partReport.py 109 KB

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  1. import pandas as pd
  2. import numpy as np
  3. import time
  4. import os
  5. from docx.shared import Inches
  6. from docx.shared import Pt, RGBColor
  7. from docx import Document
  8. from docx.enum.table import WD_TABLE_ALIGNMENT, WD_CELL_VERTICAL_ALIGNMENT
  9. from docx.oxml.ns import qn
  10. from docx.enum.text import WD_ALIGN_PARAGRAPH
  11. from docx.enum.text import WD_PARAGRAPH_ALIGNMENT
  12. import report
  13. # 频度信息表生成
  14. def makeInfoTable(data, doc):
  15. rows = (int(len(data.columns) / 6) + 1)
  16. columnsList = np.arange(0, rows * 6, 6)
  17. dataList = []
  18. for i in columnsList:
  19. res = data.iloc[:, i:i + 6]
  20. res = res.reset_index()
  21. dataList.append(res)
  22. table_f_2 = doc.add_table(rows=rows * 6, cols=7, style='Light Shading Accent 1')
  23. for i, row in enumerate(table_f_2.rows):
  24. for j, cell in enumerate(row.cells):
  25. # 获取单元格中的段落对象
  26. paragraph = cell.paragraphs[0]
  27. if i == columnsList[0]:
  28. # 第一行 显示前6个指标的列名
  29. if len(dataList[0].columns) > j:
  30. r = paragraph.add_run(dataList[0].columns[j])
  31. r.font.bold = True
  32. r.font.size = Pt(10.5)
  33. r.font.name = 'Times New Roman'
  34. r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  35. else:
  36. paragraph.add_run('')
  37. elif len(columnsList) > 1 and i > columnsList[0] and i < columnsList[1]:
  38. if len(dataList[0].columns) > j:
  39. r = paragraph.add_run(str(dataList[0].iloc[i - 1, j]))
  40. r.font.size = Pt(10.5)
  41. r.font.name = 'Times New Roman'
  42. r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  43. else:
  44. paragraph.add_run('')
  45. elif i == columnsList[1]:
  46. # 第6行 显示前6个指 标的列名
  47. if len(dataList[1].columns) > j:
  48. r = paragraph.add_run(dataList[1].columns[j])
  49. r.font.bold = True
  50. r.font.size = Pt(10.5)
  51. r.font.name = 'Times New Roman'
  52. r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  53. else:
  54. paragraph.add_run('')
  55. elif len(columnsList) > 2 and i > columnsList[1] and i < columnsList[2]:
  56. if len(dataList[1].columns) > j:
  57. r = paragraph.add_run(str(dataList[1].iloc[i - 7, j]))
  58. r.font.size = Pt(10.5)
  59. r.font.name = 'Times New Roman'
  60. r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  61. else:
  62. paragraph.add_run('')
  63. elif i == columnsList[2]:
  64. # 第6*2行 显示前6个指 标的列名
  65. if len(dataList[2].columns) > j:
  66. r = paragraph.add_run(dataList[2].columns[j])
  67. r.font.bold = True
  68. r.font.size = Pt(10.5)
  69. r.font.name = 'Times New Roman'
  70. r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  71. else:
  72. paragraph.add_run('')
  73. elif len(columnsList) > 3 and i > columnsList[2] and i < columnsList[3]:
  74. if len(dataList[2].columns) > j:
  75. r = paragraph.add_run(str(dataList[2].iloc[i - 13, j]))
  76. r.font.size = Pt(10.5)
  77. r.font.name = 'Times New Roman'
  78. r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  79. else:
  80. paragraph.add_run('')
  81. elif i == columnsList[3]:
  82. # 第6*3行 显示前6个指 标的列名
  83. if len(dataList[3].columns) > j:
  84. r = paragraph.add_run(dataList[3].columns[j])
  85. r.font.bold = True
  86. r.font.size = Pt(10.5)
  87. r.font.name = 'Times New Roman'
  88. r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  89. else:
  90. paragraph.add_run('')
  91. elif len(columnsList) > 4 and i > columnsList[3] and i < columnsList[4]:
  92. if len(dataList[3].columns) > j:
  93. r = paragraph.add_run(str(dataList[3].iloc[i - 19, j]))
  94. r.font.size = Pt(10.5)
  95. r.font.name = 'Times New Roman'
  96. r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  97. else:
  98. paragraph.add_run('')
  99. elif i == columnsList[4]:
  100. # 第6*4行 显示前6个指 标的列名
  101. if len(dataList[4].columns) > j:
  102. r = paragraph.add_run(dataList[4].columns[j])
  103. r.font.bold = True
  104. r.font.size = Pt(10.5)
  105. r.font.name = 'Times New Roman'
  106. r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  107. else:
  108. paragraph.add_run('')
  109. elif len(columnsList) > 5 and i > columnsList[4] and i < columnsList[5]:
  110. if len(dataList[4].columns) > j:
  111. r = paragraph.add_run(str(dataList[4].iloc[i - 25, j]))
  112. r.font.size = Pt(10.5)
  113. r.font.name = 'Times New Roman'
  114. r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  115. else:
  116. paragraph.add_run('')
  117. elif i == columnsList[5]:
  118. # 第6*5行 显示前6个指 标的列名
  119. if len(dataList[5].columns) > j:
  120. r = paragraph.add_run(dataList[5].columns[j])
  121. r.font.bold = True
  122. r.font.size = Pt(10.5)
  123. r.font.name = 'Times New Roman'
  124. r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  125. else:
  126. paragraph.add_run('')
  127. elif len(columnsList) > 6 and i > columnsList[5] and i < columnsList[6]:
  128. if len(dataList[5].columns) > j:
  129. r = paragraph.add_run(str(dataList[5].iloc[i - 31, j]))
  130. r.font.size = Pt(10.5)
  131. r.font.name = 'Times New Roman'
  132. r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  133. else:
  134. paragraph.add_run('')
  135. elif i == columnsList[6]:
  136. # 第6*6行 显示前6个指 标的列名
  137. if len(dataList[6].columns) > j:
  138. r = paragraph.add_run(dataList[6].columns[j])
  139. r.font.bold = True
  140. r.font.size = Pt(10.5)
  141. r.font.name = 'Times New Roman'
  142. r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  143. else:
  144. paragraph.add_run('')
  145. elif len(columnsList) > 7 and i > columnsList[6] and i < columnsList[7]:
  146. if len(dataList[6].columns) > j:
  147. r = paragraph.add_run(str(dataList[6].iloc[i - 37, j]))
  148. r.font.size = Pt(10.5)
  149. r.font.name = 'Times New Roman'
  150. r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  151. else:
  152. paragraph.add_run('')
  153. elif i == columnsList[7]:
  154. # 第6*7行 显示前6个指 标的列名
  155. if len(dataList[7].columns) > j:
  156. r = paragraph.add_run(dataList[7].columns[j])
  157. r.font.bold = True
  158. r.font.size = Pt(10.5)
  159. r.font.name = 'Times New Roman'
  160. r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  161. else:
  162. paragraph.add_run('')
  163. elif len(columnsList) >= 8 and i > columnsList[7] and i < columnsList[8]:
  164. if len(dataList[7].columns) > j:
  165. r = paragraph.add_run(str(dataList[7].iloc[i - 43, j]))
  166. r.font.size = Pt(10.5)
