"execution_count": 279,
"execution_count": null,
"id": "35d1738a-1ec1-4764-bcbd-c1333fac6bfd",
"metadata": {
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"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['12167', 'ptv_022_sh', '', '边晓睿', '3145586', '{\"gender\":\"f\",\"psy1\":4,\"psy2\":4,\"psy3\":4,\"psy4\":4,\"psy5\":4,\"psy6\":4,\"psy7\":3,\"psy8\":4,\"psy9\":4,\"psy10\":4,\"psy11\":4,\"psy12\":3,\"psy13\":3,\"psy14\":2,\"psy15\":4,\"psy16\":3,\"psy17\":4,\"psy18\":3,\"psy19\":4,\"psy20\":4,\"psy21\":4,\"psy22\":4,\"psy23\":4,\"psy24\":4,\"psy25\":4,\"psy26\":4,\"psy27\":0,\"psy28\":0,\"psy29\":0,\"psy30\":1,\"psy31\":1,\"psy32\":0,\"psy33\":1,\"psy34\":0,\"psy35\":1,\"psy36\":1,\"psy37\":1,\"psy38\":0,\"psy39\":0,\"psy40\":0,\"psy41\":5,\"psy42\":5,\"psy43\":5,\"psy44\":5,\"tcm1\":1,\"tcm2\":4,\"tcm3\":3,\"tcm4\":2,\"tcm5\":3,\"tcm6\":4,\"tcm7\":2,\"tcm8\":5,\"tcm9\":2,\"tcm10\":2,\"tcm11\":4,\"tcm12\":1,\"tcm13\":4,\"tcm14\":1,\"tcm15\":5,\"tcm16\":2,\"tcm17\":1,\"tcm18\":4,\"tcm19\":3,\"tcm20\":1,\"tcm21\":1,\"tcm22\":3,\"tcm23\":1,\"tcm24\":4,\"tcm25\":2,\"tcm26\":5,\"tcm27\":3,\"tcm28\":5,\"tcm29\":4,\"tcm30\":2,\"tcm31\":5,\"tcm32\":1,\"tcm33\":1,\"tcm34\":1,\"tcm35\":1,\"tcm36\":5,\"tcm37\":3,\"tcm38\":2,\"tcm39\":5,\"tcm40\":2,\"tcm41\":1,\"tcm42\":3,\"tcm43\":1,\"tcm44\":3,\"tcm45\":1,\"tcm46\":5,\"tcm47\":5,\"tcm48\":2,\"tcm49\":2,\"tcm50\":3,\"tcm51\":2,\"tcm52\":2,\"tcm53\":1,\"tcm54\":3,\"tcm55\":2,\"tcm56\":2,\"tcm57\":2,\"tcm58\":1,\"tcm59\":1,\"tcm60\":3,\"spine1\":1,\"spine2\":1,\"spine3\":2,\"spine4\":1,\"spine5\":2,\"spine6\":2,\"spine7\":2,\"spine8\":2,\"spine9\":1,\"spine10\":2,\"spine11\":1,\"spine12\":2,\"spine13\":2,\"spine14\":2,\"spine15\":1,\"spine16\":1,\"spine17\":2,\"spine18\":2,\"spine19\":2,\"spine20\":2,\"spine21\":1,\"spine23\":2,\"spine24\":1,\"spine25\":2,\"spine26\":2}', '2023-11-13 14:25:18']\n",
"['12168', 'ptv_022_sh', '', '孙海红', '1733738', '{\"gender\":\"f\",\"psy1\":3,\"psy2\":3,\"psy3\":2,\"psy4\":3,\"psy5\":3,\"psy6\":4,\"psy7\":3,\"psy8\":3,\"psy9\":4,\"psy10\":3,\"psy11\":4,\"psy12\":4,\"psy13\":3,\"psy14\":3,\"psy15\":3,\"psy16\":4,\"psy17\":4,\"psy18\":4,\"psy19\":4,\"psy20\":4,\"psy21\":3,\"psy22\":4,\"psy23\":4,\"psy24\":4,\"psy25\":4,\"psy26\":4,\"psy27\":0,\"psy28\":0,\"psy29\":0,\"psy30\":0,\"psy31\":0,\"psy32\":0,\"psy33\":1,\"psy34\":1,\"psy35\":0,\"psy36\":0,\"psy37\":0,\"psy38\":0,\"psy39\":0,\"psy40\":1,\"psy41\":4,\"psy42\":4,\"psy43\":4,\"psy44\":4,\"tcm1\":2,\"tcm2\":4,\"tcm3\":4,\"tcm4\":3,\"tcm5\":1,\"tcm6\":3,\"tcm7\":1,\"tcm8\":4,\"tcm9\":1,\"tcm10\":1,\"tcm11\":4,\"tcm12\":3,\"tcm13\":4,\"tcm14\":1,\"tcm15\":3,\"tcm16\":3,\"tcm17\":3,\"tcm18\":3,\"tcm19\":3,\"tcm20\":3,\"tcm21\":2,\"tcm22\":2,\"tcm23\":2,\"tcm24\":1,\"tcm25\":1,\"tcm26\":1,\"tcm27\":3,\"tcm28\":1,\"tcm29\":3,\"tcm30\":2,\"tcm31\":2,\"tcm32\":2,\"tcm33\":2,\"tcm34\":3,\"tcm35\":5,\"tcm36\":3,\"tcm37\":2,\"tcm38\":2,\"tcm39\":2,\"tcm40\":1,\"tcm41\":2,\"tcm42\":1,\"tcm43\":1,\"tcm44\":3,\"tcm45\":3,\"tcm46\":3,\"tcm47\":2,\"tcm49\":2,\"tcm50\":2,\"tcm48\":2,\"tcm51\":2,\"tcm52\":2,\"tcm53\":3,\"tcm54\":3,\"tcm55\":1,\"tcm56\":1,\"tcm57\":1,\"tcm58\":2,\"tcm59\":1,\"tcm60\":5,\"spine1\":2,\"spine2\":1,\"spine3\":1,\"spine4\":1,\"spine5\":2,\"spine6\":2,\"spine7\":2,\"spine8\":2,\"spine9\":1,\"spine10\":2,\"spine11\":2,\"spine12\":2,\"spine13\":2,\"spine14\":2,\"spine15\":2,\"spine16\":2,\"spine17\":2,\"spine18\":2,\"spine19\":1,\"spine20\":2,\"spine21\":2,\"spine23\":2,\"spine24\":1,\"spine25\":1,\"spine26\":2}', '2023-11-13 14:32:18']\n"
]
}
],
"outputs": [],
"source": [
"import json\n",
"import csv\n",
@@ -2660,28 +2628,12 @@
},
{
"cell_type": "code",
"execution_count": 280,
"execution_count": null,
"id": "cc9e1717-f445-49a9-a770-c103da603434",
"metadata": {
"execution": {
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},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"3145586 边晓睿 {\"errmsg\":\"ok\"}\n",
"1733738 孙海红 {\"errmsg\":\"ok\"}\n"
]
}
],
"outputs": [],
"source": [
"import requests\n",
"import json\n",
@@ -2751,7 +2703,6 @@
"shell.execute_reply": "2023-10-25T02:50:57.004773Z",
"shell.execute_reply.started": "2023-10-25T02:50:56.997463Z"
},
"jp-MarkdownHeadingCollapsed": true,
"tags": []
},
"source": [
@@ -2848,31 +2799,12 @@
},
{
"cell_type": "code",
"execution_count": 87,
"execution_count": null,
"id": "006afc6c-2b1f-4edf-be1b-5f60e2029ee8",
"metadata": {
"execution": {
"iopub.execute_input": "2023-11-14T05:31:33.869705Z",
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"shell.execute_reply.started": "2023-11-14T05:31:33.869655Z"
},
"tags": []
},
"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"
]
}
],
"outputs": [],
"source": [
"import json\n",
"\n",
@@ -2915,34 +2847,12 @@
},
{
"cell_type": "code",
"execution_count": 88,
"execution_count": null,
"id": "949e4c3c-023d-44a4-b99e-c5460da61161",
"metadata": {
"execution": {
"iopub.execute_input": "2023-11-14T05:32:00.827469Z",
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"shell.execute_reply": "2023-11-14T05:32:00.922591Z",
"shell.execute_reply.started": "2023-11-14T05:32:00.827429Z"
},
"tags": []
},
"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"
]
}
],
"outputs": [],
"source": [
"nld = [[20,24],[25,29],[30,34],[35,39],[40,44],[45,49],[50,54],[55,69]]\n",
"\n",
@@ -2975,34 +2885,12 @@
},
{
"cell_type": "code",
"execution_count": 86,
"execution_count": null,
"id": "721977d3-5816-4bf6-82fc-26fd170e5454",
"metadata": {
"execution": {
"iopub.execute_input": "2023-11-14T05:29:45.231085Z",
"iopub.status.busy": "2023-11-14T05:29:45.230706Z",
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"shell.execute_reply": "2023-11-14T05:29:45.290397Z",
"shell.execute_reply.started": "2023-11-14T05:29:45.231052Z"
},
"tags": []
},
