20230214

体测单位/天津石化.ipynb

@@ -1344,10 +1344,104 @@
     "print('ok!')"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "42e4ef5b-9aa8-4098-8f33-df9787dd34ab",
+   "metadata": {},
+   "source": [
+    "#### 倒班时间因素分析"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "255b5649-fb85-424d-9fad-0f3e1dff2be3",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-02-14T14:30:30.331426Z",
+     "iopub.status.busy": "2023-02-14T14:30:30.330830Z",
+     "iopub.status.idle": "2023-02-14T14:30:30.441098Z",
+     "shell.execute_reply": "2023-02-14T14:30:30.440041Z",
+     "shell.execute_reply.started": "2023-02-14T14:30:30.331376Z"
+    },
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{2: {'num': 571, 'score': 1619.279999999999, 'zhongyi': 55, 'pianpo': 44}, 3: {'num': 665, 'score': 1730.73, 'zhongyi': 76, 'pianpo': 62}, 1: {'num': 129, 'score': 358.9600000000001, 'zhongyi': 23, 'pianpo': 19}, 0: {'num': 706, 'score': 1963.300000000001, 'zhongyi': 70, 'pianpo': 32}, 4: {'num': 81, 'score': 194.23999999999992, 'zhongyi': 17, 'pianpo': 14}}\n",
+      "ok!\n"
+     ]
+    }
+   ],
+   "source": [
+    "import json\n",
+    "import openpyxl\n",
+    "\n",
+    "filename = 'data/天津石化人员231113_1.json'\n",
+    "with open(filename,'r') as fl:\n",
+    "    dict1 = json.load(fl)\n",
+    "unit = set()\n",
+    "\n",
+    "for k, v in dict1.items():\n",
+    "    unit.add(dict1[k]['unit'])\n",
+    "#print(unit)\n",
+    "dict2 = {}\n",
+    "for k, v in dict1.items():\n",
+    "    if v['daoban'] == '是':\n",
+    "        \n",
+    "        gld = int(int(v['gl'])/10)\n",
+    "        dict2.setdefault(gld,{})    \n",
+    "        dict2[gld].setdefault('num',0)\n",
+    "        dict2[gld].setdefault('score',0)\n",
+    "        dict2[gld].setdefault('zhongyi',0)\n",
+    "        dict2[gld].setdefault('pianpo',0) \n",
+    "        if 'avg' in v.keys():\n",
+    "            dict2[gld]['num'] = dict2[gld]['num'] + 1\n",
+    "            dict2[gld]['score'] = dict2[gld]['score'] + v['avg']\n",
+    "        if 'zhongyi' in v.keys() :\n",
+    "            dict2[gld]['zhongyi'] = dict2[gld]['zhongyi'] + 1\n",
+    "        if 'zhongyi' in v.keys()  and v['zhongyi']!='平和':\n",
+    "            dict2[gld]['pianpo'] = dict2[gld]['pianpo'] + 1\n",
+    "print(dict2)\n",
+    "nl = {}\n",
+    "nl[0] = '倒班工龄0-9年'\n",
+    "nl[1] = '倒班工龄10-19年'\n",
+    "nl[2] = '倒班工龄20-29年'\n",
+    "nl[3] = '倒班工龄30-39年'\n",
+    "nl[4] = '倒班工龄40-49年'\n",
+    "list1 = []        \n",
+    "for k, v in nl.items():\n",
+    "    list2 = []\n",
+    "    gld = v\n",
+    "    \n",
+    "    num = dict2[k]['num']\n",
+    "    score = dict2[k]['score']\n",
+    "    if num > 0:\n",
+    "        avg = round(score/num,2)\n",
+    "    else:\n",
+    "        avg = 0\n",
+    "    zhongyi = dict2[k]['zhongyi']\n",
+    "    pianpo = dict2[k]['pianpo']\n",
+    "    list2 = [gld,num,avg,zhongyi,pianpo]\n",
+    "    list1.append(list2)\n",
+    "filename = 'data/天津倒班因素分析表（倒班工龄）.xlsx'    \n",
+    "wb = openpyxl.Workbook()\n",
+    "sheet = wb.active\n",
+    "\n",
+    "for row in list1:\n",
+    "    sheet.append(row)\n",
+    "    \n",
+    "wb.save(filename)\n",
+    "print('ok!')"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "93ae7587-e49d-41c2-bd57-f89b9eed37e4",
+   "id": "683297cb-709a-40e1-a07f-59cf2cf8655b",
    "metadata": {},
    "outputs": [],
    "source": []