  167. r.font.name = 'Times New Roman'
  168. r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  169. else:
  170. paragraph.add_run('')
  171. elif i == columnsList[8]:
  172. if len(dataList[8].columns) > j:
  173. # 第6*8行 显示前6个指 标的列名
  174. r = paragraph.add_run(dataList[8].columns[j])
  175. r.font.bold = True
  176. r.font.size = Pt(10.5)
  177. r.font.name = 'Times New Roman'
  178. r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  179. else:
  180. paragraph.add_run('')
  181. elif len(columnsList) >= 9 and i > columnsList[8] and i < columnsList[9]:
  182. if len(dataList[8].columns) > j:
  183. r = paragraph.add_run(str(dataList[8].iloc[i - 49, j]))
  184. r.font.size = Pt(10.5)
  185. r.font.name = 'Times New Roman'
  186. r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  187. else:
  188. paragraph.add_run('')
  189. elif i == columnsList[9]:
  190. # 第6*9行 显示前6个指 标的列名
  191. if len(dataList[9].columns) > j:
  192. r = paragraph.add_run(dataList[9].columns[j])
  193. r.font.bold = True
  194. r.font.size = Pt(10.5)
  195. r.font.name = 'Times New Roman'
  196. r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  197. else:
  198. paragraph.add_run('')
  199. elif len(columnsList) > 10 and i > columnsList[9] and i <columnsList[10]:
  200. if len(dataList[9].columns) > j:
  201. r = paragraph.add_run(str(dataList[9].iloc[i - 55, j]))
  202. r.font.size = Pt(10.5)
  203. r.font.name = 'Times New Roman'
  204. r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  205. else:
  206. paragraph.add_run('')
  207. elif i == columnsList[10]:
  208. # 第6*9行 显示前6个指 标的列名
  209. if len(dataList[10].columns) > j:
  210. r = paragraph.add_run(dataList[10].columns[j])
  211. r.font.bold = True
  212. r.font.size = Pt(10.5)
  213. r.font.name = 'Times New Roman'
  214. r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  215. else:
  216. paragraph.add_run('')
  217. elif len(columnsList) > 11 and i > columnsList[10] and i < columnsList[11]:
  218. if len(dataList[10].columns) > j:
  219. r = paragraph.add_run(str(dataList[10].iloc[i - 61, j]))
  220. r.font.size = Pt(10.5)
  221. r.font.name = 'Times New Roman'
  222. r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  223. else:
  224. paragraph.add_run('')
  225. elif i == columnsList[11]:
  226. # 第6*9行 显示前6个指 标的列名
  227. if len(dataList[11].columns) > j:
  228. r = paragraph.add_run(dataList[11].columns[j])
  229. r.font.bold = True
  230. r.font.size = Pt(10.5)
  231. r.font.name = 'Times New Roman'
  232. r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  233. else:
  234. paragraph.add_run('')
  235. elif len(columnsList) > 12 and i > columnsList[11] and i < columnsList[12]:
  236. if len(dataList[11].columns) > j:
  237. r = paragraph.add_run(str(dataList[11].iloc[i - 67, j]))
  238. r.font.size = Pt(10.5)
  239. r.font.name = 'Times New Roman'
  240. r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  241. else:
  242. paragraph.add_run('')
  243. elif i == columnsList[12]:
  244. print(i)
  245. # 第6*9行 显示前6个指 标的列名
  246. if len(dataList[12].columns) > j:
  247. r = paragraph.add_run(dataList[12].columns[j])
  248. r.font.bold = True
  249. r.font.size = Pt(10.5)
  250. r.font.name = 'Times New Roman'
  251. r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  252. else:
  253. paragraph.add_run('')
  254. elif len(columnsList) >= 13 and i > columnsList[12] and i <= 77:
  255. print('last---',i)
  256. if len(dataList[12].columns) > j:
  257. r = paragraph.add_run(str(dataList[12].iloc[i - 73, j]))
  258. r.font.size = Pt(10.5)
  259. r.font.name = 'Times New Roman'
  260. r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  261. else:
  262. paragraph.add_run('')
  263. paragraph.alignment = WD_PARAGRAPH_ALIGNMENT.CENTER
  264. paragraph.paragraph_format.alignment = WD_TABLE_ALIGNMENT.CENTER # 对齐
  265. paragraph.paragraph_format.line_spacing = 1 # 段落行间距
  266. # 生成子报告: 物理指标 常规养分指标 一般化学性指标 重金属指标
  267. indexClassificationList = {
  268. '物理指标': ['pH', '土壤质地', '土壤容重1(g/cm³)', '土壤容重2(g/cm³)', '土壤容重3(g/cm³)', '土壤容重4(g/cm³)', '土壤容重平均值(g/cm³)',
  269. '2~0.2mm颗粒含量', '0.2~0.02mm颗粒含量', '0.02~0.002mm颗粒含量', '0.002mm以下颗粒含量', '水稳>5mm(%)', '水稳3mm~5mm(%)',
  270. '水稳2mm~3mm(%)', '水稳1mm~2mm(%)', '水稳0.5mm~1mm(%)', '水稳0.25mm~0.5mm(%)', '水稳性大团聚体总和(%)', '洗失量(吸管法需填)', '风干试样含水量(分析基)'],
  271. '常规养分指标': ['pH','有机质', '全氮', '全磷', '全钾', '有效磷', '速效钾', '有效硫', '有效硼', '有效铁', '有效锰', '有效铜', '有效锌', '有效钼', '有效硅', '缓效钾'],
  272. '一般化学性指标': ['pH','阳离子交换量', '交换性盐基总量', '交换性钙', '交换性镁', '交换性钠', '交换性钾', '全盐量', '电导率',
  273. '水溶性Na⁺含量', '水溶性K⁺含量', '水溶性Ca²⁺含量', '水溶性Mg²⁺含量', '水溶性Cl⁻含量', '水溶性CO₃²⁻含量','水溶性HCO₃⁻含量',
  274. '水溶性SO₄²⁻含量', '离子总量', '碳酸钙'],
  275. '重金属指标': ['pH', '总汞', '总砷', '总铅', '总镉', '总铬', '总镍']
  276. }
  277. # 生成物理指标审核报告
  278. def getphysicsReport(data,type, changeFileUrl, saveFileUrl, check_1_data,
  279. check_3_data,
  280. check_5_data ,
  281. check_8_data, # 样品编号替换为编号
  282. check_10_data,
  283. check_12_data,
  284. check_14_data ):
  285. """
  286. :param type: 指标类型
  287. :param changeFileUrl: 选择的数据文件路径
  288. :param saveFileUrl: 保存的文件路径
  289. :param check_1_data: 土壤容重数据
  290. :param check_3_data: 水稳审核数据
  291. :param check_5_data: 盐离子数据
  292. :param check_8_data: 水溶性离子数据
  293. :param check_10_data: 有机质及氮磷钾数据
  294. :param check_12_data: 有效养分数据
  295. :param check_14_data: 重金属数据
  296. :return:
  297. """
  298. # 生成报告
  299. name = os.path.basename(changeFileUrl)
  300. n = name.split('.')
  301. areaName = n[0].replace('数据', '')
  302. # 生成一个新的文件夹用于存放审核报告相关的数据
  303. nowTime = time.strftime("%Y-%m-%d %H时%M分%S秒", time.localtime())
  304. dir_name = f'{areaName}-{type}数据审核报告'
  305. mkdir_path = saveFileUrl + '/' + dir_name + nowTime
  306. if not os.path.exists(mkdir_path):
  307. os.mkdir(mkdir_path)
  308. # 获取相应指标数据
  309. physicsData = data[indexClassificationList[type]]
  310. report.getFrequencyImage(physicsData, mkdir_path)
  311. physicsData['序号'] = data['序号']
  312. physicsData['原样品编号'] = data['原样品编号']
  313. physicsData['样品编号'] = data['样品编号']
  314. physicsData['地理位置'] = data['地理位置']
  315. physicsData['母质'] = data['母质']
  316. physicsData['土壤类型'] = data['土壤类型']
  317. physicsData['土地利用类型'] = data['土地利用类型']
  318. physicsData['土壤质地'] = data['土壤质地']
  319. # 生成相应审核报告
  320. # 根据选择的路径读取数据
  321. physicsData['原样品编号'] = physicsData['原样品编号'].astype(str)
  322. # todo 有数据后这里去掉注释
  323. # checkData = pd.read_excel(changeFileUrl, sheet_name='检测方法')