"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"
]
}
],
"outputs": [],
"source": [
"import json\n",
"\n",
@@ -3075,29 +2963,12 @@
},
{
"cell_type": "code",
"execution_count": 90,
"execution_count": null,
"id": "7155f2c2-0719-4558-aa3b-629fb70194d6",
"metadata": {
"execution": {
"iopub.execute_input": "2023-11-14T05:32:38.731026Z",
"iopub.status.busy": "2023-11-14T05:32:38.730664Z",
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"shell.execute_reply": "2023-11-14T05:32:38.801563Z",
"shell.execute_reply.started": "2023-11-14T05:32:38.730994Z"
},
"tags": []
},
"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"
]
}
],
"outputs": [],
"source": [
"import json\n",
"\n",
@@ -3232,36 +3103,12 @@
},
{
"cell_type": "code",
"execution_count": 91,
"execution_count": null,
"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"
]
}
],
"outputs": [],
"source": [
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl) \n",
@@ -3452,27 +3299,12 @@
},
{
"cell_type": "code",
"execution_count": 80,
"execution_count": null,
"id": "518a1e40-d383-4d78-a4ea-224ddab49b79",
"metadata": {
"execution": {
"iopub.execute_input": "2023-11-14T04:54:34.744376Z",
"iopub.status.busy": "2023-11-14T04:54:34.744069Z",
"iopub.status.idle": "2023-11-14T04:54:36.013106Z",
"shell.execute_reply": "2023-11-14T04:54:36.012373Z",
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},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"3657\n"
]
}
],
"outputs": [],
"source": [
"import json\n",
"import openpyxl\n",
@@ -3494,6 +3326,7 @@
" 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",
"print(len(dict2))\n",
"filename = 'data/data_天津231017_倒班.json'\n",
"with open(filename,'w') as fl:\n",
" json.dump(dict2, fl) \n",
@@ -3526,10 +3359,8 @@
"outputs": [],
"source": [
"import json\n",
"import openpyxl\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",
" dict1 = json.load(fl)\n",
"\n",
@@ -3551,10 +3382,475 @@
" print(i,k,v['name'])"
]
},
{
"cell_type": "markdown",
"id": "dc51915d-7593-411c-8730-4ee9445ebd51",
"metadata": {},
"source": [
"### 对比倒班及非倒班人员得分"
]
},
{
"cell_type": "code",
"execution_count": 312,
"id": "096bb641-c000-490b-bd77-296fb0395dc8",
"metadata": {
"execution": {
"iopub.execute_input": "2023-11-28T12:54:35.962454Z",
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"iopub.status.idle": "2023-11-28T12:54:36.084684Z",
"shell.execute_reply": "2023-11-28T12:54:36.084138Z",
"shell.execute_reply.started": "2023-11-28T12:54:35.962418Z"
},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"南港烯烃部 {'非倒班': [13882, 681, 5591], '倒班': [0, 0, 0]}\n",
"消防支队 {'非倒班': [1420, 72, 558], '倒班': [0, 0, 0]}\n",
"化工部 {'非倒班': [9833, 498, 3792], '倒班': [483, 24, 185]}\n",
"炼油部 {'非倒班': [12059, 548, 4459], '倒班': [13153, 643, 5046]}\n",
"电仪部 {'非倒班': [2162, 110, 885], '倒班': [4206, 212, 1744]}\n",
"物资采购中心 {'非倒班': [1736, 84, 643], '倒班': [0, 0, 0]}\n",
"化验计量部 {'非倒班': [3561, 185, 1368], '倒班': [5241, 284, 2065]}\n",