  324. # 上面这个地址,可以传递给函数中,用于保存表格和图片
  325. # 调用函数 开始生成报告相关内容
  326. # 表1相关数据
  327. typeData = report.getSimpleNum(physicsData)
  328. lenNum_1 = len(typeData['sData'])
  329. lenNum_1_f = len(typeData['allData'])
  330. table_1_data = pd.DataFrame({
  331. '类型': typeData['sData'].index,
  332. '数量': typeData['sData'],
  333. '合计': [typeData['sData'].sum() for _ in range(lenNum_1)]
  334. })
  335. # 表2数据
  336. table_2_data = report.getDataComplete(physicsData)
  337. table_2_data = table_2_data.reset_index()
  338. table_2_data.columns = ['指标名称', '实测数量', '应测数量']
  339. # 表3数据
  340. # table_3_data = report.checkMethod(checkData, mkdir_path)
  341. # 数据修约 表4
  342. report.getNum(physicsData, mkdir_path)
  343. # 数据填报项审核 表5
  344. report.dataReportResult(physicsData, mkdir_path)
  345. # 表6数据 土壤质地类型不一致
  346. middData = physicsData[['原样品编号', '样品编号']].astype(str)
  347. middData['编号'] = middData['原样品编号']
  348. del middData['原样品编号']
  349. check_1_data = pd.merge(check_1_data, middData, how='left', on='编号')
  350. check_1_data = check_1_data.replace(np.nan, '')
  351. typeNotSame = check_1_data[check_1_data['土壤质地'] != check_1_data['土壤类型(判断)']]
  352. table_6_data = typeNotSame[['编号', '样品编号', '土壤质地', '土壤类型(判断)']]
  353. allNeedData = pd.DataFrame({})
  354. allNeedData['原样品编号'] = check_1_data['编号']
  355. getSimpleDataNumber = pd.merge(allNeedData, physicsData[['原样品编号', '样品编号']], how='left', on="原样品编号")
  356. allNeedData['样品编号'] = getSimpleDataNumber['样品编号']
  357. allNeedData['土地利用类型'] = check_1_data['土地利用类型']
  358. allNeedData['审核结果'] = check_1_data['审核结果'] + check_3_data['审核结果']
  359. allNeedData['外业'] = ['' for _ in range(len(check_1_data))]
  360. table_7_data = allNeedData[allNeedData['审核结果'] != '']
  361. del table_7_data['审核结果']
  362. # 写进表格
  363. with pd.ExcelWriter(f'{mkdir_path}/超阈值样品统计表.xlsx', engine='openpyxl') as writer:
  364. table_7_data.to_excel(writer, index=False, sheet_name='超阈值数据')
  365. # 表8数据
  366. table_8_data = report.getPHData(physicsData, mkdir_path)
  367. # 表13 所有存疑数据
  368. with pd.ExcelWriter(f'{mkdir_path}/数据审核过程存疑数据一览表.xlsx', engine='openpyxl') as writer:
  369. allNeedData[allNeedData['审核结果'] != ''].to_excel(writer, index=False, sheet_name='存疑数据')
  370. # 附表: 频度分析图
  371. # report.getFrequencyImage(physicsData, mkdir_path)
  372. table_f_2_data = report.getFrequencyInformation(data, mkdir_path)
  373. # 新建一个文档
  374. doc = Document()
  375. # 添加标题
  376. doc.add_heading(f"{areaName}第三次全国土壤普查数据审核报告", level=0)
  377. # 添加一级标题
  378. doc.add_heading('一、数据完整性审核', level=1)
  379. doc.add_heading('1、土地利用类型与检测指标符合性审核', level=2)
  380. # 插入表格1
  381. paragraph_1 = doc.add_paragraph()
  382. paragraph_1.add_run(f"表1:{areaName}三普样品数量统计表(表层)").bold = True
  383. # 设置居中
  384. paragraph_1.alignment = WD_ALIGN_PARAGRAPH.CENTER
  385. table_1 = doc.add_table(rows=lenNum_1 + 1, cols=3, style='Light Shading Accent 1')
  386. table_1.alignment = WD_TABLE_ALIGNMENT.CENTER
  387. # 遍历表格 插入数据
  388. # 遍历表格的所有单元格,并填充内容
  389. for i, row in enumerate(table_1.rows):
  390. for j, cell in enumerate(row.cells):
  391. # 获取单元格中的段落对象
  392. paragraph = cell.paragraphs[0]
  393. if i == 0:
  394. r = paragraph.add_run(str(table_1_data.columns[j]))
  395. r.font.bold = True
  396. else:
  397. r = paragraph.add_run(str(table_1_data.iloc[i - 1, j]))
  398. r.font.size = Pt(10.5)
  399. r.font.name = 'Times New Roman'
  400. r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  401. paragraph.alignment = WD_PARAGRAPH_ALIGNMENT.CENTER
  402. paragraph.paragraph_format.alignment = WD_TABLE_ALIGNMENT.CENTER # 对齐
  403. paragraph.paragraph_format.line_spacing = 1 # 段落行间距
  404. # 合并单元格 合并第3列的第二行和第三行
  405. if lenNum_1 > 1:
  406. table_1.cell(2, 2).text = ''
  407. table_1.cell(1, 2).merge(table_1.cell(2, 2))
  408. ############test##############
  409. doc.add_heading('2、指标名称与实际检测样品数量完整性审核', level=2)
  410. # 插入表格2
  411. paragraph_2 = doc.add_paragraph()
  412. paragraph_2.add_run(f'表2:{areaName}指标名称与实际检测样品数量统计表').bold = True
  413. table_2 = doc.add_table(rows=len(table_2_data) + 1, cols=3, style='Light Shading Accent 1')
  414. paragraph_2.alignment = WD_ALIGN_PARAGRAPH.CENTER
  415. table_2.alignment = WD_TABLE_ALIGNMENT.CENTER
  416. for i, row in enumerate(table_2.rows):
  417. for j, cell in enumerate(row.cells):
  418. # 获取单元格中的段落对象
  419. paragraph = cell.paragraphs[0]
  420. if i == 0:
  421. r = paragraph.add_run(str(table_2_data.columns[j]))
  422. r.font.bold = True
  423. else:
  424. r = paragraph.add_run(str(table_2_data.iloc[i - 1, j]))
  425. paragraph.alignment = WD_PARAGRAPH_ALIGNMENT.CENTER
  426. paragraph.paragraph_format.alignment = WD_TABLE_ALIGNMENT.CENTER # 对齐
  427. paragraph.paragraph_format.line_spacing = 1 # 段落行间距
  428. r.font.size = Pt(10.5)
  429. r.font.name = 'Times New Roman'
  430. r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  431. doc.add_heading('二、数据规范性审核', level=1)
  432. doc.add_heading('1、数据填报规范性审核', level=2)
  433. # 插入表3
  434. paragraph_3 = doc.add_paragraph()
  435. paragraph_3.add_run(f'表3:{areaName}土壤检测数据检测方法填报审核结果表').bold = True
  436. # table_3 = doc.add_table(rows=2, cols=2)
  437. paragraph_3.alignment = WD_ALIGN_PARAGRAPH.CENTER
  438. # table_3.alignment = WD_TABLE_ALIGNMENT.CENTER
  439. # 写入数据 这里数据写不下 嵌入链接
  440. doc.add_heading('为避免数据量过多无法显示,请至数据保存文件夹中查看数据表:检测方法审核结果.xlsx', level=4)
  441. doc.add_heading('2、数值修约规范性审核', level=2)
  442. # 插入表4
  443. paragraph_4 = doc.add_paragraph()
  444. paragraph_4.add_run(f'表4:{areaName}土壤检测数据数值修约结果表').bold = True
  445. # table_4 = doc.add_table(rows=2, cols=2)
  446. paragraph_4.alignment = WD_ALIGN_PARAGRAPH.CENTER
  447. # table_4.alignment = WD_TABLE_ALIGNMENT.CENTER
  448. doc.add_heading('为避免数据量过多无法显示,请至数据保存文件夹中查看数据表:数值修约审核.xlsx', level=4)
  449. # 填入数据 这里数据也放不下 嵌入链接
  450. doc.add_heading('3、数据未检出的填报规范性审核', level=2)
  451. # 插入表5
  452. paragraph_5 = doc.add_paragraph()
  453. paragraph_5.add_run(f'表5:{areaName}土壤检测数据未检出项填报审核结果表').bold = True
  454. # table_5 = doc.add_table(rows=2, cols=2)
  455. paragraph_5.alignment = WD_ALIGN_PARAGRAPH.CENTER
  456. # table_5.alignment = WD_TABLE_ALIGNMENT.CENTER
  457. # 写入数据 这里数据也放不下 嵌入链接
  458. doc.add_heading('为避免数据量过多无法显示,请至数据保存文件夹中查看数据表:数据填报项审核结果.xlsx', level=4)
  459. doc.add_heading('4、土壤质地填报规范性审核', level=2)
  460. # 插入表6
  461. paragraph_6 = doc.add_paragraph()
  462. paragraph_6.add_run(f'表6:{areaName}土壤质地填报审核结果表').bold = True