"运输销售部 {'非倒班': [3316, 188, 1341], '倒班': [203, 11, 78]}\n",
"原油储运部 {'非倒班': [2561, 125, 1002], '倒班': [949, 53, 397]}\n",
"公司机关 {'非倒班': [2364, 112, 883], '倒班': [0, 0, 0]}\n",
"南港乙烯项目管理部 {'非倒班': [325, 15, 124], '倒班': [0, 0, 0]}\n",
"党委党校（培训中心） {'非倒班': [1011, 48, 360], '倒班': [0, 0, 0]}\n",
"聚醚部 {'非倒班': [2036, 96, 744], '倒班': [263, 16, 118]}\n",
"装备研究院 {'非倒班': [1028, 48, 378], '倒班': [0, 0, 0]}\n",
"热电部 {'非倒班': [3849, 187, 1419], '倒班': [4409, 225, 1700]}\n",
"行政事务中心 {'非倒班': [851, 41, 322], '倒班': [0, 0, 0]}\n",
"烯烃部 {'非倒班': [3501, 165, 1268], '倒班': [3007, 155, 1182]}\n",
"水务部 {'非倒班': [5790, 293, 2196], '倒班': [1807, 103, 760]}\n",
"信息档案管理中心 {'非倒班': [1384, 60, 485], '倒班': [0, 0, 0]}\n",
"研究院 {'非倒班': [2225, 101, 788], '倒班': [0, 0, 0]}\n"
]
}
],
"source": [
"import json\n",
"\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",
"\n",
"filename = 'data/data_天津231017_非倒班.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
"\n",
"dict3 = {}\n",
"for k, v in dict1.items():\n",
" unit = v['unit']\n",
" dict3.setdefault(unit,{})\n",
" dict3[unit].setdefault('非倒班',[0,0,0])\n",
" dict3[unit].setdefault('倒班',[0,0,0])\n",
" for k1,v1 in v['fits'].items():\n",
" if k1 in items:\n",
" dict3[unit]['非倒班'][0] = dict3[unit]['非倒班'][0]+ v1['score']\n",
" dict3[unit]['非倒班'][2]+=1\n",
" dict3[unit]['非倒班'][1] +=1\n",
"filename = 'data/data_天津231017_倒班.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
"\n",
"for k, v in dict1.items():\n",
" unit = v['unit']\n",
" dict3.setdefault(unit,{})\n",
" dict3[unit].setdefault('非倒班',[0,0])\n",
" dict3[unit].setdefault('倒班',[0,0])\n",
" for k1,v1 in v['fits'].items():\n",
" if k1 in items:\n",
" dict3[unit]['倒班'][0] = dict3[unit]['倒班'][0]+ v1['score']\n",
" dict3[unit]['倒班'][2] +=1\n",
" dict3[unit]['倒班'][1] +=1\n",
"\n",
"for k ,v in dict3.items():\n",
" print(k,v)"
]
},
{
"cell_type": "markdown",
"id": "ce2c7879-308c-45aa-aaeb-2323b3a060be",
"metadata": {},
"source": [
"### 划分年龄段"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "54b2abad-9891-4e06-93b7-ca5c0659ea49",
"id": "c1b68d99-e8c1-455a-973f-20f4c1fd58a2",
"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",
"nld ={'20':[20,29],'30':[30,39],'40':[40,49],'50':[50,69]}\n",
"for k,v in nld.items():\n",
" age_min = v[0]\n",
" age_max = v[1]\n",
" for k1,v1 in dict1.items():\n",
" if v1['age'] >=v[0] and v1['age']<=v[1]:\n",
" dict1[k1]['nld'] = k\n",
"\n",
"filename = 'data/data_天津_nld.json' \n",
"with open(filename,'w') as fl:\n",
" json.dump(dict1, fl) \n",
" "
]
},
{
"cell_type": "markdown",
"id": "eb35716c-cd5a-476b-95d0-b326bfa04963",
"metadata": {},
"source": [
"### 上肢、下肢力量分析（男）"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "6a8cfab1-c99b-4376-9ad2-4ae096dd4866",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"import json\n",
"\n",
"filename = 'data/data_天津_nld.json' \n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
"\n",