  463. table_6 = doc.add_table(rows=len(table_6_data) + 1, cols=4, style='Light Shading Accent 1')
  464. paragraph_6.alignment = WD_ALIGN_PARAGRAPH.CENTER
  465. table_6.alignment = WD_TABLE_ALIGNMENT.CENTER
  466. # 提取结果表中数据
  467. # 写入数据 土壤质地类型不一致的数据提取出来
  468. for i, row in enumerate(table_6.rows):
  469. for j, cell in enumerate(row.cells):
  470. # 获取单元格中的段落对象
  471. paragraph = cell.paragraphs[0]
  472. if i == 0:
  473. r = paragraph.add_run(str(table_6_data.columns[j]))
  474. r.font.bold = True
  475. else:
  476. r = paragraph.add_run(str(table_6_data.iloc[i - 1, j]))
  477. paragraph.alignment = WD_PARAGRAPH_ALIGNMENT.CENTER
  478. paragraph.paragraph_format.alignment = WD_TABLE_ALIGNMENT.CENTER # 对齐
  479. paragraph.paragraph_format.line_spacing = 1 # 段落行间距
  480. r.font.size = Pt(10.5)
  481. r.font.name = 'Times New Roman'
  482. r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  483. doc.add_heading('三、数据合理性审核', level=1)
  484. doc.add_heading('1、阈值法审核', level=2)
  485. # 插入表格
  486. paragraph_7 = doc.add_paragraph()
  487. paragraph_7.add_run(f'表7:{areaName}土壤检测数据超阈值样品统计表').bold = True
  488. # table_7 = doc.add_table(rows=2, cols=2)
  489. # paragraph_7.alignment = WD_ALIGN_PARAGRAPH.CENTER
  490. # table_7.alignment = WD_TABLE_ALIGNMENT.CENTER
  491. # 写入数据 点击查看数据 这里也不一定写的下 最好是嵌入链接
  492. doc.add_heading('为避免数据量过多无法显示,请至数据保存文件夹中查看数据表:超阈值样品统计表.xlsx', level=4)
  493. # todo 合并所有数据 审核结果不为空的数据 写入表格保存到指定文件夹
  494. doc.add_heading('2、极值法审核', level=2)
  495. doc.add_heading('(1)pH', level=3)
  496. # 插入ph分布图
  497. if os.path.isfile(f'{mkdir_path}/PH值分布图.png'):
  498. doc.add_picture(f'{mkdir_path}/PH值分布图.png', width=Inches(6.0))
  499. paragraph_t_1 = doc.add_paragraph()
  500. paragraph_t_1.add_run(f'图1:pH值分布情况').bold = True
  501. paragraph_t_1.alignment = WD_ALIGN_PARAGRAPH.CENTER
  502. # 插入频度统计表
  503. paragraph_8 = doc.add_paragraph()
  504. paragraph_8.add_run('表8:pH数据统计表').bold = True
  505. table_8 = doc.add_table(rows=6, cols=2, style='Light Shading Accent 1')
  506. t_8 = table_8_data['频度分析']
  507. t_8 = t_8.reset_index()
  508. t_8.columns = ['指标', '数据']
  509. paragraph_8.alignment = WD_ALIGN_PARAGRAPH.CENTER
  510. table_8.alignment = WD_TABLE_ALIGNMENT.CENTER
  511. for i, row in enumerate(table_8.rows):
  512. for j, cell in enumerate(row.cells):
  513. # 获取单元格中的段落对象
  514. paragraph = cell.paragraphs[0]
  515. if i == 0:
  516. r = paragraph.add_run(str(t_8.columns[j]))
  517. r.font.bold = True
  518. else:
  519. r = paragraph.add_run(str(t_8.iloc[i - 1, j]))
  520. r.font.size = Pt(10.5)
  521. r.font.name = 'Times New Roman'
  522. r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  523. paragraph.alignment = WD_PARAGRAPH_ALIGNMENT.CENTER
  524. paragraph.paragraph_format.alignment = WD_TABLE_ALIGNMENT.CENTER # 对齐
  525. paragraph.paragraph_format.line_spacing = 1 # 段落行间距
  526. # 插入异常数据提取表格 todo 这里数据多的话也可能写不下 最好是嵌入一下
  527. if not table_8_data['异常数据'].empty:
  528. paragraph_9 = doc.add_paragraph()
  529. paragraph_9.add_run('表9:pH异常数据统计表').bold = True
  530. table_9 = doc.add_table(rows=len(table_8_data['异常数据']) + 1, cols=6, style='Light Shading Accent 1')
  531. t_9 = table_8_data['异常数据']
  532. paragraph_9.alignment = WD_ALIGN_PARAGRAPH.CENTER
  533. table_9.alignment = WD_TABLE_ALIGNMENT.CENTER
  534. for i, row in enumerate(table_9.rows):
  535. for j, cell in enumerate(row.cells):
  536. # 获取单元格中的段落对象
  537. paragraph = cell.paragraphs[0]
  538. if i == 0:
  539. r = paragraph.add_run(str(t_9.columns[j]))
  540. r.font.bold = True
  541. else:
  542. r = paragraph.add_run(str(t_9.iloc[i - 1, j]))
  543. r.font.size = Pt(10.5)
  544. r.font.name = 'Times New Roman'
  545. r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  546. paragraph.alignment = WD_PARAGRAPH_ALIGNMENT.CENTER
  547. paragraph.paragraph_format.alignment = WD_TABLE_ALIGNMENT.CENTER # 对齐
  548. paragraph.paragraph_format.line_spacing = 1 # 段落行间距
  549. doc.add_heading('四、审核存疑数据', level=1)
  550. paragraph_12 = doc.add_paragraph()
  551. paragraph_12.add_run(f'表10:数据审核过程存疑数据一览表').bold = True
  552. paragraph_12.alignment = WD_ALIGN_PARAGRAPH.CENTER
  553. doc.add_heading('为避免数据量过多无法显示,请至数据保存文件夹中查看数据表:物理指标数据审核过程存疑数据一览表.xlsx', level=4)
  554. doc.add_heading('五、附表', level=1)
  555. doc.add_heading('附表1:某区三普样品数量统计表(表层)', level=2)
  556. # 插入附表1
  557. table_1_f = doc.add_table(rows=lenNum_1 + 1, cols=3, style='Light Shading Accent 1')
  558. table_1_f.alignment = WD_TABLE_ALIGNMENT.CENTER
  559. # 遍历表格 插入数据
  560. # 遍历表格的所有单元格,并填充内容
  561. for i, row in enumerate(table_1_f.rows):
  562. for j, cell in enumerate(row.cells):
  563. # 获取单元格中的段落对象
  564. paragraph = cell.paragraphs[0]
  565. if i == 0:
  566. r = paragraph.add_run(str(table_1_data.columns[j]))
  567. r.font.bold = True
  568. else:
  569. r = paragraph.add_run(str(table_1_data.iloc[i - 1, j]))
  570. r.font.size = Pt(10.5)
  571. r.font.name = 'Times New Roman'
  572. r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  573. paragraph.alignment = WD_PARAGRAPH_ALIGNMENT.CENTER
  574. paragraph.paragraph_format.alignment = WD_TABLE_ALIGNMENT.CENTER # 对齐
  575. paragraph.paragraph_format.line_spacing = 1 # 段落行间距
  576. # 合并单元格 合并第3列的第二行和第三行
  577. if lenNum_1 > 1:
  578. table_1_f.cell(2, 2).text = ''
  579. table_1_f.cell(1, 2).merge(table_1_f.cell(2, 2))
  580. doc.add_heading('附表2:各指标频度分析表', level=2)
  581. # 插入表格 写入数据
  582. table_f_2_data = table_f_2_data.replace(np.nan, '')
  583. makeInfoTable(table_f_2_data, doc)
  584. # table_f_2 = doc.add_table(rows=len(table_f_2_data) + 1, cols=6, style='Light Shading Accent 1')
  585. # for i, row in enumerate(table_f_2.rows):
  586. # for j, cell in enumerate(row.cells):
  587. # # 获取单元格中的段落对象
  588. # paragraph = cell.paragraphs[0]
  589. # if i == 0:
  590. # r = paragraph.add_run(str(table_f_2_data.columns[j]))
  591. # r.font.bold = True
  592. # else:
  593. # r = paragraph.add_run(str(table_f_2_data.iloc[i - 1, j]))
  594. # r.font.size = Pt(10.5)
  595. # r.font.name = 'Times New Roman'
  596. # r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  597. # paragraph.alignment = WD_PARAGRAPH_ALIGNMENT.CENTER
  598. # paragraph.paragraph_format.alignment = WD_TABLE_ALIGNMENT.CENTER # 对齐
  599. # paragraph.paragraph_format.line_spacing = 1 # 段落行间距
  600. # doc.add_heading('为避免数据量过多无法显示,请至数据保存文件夹中查看数据表:频度分析表.xlsx', level=4)
  601. doc.add_heading('附表3:各指标频度分析图', level=2)
  602. # 插入频度信息的图形
  603. if os.path.isfile(f'{mkdir_path}/0.002mm以下颗粒含量分析图.png'):
  604. doc.add_picture(f'{mkdir_path}/0.002mm以下颗粒含量分析图.png', width=Inches(6.0))
  605. if os.path.isfile(f'{mkdir_path}/0.02~0.002mm颗粒含量分析图.png.png'):
  606. doc.add_picture(f'{mkdir_path}/0.02~0.002mm颗粒含量分析图.png', width=Inches(6.0))
  607. if os.path.isfile(f'{mkdir_path}/0.2~0.02mm颗粒含量分析图.png'):
  608. doc.add_picture(f'{mkdir_path}/0.2~0.02mm颗粒含量分析图.png', width=Inches(6.0))
  609. if os.path.isfile(f'{mkdir_path}/2~0.2mm颗粒含量分析图.png'):
  610. doc.add_picture(f'{mkdir_path}/2~0.2mm颗粒含量分析图.png', width=Inches(6.0))
  611. if os.path.isfile(f'{mkdir_path}/pH分析图.png'):
  612. doc.add_picture(f'{mkdir_path}/pH分析图.png', width=Inches(6.0))
  613. if os.path.isfile(f'{mkdir_path}/风干试样含水量(分析基)分析图.png'):
  614. doc.add_picture(f'{mkdir_path}/风干试样含水量(分析基)分析图.png', width=Inches(6.0))
  615. if os.path.isfile(f'{mkdir_path}/洗失量(吸管法需填)分析图.png'):
  616. doc.add_picture(f'{mkdir_path}/洗失量(吸管法需填)分析图.png', width=Inches(6.0))
  617. if os.path.isfile(f'{mkdir_path}/土壤容重1分析图.png'):
  618. doc.add_picture(f'{mkdir_path}/土壤容重1分析图.png', width=Inches(6.0))
  619. if os.path.isfile(f'{mkdir_path}/土壤容重2分析图.png'):
  620. doc.add_picture(f'{mkdir_path}/土壤容重2分析图.png', width=Inches(6.0))
  621. if os.path.isfile(f'{mkdir_path}/土壤容重3分析图.png'):
  622. doc.add_picture(f'{mkdir_path}/土壤容重3分析图.png', width=Inches(6.0))
  623. if os.path.isfile(f'{mkdir_path}/土壤容重4分析图.png'):
  624. doc.add_picture(f'{mkdir_path}/土壤容重4分析图.png', width=Inches(6.0))
  625. if os.path.isfile(f'{mkdir_path}/土壤容重平均值分析图.png'):
  626. doc.add_picture(f'{mkdir_path}/土壤容重平均值分析图.png', width=Inches(6.0))
  627. if os.path.isfile(f'{mkdir_path}/水稳0.5mm~1mm分析图.png'):
  628. doc.add_picture(f'{mkdir_path}/水稳0.5mm~1mm分析图.png', width=Inches(6.0))
  629. if os.path.isfile(f'{mkdir_path}/水稳0.25mm~0.5mm分析图.png'):
  630. doc.add_picture(f'{mkdir_path}/水稳0.25mm~0.5mm分析图.png', width=Inches(6.0))
  631. if os.path.isfile(f'{mkdir_path}/水稳1mm~2mm分析图.png'):
  632. doc.add_picture(f'{mkdir_path}/水稳1mm~2mm分析图.png', width=Inches(6.0))
  633. if os.path.isfile(f'{mkdir_path}/水稳2mm~3mm分析图.png'):
  634. doc.add_picture(f'{mkdir_path}/水稳2mm~3mm分析图.png', width=Inches(6.0))
  635. if os.path.isfile(f'{mkdir_path}/水稳3mm~5mm分析图.png'):
  636. doc.add_picture(f'{mkdir_path}/水稳3mm~5mm分析图.png', width=Inches(6.0))
  637. if os.path.isfile(f'{mkdir_path}/水稳5mm分析图.png'):
  638. doc.add_picture(f'{mkdir_path}/水稳5mm分析图.png', width=Inches(6.0))
  639. doc.add_heading('附表4:数值修约标准', level=2)
  640. # 读取数据 插入表格 写入数据
  641. numData = pd.read_excel('./img/数值修约要求.xlsx', sheet_name='Sheet1')
  642. table_2_f = doc.add_table(rows=len(numData) + 1, cols=2, style='Light Shading Accent 1')
  643. table_2_f.alignment = WD_TABLE_ALIGNMENT.CENTER
  644. for i, row in enumerate(table_2_f.rows):
  645. for j, cell in enumerate(row.cells):
  646. # 获取单元格中的段落对象
  647. paragraph = cell.paragraphs[0]
  648. if i == 0:
  649. r = paragraph.add_run(str(numData.columns[j]))
  650. r.font.bold = True
  651. else:
  652. r = paragraph.add_run(str(numData.iloc[i - 1, j]))
  653. r.font.size = Pt(10.5)
  654. r.font.name = 'Times New Roman'
  655. r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  656. paragraph.alignment = WD_PARAGRAPH_ALIGNMENT.CENTER
  657. paragraph.paragraph_format.alignment = WD_TABLE_ALIGNMENT.CENTER # 对齐
  658. paragraph.paragraph_format.line_spacing = 1 # 段落行间距
  659. # 处理样式 遍历所有的段落 修改字体
  660. # 遍历并打印每个段落的文本
  661. paragraphs = doc.paragraphs
  662. for paragraph in paragraphs:
  663. for run in paragraph.runs:
  664. run.font.color.rgb = RGBColor(0, 0, 0)
  665. run.font.name = 'Times New Roman'
  666. run.font.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  667. # 保存Word文档
  668. doc.save(f'{mkdir_path}/{areaName}-{type}审核报告.docx')
  669. # 生成常规养分指标审核报告
  670. def getConventionalNutrientIndicators(data,type, changeFileUrl, saveFileUrl, check_1_data,
  671. check_3_data,
  672. check_5_data,
  673. check_8_data, # 样品编号替换为编号
  674. check_10_data,
  675. check_12_data,
  676. check_14_data ):
  677. # 生成报告
  678. name = os.path.basename(changeFileUrl)
  679. n = name.split('.')
  680. areaName = n[0].replace('数据', '')
  681. # 生成一个新的文件夹用于存放审核报告相关的数据
  682. nowTime = time.strftime("%Y-%m-%d %H时%M分%S秒", time.localtime())
  683. dir_name = f'{areaName}-{type}数据审核报告'
  684. mkdir_path = saveFileUrl + '/' + dir_name + nowTime
  685. if not os.path.exists(mkdir_path):
  686. os.mkdir(mkdir_path)
  687. # 根据选择的路径读取数据
  688. ConventionalNutrientData = data[indexClassificationList[type]]
  689. report.getFrequencyImage(ConventionalNutrientData, mkdir_path)
  690. ConventionalNutrientData['序号'] = data['序号']
  691. ConventionalNutrientData['原样品编号'] = data['原样品编号']
  692. ConventionalNutrientData['样品编号'] = data['样品编号']
  693. ConventionalNutrientData['地理位置'] = data['地理位置']
  694. ConventionalNutrientData['母质'] = data['母质']
  695. ConventionalNutrientData['土壤类型'] = data['土壤类型']
  696. ConventionalNutrientData['土地利用类型'] = data['土地利用类型']
  697. # ConventionalNutrientData['土壤质地'] = data['土壤质地']
  698. # 生成相应审核报告
  699. ConventionalNutrientData['原样品编号'] = ConventionalNutrientData['原样品编号'].astype(str)
  700. data['原样品编号'] = data['原样品编号'].astype(str)
  701. # checkData = pd.read_excel(changeFileUrl, sheet_name='检测方法')
  702. # 上面这个地址,可以纯递给函数中,用于保存表格和图片
  703. # 调用函数 开始生成报告相关内容
  704. # 表1相关数据
  705. typeData = report.getSimpleNum(ConventionalNutrientData)
  706. lenNum_1 = len(typeData['sData'])
  707. lenNum_1_f = len(typeData['allData'])
  708. table_1_data = pd.DataFrame({
  709. '类型': typeData['sData'].index,
  710. '数量': typeData['sData'],
  711. '合计': [typeData['sData'].sum() for _ in range(lenNum_1)]
  712. })
  713. # 表2数据
  714. table_2_data = report.getDataComplete(ConventionalNutrientData)
  715. table_2_data = table_2_data.reset_index()
  716. table_2_data.columns = ['指标名称', '实测数量', '应测数量']
  717. # 表3数据
  718. # table_3_data = report.checkMethod(checkData, mkdir_path)
  719. # 数据修约 表4
  720. report.getNum(ConventionalNutrientData, mkdir_path)
  721. # 数据填报项审核 表5
  722. report.dataReportResult(ConventionalNutrientData, mkdir_path)
  723. # 表6数据 土壤质地类型不一致
  724. middData = data[['原样品编号', '样品编号']].astype(str)
  725. middData['编号'] = middData['原样品编号']
  726. del middData['原样品编号']
  727. check_1_data = pd.merge(check_1_data, middData, how='left', on='编号')
  728. check_1_data = check_1_data.replace(np.nan, '')
  729. # typeNotSame = check_1_data[check_1_data['土壤质地'] != check_1_data['土壤类型(判断)']]