"list1 = ['20','30','40','50']\n",
"shangzhi = ['握力','俯卧撑']\n",
"xiazhi = ['纵跳','闭眼单脚站立']\n",
"zongrenshu = 0\n",
"ruo = 0\n",
"for item in list1:\n",
" print(item)\n",
" renshu = 0\n",
" ruo = 0\n",
" \n",
" for k, v in dict1.items():\n",
" if v['nld'] == item and v['sex']=='男':\n",
" renshu+=1\n",
" n =0\n",
" defen = 0\n",
" for k1, v1 in v['fits'].items():\n",
" if k1 in xiazhi:\n",
" n+=1\n",
" defen =defen+v1['score']\n",
" if n>0 and (defen/n)<3:\n",
" ruo+=1\n",
" print(renshu,ruo)\n",
" \n",
" \n",
" \n",
" \n",
" \n",
" "
]
},
{
"cell_type": "markdown",
"id": "6f83db87-9844-41dc-bf43-789c3367f411",
"metadata": {},
"source": [
"### 上肢、下肢力量分析（女）"
]
},
{
"cell_type": "code",
"execution_count": 295,
"id": "2cb586f9-cdf1-4b51-8900-50416b5f0ae5",
"metadata": {
"execution": {
"iopub.execute_input": "2023-11-28T11:55:13.064209Z",
"iopub.status.busy": "2023-11-28T11:55:13.063792Z",
"iopub.status.idle": "2023-11-28T11:55:13.118894Z",
"shell.execute_reply": "2023-11-28T11:55:13.118359Z",
"shell.execute_reply.started": "2023-11-28T11:55:13.064179Z"
},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"20\n",
"506 301\n",
"30\n",
"222 97\n",
"40\n",
"583 305\n",
"50\n",
"284 169\n"
]
}
],
"source": [
"import json\n",
"\n",
"filename = 'data/data_天津_nld.json' \n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
"\n",
"list1 = ['20','30','40','50']\n",
"shangzhi = ['握力']\n",
"xiazhi = ['纵跳','闭眼单脚站立']\n",
"zongrenshu = 0\n",
"ruo = 0\n",
"for item in list1:\n",
" print(item)\n",
" renshu = 0\n",
" ruo = 0\n",
" \n",
" for k, v in dict1.items():\n",
" if v['nld'] == item and v['sex']=='女':\n",
" renshu+=1\n",
" n =0\n",
" defen = 0\n",
" for k1, v1 in v['fits'].items():\n",
" if k1 in xiazhi:\n",
" n+=1\n",
" defen =defen+v1['score']\n",
" if n>0 and (defen/n)<3:\n",
" ruo+=1\n",
" print(renshu,ruo)\n",
" "
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "dd822864-0226-40c1-b385-cd146f6972c9",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"import json\n",
"\n",
"filename = 'data/data_天津_nld.json' \n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
"\n",
"for k ,v in dict1.items():\n",
" if v['sex'] == '男' and '握力' in v['fits'].keys():\n",
" print(v['name'],v['nld'],v['fits']['握力']['mark'],v['fits']['握力']['score'])\n",
" "
]
},
{
"cell_type": "markdown",
"id": "1015b957-448a-4029-827f-3abc3c0e9173",
"metadata": {},
"source": [
"### 弱项分析（男）"
]
},
{
"cell_type": "code",
"execution_count": 302,
"id": "d3ea1ddb-db7a-4b4f-a23c-6951e88df2ff",
"metadata": {
"execution": {
"iopub.execute_input": "2023-11-28T12:15:45.478108Z",
"iopub.status.busy": "2023-11-28T12:15:45.477633Z",
"iopub.status.idle": "2023-11-28T12:15:45.604185Z",
"shell.execute_reply": "2023-11-28T12:15:45.603612Z",
"shell.execute_reply.started": "2023-11-28T12:15:45.478072Z"
},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"20\n",
"BMI 3.0\n",
"肺活量 3.65\n",
"握力 1.25\n",