  730. # table_6_data = typeNotSame[['编号', '样品编号', '土壤质地', '土壤类型(判断)']]
  731. allNeedData = pd.DataFrame({})
  732. allNeedData['原样品编号'] = check_1_data['编号']
  733. getSimpleDataNumber = pd.merge(allNeedData, ConventionalNutrientData[['原样品编号', '样品编号']], how='left', on="原样品编号")
  734. allNeedData['样品编号'] = getSimpleDataNumber['样品编号']
  735. allNeedData['土地利用类型'] = check_1_data['土地利用类型']
  736. allNeedData['审核结果'] = check_10_data['审核结果'] + check_12_data['审核结果']
  737. allNeedData['外业'] = ['' for _ in range(len(check_1_data))]
  738. table_7_data = allNeedData[allNeedData['审核结果'] != '']
  739. del table_7_data['审核结果']
  740. # 写进表格
  741. with pd.ExcelWriter(f'{mkdir_path}/超阈值样品统计表.xlsx', engine='openpyxl') as writer:
  742. table_7_data.to_excel(writer, index=False, sheet_name='超阈值数据')
  743. # 表8数据
  744. table_8_data = report.getPHData(ConventionalNutrientData, mkdir_path)
  745. # 表10 数据
  746. table_10_data = report.getNAndC(ConventionalNutrientData, mkdir_path)
  747. # 表11 数据:全磷和有效磷异常数据统计
  748. table_11_data = report.getPData(ConventionalNutrientData, mkdir_path)
  749. report.getKData(ConventionalNutrientData, mkdir_path)
  750. # 表13 所有存疑数据
  751. with pd.ExcelWriter(f'{mkdir_path}/数据审核过程存疑数据一览表.xlsx', engine='openpyxl') as writer:
  752. allNeedData[allNeedData['审核结果'] != ''].to_excel(writer, index=False, sheet_name='存疑数据')
  753. # 附表: 频度分析图
  754. # report.getFrequencyImage(ConventionalNutrientData, mkdir_path)
  755. table_f_2_data = report.getFrequencyInformation(data, mkdir_path)
  756. # 新建一个文档
  757. doc = Document()
  758. # 添加标题
  759. doc.add_heading(f"{areaName}第三次全国土壤普查数据审核报告", level=0)
  760. # 添加一级标题
  761. doc.add_heading('一、数据完整性审核', level=1)
  762. doc.add_heading('1、土地利用类型与检测指标符合性审核', level=2)
  763. # 插入表格1
  764. paragraph_1 = doc.add_paragraph()
  765. paragraph_1.add_run(f"表1:{areaName}三普样品数量统计表(表层)").bold = True
  766. # 设置居中
  767. paragraph_1.alignment = WD_ALIGN_PARAGRAPH.CENTER
  768. table_1 = doc.add_table(rows=lenNum_1 + 1, cols=3, style='Light Shading Accent 1')
  769. table_1.alignment = WD_TABLE_ALIGNMENT.CENTER
  770. # 遍历表格 插入数据
  771. # 遍历表格的所有单元格,并填充内容
  772. for i, row in enumerate(table_1.rows):
  773. for j, cell in enumerate(row.cells):
  774. # 获取单元格中的段落对象
  775. paragraph = cell.paragraphs[0]
  776. if i == 0:
  777. r = paragraph.add_run(str(table_1_data.columns[j]))
  778. r.font.bold = True
  779. else:
  780. r = paragraph.add_run(str(table_1_data.iloc[i - 1, j]))
  781. r.font.size = Pt(10.5)
  782. r.font.name = 'Times New Roman'
  783. r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  784. paragraph.alignment = WD_PARAGRAPH_ALIGNMENT.CENTER
  785. paragraph.paragraph_format.alignment = WD_TABLE_ALIGNMENT.CENTER # 对齐
  786. paragraph.paragraph_format.line_spacing = 1 # 段落行间距
  787. # 合并单元格 合并第3列的第二行和第三行
  788. if lenNum_1 > 1:
  789. table_1.cell(2, 2).text = ''
  790. table_1.cell(1, 2).merge(table_1.cell(2, 2))
  791. ############test##############
  792. doc.add_heading('2、指标名称与实际检测样品数量完整性审核', level=2)
  793. # 插入表格2
  794. paragraph_2 = doc.add_paragraph()
  795. paragraph_2.add_run(f'表2:{areaName}指标名称与实际检测样品数量统计表').bold = True
  796. table_2 = doc.add_table(rows=len(table_2_data) + 1, cols=3, style='Light Shading Accent 1')
  797. paragraph_2.alignment = WD_ALIGN_PARAGRAPH.CENTER
  798. table_2.alignment = WD_TABLE_ALIGNMENT.CENTER
  799. for i, row in enumerate(table_2.rows):
  800. for j, cell in enumerate(row.cells):
  801. # 获取单元格中的段落对象
  802. paragraph = cell.paragraphs[0]
  803. if i == 0:
  804. r = paragraph.add_run(str(table_2_data.columns[j]))
  805. r.font.bold = True
  806. else:
  807. r = paragraph.add_run(str(table_2_data.iloc[i - 1, j]))
  808. paragraph.alignment = WD_PARAGRAPH_ALIGNMENT.CENTER
  809. paragraph.paragraph_format.alignment = WD_TABLE_ALIGNMENT.CENTER # 对齐
  810. paragraph.paragraph_format.line_spacing = 1 # 段落行间距
  811. r.font.size = Pt(10.5)
  812. r.font.name = 'Times New Roman'
  813. r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  814. doc.add_heading('二、数据规范性审核', level=1)
  815. doc.add_heading('1、数据填报规范性审核', level=2)
  816. # 插入表3
  817. paragraph_3 = doc.add_paragraph()
  818. paragraph_3.add_run(f'表3:{areaName}土壤检测数据检测方法填报审核结果表').bold = True
  819. # table_3 = doc.add_table(rows=2, cols=2)
  820. paragraph_3.alignment = WD_ALIGN_PARAGRAPH.CENTER
  821. # table_3.alignment = WD_TABLE_ALIGNMENT.CENTER
  822. # 写入数据 这里数据写不下 嵌入链接
  823. doc.add_heading('为避免数据量过多无法显示,请至数据保存文件夹中查看数据表:检测方法审核结果.xlsx', level=4)
  824. doc.add_heading('2、数值修约规范性审核', level=2)
  825. # 插入表4
  826. paragraph_4 = doc.add_paragraph()
  827. paragraph_4.add_run(f'表4:{areaName}土壤检测数据数值修约结果表').bold = True
  828. # table_4 = doc.add_table(rows=2, cols=2)
  829. paragraph_4.alignment = WD_ALIGN_PARAGRAPH.CENTER
  830. # table_4.alignment = WD_TABLE_ALIGNMENT.CENTER
  831. doc.add_heading('为避免数据量过多无法显示,请至数据保存文件夹中查看数据表:数值修约审核.xlsx', level=4)
  832. # 填入数据 这里数据也放不下 嵌入链接
  833. doc.add_heading('3、数据未检出的填报规范性审核', level=2)
  834. # 插入表5
  835. paragraph_5 = doc.add_paragraph()
  836. paragraph_5.add_run(f'表5:{areaName}土壤检测数据未检出项填报审核结果表').bold = True
  837. # table_5 = doc.add_table(rows=2, cols=2)
  838. paragraph_5.alignment = WD_ALIGN_PARAGRAPH.CENTER
  839. # table_5.alignment = WD_TABLE_ALIGNMENT.CENTER
  840. # 写入数据 这里数据也放不下 嵌入链接
  841. doc.add_heading('为避免数据量过多无法显示,请至数据保存文件夹中查看数据表:数据填报项审核结果.xlsx', level=4)
  842. # doc.add_heading('4、土壤质地填报规范性审核', level=2)
  843. # 插入表6
  844. # paragraph_6 = doc.add_paragraph()
  845. # paragraph_6.add_run(f'表6:{areaName}土壤质地填报审核结果表').bold = True
  846. # table_6 = doc.add_table(rows=len(table_6_data) + 1, cols=4, style='Light Shading Accent 1')
  847. # paragraph_6.alignment = WD_ALIGN_PARAGRAPH.CENTER
  848. # table_6.alignment = WD_TABLE_ALIGNMENT.CENTER
  849. # # 提取结果表中数据
  850. # # 写入数据 土壤质地类型不一致的数据提取出来
  851. # for i, row in enumerate(table_6.rows):
  852. # for j, cell in enumerate(row.cells):
  853. # # 获取单元格中的段落对象
  854. # paragraph = cell.paragraphs[0]
  855. # if i == 0:
  856. # r = paragraph.add_run(str(table_6_data.columns[j]))
  857. # r.font.bold = True
  858. # else:
  859. # r = paragraph.add_run(str(table_6_data.iloc[i - 1, j]))
  860. # paragraph.alignment = WD_PARAGRAPH_ALIGNMENT.CENTER
  861. # paragraph.paragraph_format.alignment = WD_TABLE_ALIGNMENT.CENTER # 对齐
  862. # paragraph.paragraph_format.line_spacing = 1 # 段落行间距
  863. # r.font.size = Pt(10.5)