"坐位体前屈 2.65\n",
"纵跳 2.29\n",
"俯卧撑 2.51\n",
"单脚站立 1.76\n",
"选择反应时 2.53\n",
"台阶指数 2.2\n",
"30\n",
"BMI 2.85\n",
"肺活量 3.44\n",
"握力 1.17\n",
"坐位体前屈 2.54\n",
"纵跳 2.57\n",
"俯卧撑 2.77\n",
"单脚站立 1.9\n",
"选择反应时 2.84\n",
"台阶指数 2.59\n",
"40\n",
"BMI 3.31\n",
"肺活量 3.13\n",
"握力 1.39\n",
"坐位体前屈 2.72\n",
"纵跳 1.83\n",
"俯卧撑 2.64\n",
"单脚站立 1.93\n",
"选择反应时 3.15\n",
"台阶指数 2.79\n",
"50\n",
"BMI 3.71\n",
"肺活量 2.99\n",
"握力 1.52\n",
"坐位体前屈 3.05\n",
"纵跳 1.18\n",
"俯卧撑 2.27\n",
"单脚站立 1.73\n",
"选择反应时 3.18\n",
"台阶指数 3.04\n"
]
}
],
"source": [
"import json\n",
"\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",
"\n",
"\n",
"filename = 'data/data_天津_nld.json' \n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
"\n",
"list1 = ['20','30','40','50']\n",
"\n",
"for nld in list1:\n",
" \n",
" print(nld)\n",
" for item in items:\n",
" n =0\n",
" defen = 0\n",
" for k, v in dict1.items():\n",
" \n",
" if v['nld'] == nld and v['sex']=='男' and item in v['fits'].keys():\n",
" n+=1\n",
" defen =defen+ v['fits'][item]['score']\n",
" if n>0:\n",
" print(item,round(defen/n,2)) "
]
},
{
"cell_type": "markdown",
"id": "727fda65-7268-44f5-b953-285c86602254",
"metadata": {},
"source": [
"### 弱项分析（女）"
]
},
{
"cell_type": "code",
"execution_count": 303,
"id": "723b50a1-60f1-4001-8b30-6f77c6a4b460",
"metadata": {
"execution": {
"iopub.execute_input": "2023-11-28T12:18:25.287183Z",
"iopub.status.busy": "2023-11-28T12:18:25.286772Z",
"iopub.status.idle": "2023-11-28T12:18:25.407362Z",
"shell.execute_reply": "2023-11-28T12:18:25.406892Z",
"shell.execute_reply.started": "2023-11-28T12:18:25.287153Z"
},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"20\n",
"BMI 3.82\n",
"肺活量 3.43\n",
"握力 1.38\n",
"坐位体前屈 3.08\n",
"纵跳 2.21\n",
"一分钟仰卧起坐 3.66\n",
"单脚站立 1.87\n",
"选择反应时 2.41\n",
"台阶指数 2.47\n",
"30\n",
"BMI 4.05\n",
"肺活量 3.57\n",
"握力 1.25\n",
"坐位体前屈 3.0\n",
"纵跳 2.62\n",
"一分钟仰卧起坐 4.18\n",
"单脚站立 2.22\n",
"选择反应时 2.96\n",
"台阶指数 2.92\n",
"40\n",
"BMI 4.18\n",
"肺活量 3.38\n",
"握力 1.37\n",
"坐位体前屈 3.0\n",
"纵跳 2.07\n",
"一分钟仰卧起坐 3.99\n",
"单脚站立 2.58\n",
"选择反应时 3.13\n",
"台阶指数 2.93\n",
"50\n",
"BMI 4.13\n",
"肺活量 3.22\n",
"握力 1.28\n",
"坐位体前屈 3.22\n",
"纵跳 1.48\n",
"一分钟仰卧起坐 3.71\n",
"单脚站立 2.79\n",
"选择反应时 3.4\n",
"台阶指数 3.71\n"
]
}
],
"source": [
"import json\n",
"\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",
"\n",
"\n",
"filename = 'data/data_天津_nld.json' \n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
"\n",
"list1 = ['20','30','40','50']\n",
"\n",
"for nld in list1:\n",
" \n",
" print(nld)\n",
" for item in items:\n",
" n =0\n",
" defen = 0\n",
" for k, v in dict1.items():\n",
" \n",
" if v['nld'] == nld and v['sex']=='女' and item in v['fits'].keys():\n",
" n+=1\n",
" defen =defen+ v['fits'][item]['score']\n",
" if n>0:\n",
" print(item,round(defen/n,2))"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "62278ae0-be57-4f7c-85d6-cfb9cf61e341",
"metadata": {},
"outputs": [],
"source": []