  864. # r.font.name = 'Times New Roman'
  865. # r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  866. doc.add_heading('三、数据合理性审核', level=1)
  867. doc.add_heading('1、阈值法审核', level=2)
  868. # 插入表格
  869. paragraph_7 = doc.add_paragraph()
  870. paragraph_7.add_run(f'表6:{areaName}土壤检测数据超阈值样品统计表').bold = True
  871. # table_7 = doc.add_table(rows=2, cols=2)
  872. # paragraph_7.alignment = WD_ALIGN_PARAGRAPH.CENTER
  873. # table_7.alignment = WD_TABLE_ALIGNMENT.CENTER
  874. # 写入数据 点击查看数据 这里也不一定写的下 最好是嵌入链接
  875. doc.add_heading('为避免数据量过多无法显示,请至数据保存文件夹中查看数据表:数据审核过程存疑数据一览表.xlsx', level=4)
  876. # todo 合并所有数据 审核结果不为空的数据 写入表格保存到指定文件夹
  877. doc.add_heading('2、极值法审核', level=2)
  878. doc.add_heading('(1)pH', level=3)
  879. # 插入ph分布图
  880. if os.path.isfile(f'{mkdir_path}/PH值分布图.png'):
  881. doc.add_picture(f'{mkdir_path}/PH值分布图.png', width=Inches(6.0))
  882. paragraph_t_1 = doc.add_paragraph()
  883. paragraph_t_1.add_run(f'图1:pH值分布情况').bold = True
  884. paragraph_t_1.alignment = WD_ALIGN_PARAGRAPH.CENTER
  885. # 插入频度统计表
  886. paragraph_8 = doc.add_paragraph()
  887. paragraph_8.add_run('表7:pH数据统计表').bold = True
  888. table_8 = doc.add_table(rows=6, cols=2, style='Light Shading Accent 1')
  889. t_8 = table_8_data['频度分析']
  890. t_8 = t_8.reset_index()
  891. t_8.columns = ['指标', '数据']
  892. paragraph_8.alignment = WD_ALIGN_PARAGRAPH.CENTER
  893. table_8.alignment = WD_TABLE_ALIGNMENT.CENTER
  894. for i, row in enumerate(table_8.rows):
  895. for j, cell in enumerate(row.cells):
  896. # 获取单元格中的段落对象
  897. paragraph = cell.paragraphs[0]
  898. if i == 0:
  899. r = paragraph.add_run(str(t_8.columns[j]))
  900. r.font.bold = True
  901. else:
  902. r = paragraph.add_run(str(t_8.iloc[i - 1, j]))
  903. r.font.size = Pt(10.5)
  904. r.font.name = 'Times New Roman'
  905. r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  906. paragraph.alignment = WD_PARAGRAPH_ALIGNMENT.CENTER
  907. paragraph.paragraph_format.alignment = WD_TABLE_ALIGNMENT.CENTER # 对齐
  908. paragraph.paragraph_format.line_spacing = 1 # 段落行间距
  909. # 插入异常数据提取表格 todo 这里数据多的话也可能写不下 最好是嵌入一下
  910. if not table_8_data['异常数据'].empty:
  911. paragraph_9 = doc.add_paragraph()
  912. paragraph_9.add_run('表8:pH异常数据统计表').bold = True
  913. table_9 = doc.add_table(rows=len(table_8_data['异常数据']) + 1, cols=6, style='Light Shading Accent 1')
  914. t_9 = table_8_data['异常数据']
  915. paragraph_9.alignment = WD_ALIGN_PARAGRAPH.CENTER
  916. table_9.alignment = WD_TABLE_ALIGNMENT.CENTER
  917. for i, row in enumerate(table_9.rows):
  918. for j, cell in enumerate(row.cells):
  919. # 获取单元格中的段落对象
  920. paragraph = cell.paragraphs[0]
  921. if i == 0:
  922. r = paragraph.add_run(str(t_9.columns[j]))
  923. r.font.bold = True
  924. else:
  925. r = paragraph.add_run(str(t_9.iloc[i - 1, j]))
  926. r.font.size = Pt(10.5)
  927. r.font.name = 'Times New Roman'
  928. r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  929. paragraph.alignment = WD_PARAGRAPH_ALIGNMENT.CENTER
  930. paragraph.paragraph_format.alignment = WD_TABLE_ALIGNMENT.CENTER # 对齐
  931. paragraph.paragraph_format.line_spacing = 1 # 段落行间距
  932. doc.add_heading('3、关联分析法审核', level=2)
  933. if os.path.isfile(f'{mkdir_path}/有机质与全氮相关性分析图.png'):
  934. doc.add_picture(f'{mkdir_path}/有机质与全氮相关性分析图.png', width=Inches(6.0))
  935. paragraph_t_2 = doc.add_paragraph()
  936. paragraph_t_2.add_run(f'图2:有机质与全氮相关关系').bold = True
  937. paragraph_t_2.alignment = WD_ALIGN_PARAGRAPH.CENTER
  938. # 插入碳氮比异常数据
  939. if not table_10_data.empty:
  940. paragraph_10 = doc.add_paragraph()
  941. paragraph_10.add_run('表9:碳氮比异常数据统计表').bold = True
  942. table_10 = doc.add_table(rows=len(table_10_data) + 1, cols=8, style='Light Shading Accent 1')
  943. paragraph_10.alignment = WD_ALIGN_PARAGRAPH.CENTER
  944. table_10.alignment = WD_TABLE_ALIGNMENT.CENTER
  945. for i, row in enumerate(table_10.rows):
  946. for j, cell in enumerate(row.cells):
  947. # 获取单元格中的段落对象
  948. paragraph = cell.paragraphs[0]
  949. if i == 0:
  950. r = paragraph.add_run(str(table_10_data.columns[j]))
  951. r.font.bold = True
  952. else:
  953. r = paragraph.add_run(str(table_10_data.iloc[i - 1, j]))
  954. r.font.size = Pt(10.5)
  955. r.font.name = 'Times New Roman'
  956. r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  957. paragraph.alignment = WD_PARAGRAPH_ALIGNMENT.CENTER
  958. paragraph.paragraph_format.alignment = WD_TABLE_ALIGNMENT.CENTER # 对齐
  959. paragraph.paragraph_format.line_spacing = 1 # 段落行间距
  960. doc.add_heading('4、指标综合分析', level=2)
  961. # 插入图片
  962. if os.path.isfile(f'{mkdir_path}/全磷分布图.png'):
  963. doc.add_picture(f'{mkdir_path}/全磷分布图.png', width=Inches(6.0))
  964. paragraph_t_3 = doc.add_paragraph()
  965. paragraph_t_3.add_run(f'图3:全磷分布图').bold = True
  966. paragraph_t_3.alignment = WD_ALIGN_PARAGRAPH.CENTER
  967. if os.path.isfile(f'{mkdir_path}/有效磷分布图.png'):
  968. doc.add_picture(f'{mkdir_path}/有效磷分布图.png', width=Inches(6.0))
  969. paragraph_t_4 = doc.add_paragraph()
  970. paragraph_t_4.add_run(f'图4:有效磷分布图').bold = True
  971. paragraph_t_4.alignment = WD_ALIGN_PARAGRAPH.CENTER
  972. # 插入图片
  973. if os.path.isfile(f'{mkdir_path}/有效磷占全磷比分布图.png'):
  974. doc.add_picture(f'{mkdir_path}/有效磷占全磷比分布图.png', width=Inches(6.0))
  975. paragraph_t_5 = doc.add_paragraph()
  976. paragraph_t_5.add_run(f'图5:有效磷含量占全磷含量比例').bold = True
  977. paragraph_t_5.alignment = WD_ALIGN_PARAGRAPH.CENTER
  978. # 插入表格
  979. if not table_11_data.empty:
  980. paragraph_11 = doc.add_paragraph()
  981. paragraph_11.add_run('表10:全磷与有效磷异常样品统计表').bold = True
  982. table_11 = doc.add_table(rows=len(table_11_data) + 1, cols=7, style='Light Shading Accent 1')
  983. paragraph_11.alignment = WD_ALIGN_PARAGRAPH.CENTER
  984. table_11.alignment = WD_TABLE_ALIGNMENT.CENTER
  985. for i, row in enumerate(table_11.rows):
  986. for j, cell in enumerate(row.cells):
  987. # 获取单元格中的段落对象
  988. paragraph = cell.paragraphs[0]
  989. if i == 0:
  990. r = paragraph.add_run(str(table_11_data.columns[j]))
  991. r.font.bold = True
  992. else:
  993. r = paragraph.add_run(str(table_11_data.iloc[i - 1, j]))
  994. r.font.size = Pt(10.5)
  995. r.font.name = 'Times New Roman'
  996. r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  997. paragraph.alignment = WD_PARAGRAPH_ALIGNMENT.CENTER
  998. paragraph.paragraph_format.alignment = WD_TABLE_ALIGNMENT.CENTER # 对齐
  999. paragraph.paragraph_format.line_spacing = 1 # 段落行间距
  1000. else:
  1001. paragraph_11 = doc.add_paragraph()
  1002. paragraph_11.add_run('表10:全磷与有效磷异常样品统计表').bold = True
  1003. paragraph_11_info = doc.add_paragraph()
  1004. paragraph_11_info.add_run('无异常数据')
  1005. paragraph_11.alignment = WD_ALIGN_PARAGRAPH.CENTER
  1006. paragraph_11_info.alignment = WD_ALIGN_PARAGRAPH.CENTER
  1007. # 全钾、速效钾、缓效钾
  1008. if os.path.isfile(f'{mkdir_path}/全钾与速效钾缓效钾之和关系统计图.png'):
  1009. doc.add_picture(f'{mkdir_path}/全钾与速效钾缓效钾之和关系统计图.png', width=Inches(6.0))
  1010. paragraph_t_6 = doc.add_paragraph()
  1011. paragraph_t_6.add_run(f'图6:全钾与速效钾缓效钾之和关系统计图').bold = True
  1012. paragraph_t_6.alignment = WD_ALIGN_PARAGRAPH.CENTER
  1013. if os.path.isfile(f'{mkdir_path}/速效钾与缓效钾关系统计图.png'):
  1014. doc.add_picture(f'{mkdir_path}/速效钾与缓效钾关系统计图.png', width=Inches(6.0))
  1015. paragraph_t_7 = doc.add_paragraph()
  1016. paragraph_t_7.add_run(f'图7:速效钾与缓效钾关系统计图').bold = True
  1017. paragraph_t_7.alignment = WD_ALIGN_PARAGRAPH.CENTER
  1018. doc.add_heading('四、审核存疑数据', level=1)
  1019. paragraph_12 = doc.add_paragraph()
  1020. paragraph_12.add_run(f'表11:数据审核过程存疑数据一览表').bold = True
  1021. paragraph_12.alignment = WD_ALIGN_PARAGRAPH.CENTER
  1022. doc.add_heading('为避免数据量过多无法显示,请至数据保存文件夹中查看数据表:数据审核过程存疑数据一览表.xlsx', level=4)
  1023. doc.add_heading('五、附表', level=1)
  1024. doc.add_heading('附表1:某区三普样品数量统计表(表层)', level=2)
  1025. # 插入附表1
  1026. table_1_f = doc.add_table(rows=lenNum_1 + 1, cols=3, style='Light Shading Accent 1')
  1027. table_1_f.alignment = WD_TABLE_ALIGNMENT.CENTER
  1028. # 遍历表格 插入数据
  1029. # 遍历表格的所有单元格,并填充内容
  1030. for i, row in enumerate(table_1_f.rows):
  1031. for j, cell in enumerate(row.cells):
  1032. # 获取单元格中的段落对象
  1033. paragraph = cell.paragraphs[0]
  1034. if i == 0:
  1035. r = paragraph.add_run(str(table_1_data.columns[j]))
  1036. r.font.bold = True
  1037. else:
  1038. r = paragraph.add_run(str(table_1_data.iloc[i - 1, j]))
  1039. r.font.size = Pt(10.5)
  1040. r.font.name = 'Times New Roman'
  1041. r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  1042. paragraph.alignment = WD_PARAGRAPH_ALIGNMENT.CENTER
  1043. paragraph.paragraph_format.alignment = WD_TABLE_ALIGNMENT.CENTER # 对齐
  1044. paragraph.paragraph_format.line_spacing = 1 # 段落行间距
  1045. # 合并单元格 合并第3列的第二行和第三行
  1046. if lenNum_1 > 1:
  1047. table_1_f.cell(2, 2).text = ''
  1048. table_1_f.cell(1, 2).merge(table_1_f.cell(2, 2))
  1049. doc.add_heading('附表2:各指标频度分析表', level=2)
  1050. # 插入表格 写入数据
  1051. table_f_2_data = table_f_2_data.replace(np.nan, '')
  1052. makeInfoTable(table_f_2_data, doc)
  1053. # table_f_2 = doc.add_table(rows=len(table_f_2_data) + 1, cols=6, style='Light Shading Accent 1')
  1054. # for i, row in enumerate(table_f_2.rows):
  1055. # for j, cell in enumerate(row.cells):
  1056. # # 获取单元格中的段落对象
  1057. # paragraph = cell.paragraphs[0]
  1058. # if i == 0:
  1059. # r = paragraph.add_run(str(table_f_2_data.columns[j]))
  1060. # r.font.bold = True
  1061. # else:
  1062. # r = paragraph.add_run(str(table_f_2_data.iloc[i - 1, j]))
  1063. # r.font.size = Pt(10.5)
  1064. # r.font.name = 'Times New Roman'
  1065. # r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  1066. # paragraph.alignment = WD_PARAGRAPH_ALIGNMENT.CENTER
  1067. # paragraph.paragraph_format.alignment = WD_TABLE_ALIGNMENT.CENTER # 对齐
  1068. # paragraph.paragraph_format.line_spacing = 1 # 段落行间距
  1069. # doc.add_heading('为避免数据量过多无法显示,请至数据保存文件夹中查看数据表:频度分析表.xlsx', level=4)
  1070. doc.add_heading('附表3:各指标频度分析图', level=2)
  1071. # 插入频度信息的图形
  1072. if os.path.isfile(f'{mkdir_path}/pH分析图.png'):
  1073. doc.add_picture(f'{mkdir_path}/pH分析图.png', width=Inches(6.0))
  1074. if os.path.isfile(f'{mkdir_path}/缓效钾分析图.png'):
  1075. doc.add_picture(f'{mkdir_path}/缓效钾分析图.png', width=Inches(6.0))
  1076. if os.path.isfile(f'{mkdir_path}/全氮分析图.png'):
  1077. doc.add_picture(f'{mkdir_path}/全氮分析图.png', width=Inches(6.0))
  1078. if os.path.isfile(f'{mkdir_path}/全钾分析图.png'):
  1079. doc.add_picture(f'{mkdir_path}/全钾分析图.png', width=Inches(6.0))
  1080. if os.path.isfile(f'{mkdir_path}/全磷分析图.png'):
  1081. doc.add_picture(f'{mkdir_path}/全磷分析图.png', width=Inches(6.0))
  1082. if os.path.isfile(f'{mkdir_path}/速效钾分析图.png'):
  1083. doc.add_picture(f'{mkdir_path}/速效钾分析图.png', width=Inches(6.0))
  1084. if os.path.isfile(f'{mkdir_path}/有机质分析图.png'):
  1085. doc.add_picture(f'{mkdir_path}/有机质分析图.png', width=Inches(6.0))
  1086. if os.path.isfile(f'{mkdir_path}/有效硅分析图.png'):
  1087. doc.add_picture(f'{mkdir_path}/有效硅分析图.png', width=Inches(6.0))
  1088. if os.path.isfile(f'{mkdir_path}/有效磷分析图.png'):
  1089. doc.add_picture(f'{mkdir_path}/有效磷分析图.png', width=Inches(6.0))
  1090. if os.path.isfile(f'{mkdir_path}/有效硫分析图.png'):
  1091. doc.add_picture(f'{mkdir_path}/有效硫分析图.png', width=Inches(6.0))
  1092. if os.path.isfile(f'{mkdir_path}/有效锰分析图.png'):
  1093. doc.add_picture(f'{mkdir_path}/有效锰分析图.png', width=Inches(6.0))
  1094. if os.path.isfile(f'{mkdir_path}/有效钼分析图.png'):
  1095. doc.add_picture(f'{mkdir_path}/有效钼分析图.png', width=Inches(6.0))
  1096. if os.path.isfile(f'{mkdir_path}/有效硼分析图.png'):
  1097. doc.add_picture(f'{mkdir_path}/有效硼分析图.png', width=Inches(6.0))
  1098. if os.path.isfile(f'{mkdir_path}/有效铁分析图.png'):
  1099. doc.add_picture(f'{mkdir_path}/有效铁分析图.png', width=Inches(6.0))
  1100. if os.path.isfile(f'{mkdir_path}/有效铜分析图.png'):
  1101. doc.add_picture(f'{mkdir_path}/有效铜分析图.png', width=Inches(6.0))
  1102. if os.path.isfile(f'{mkdir_path}/有效锌分析图.png'):
  1103. doc.add_picture(f'{mkdir_path}/有效锌分析图.png', width=Inches(6.0))
  1104. doc.add_heading('附表4:数值修约标准', level=2)
  1105. # 读取数据 插入表格 写入数据
  1106. numData = pd.read_excel('./img/数值修约要求.xlsx', sheet_name='Sheet1')
  1107. table_2_f = doc.add_table(rows=len(numData) + 1, cols=2, style='Light Shading Accent 1')
  1108. table_2_f.alignment = WD_TABLE_ALIGNMENT.CENTER
  1109. for i, row in enumerate(table_2_f.rows):
  1110. for j, cell in enumerate(row.cells):
  1111. # 获取单元格中的段落对象
  1112. paragraph = cell.paragraphs[0]
  1113. if i == 0:
  1114. r = paragraph.add_run(str(numData.columns[j]))
  1115. r.font.bold = True
  1116. else:
  1117. r = paragraph.add_run(str(numData.iloc[i - 1, j]))
  1118. r.font.size = Pt(10.5)
  1119. r.font.name = 'Times New Roman'
  1120. r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  1121. paragraph.alignment = WD_PARAGRAPH_ALIGNMENT.CENTER
  1122. paragraph.paragraph_format.alignment = WD_TABLE_ALIGNMENT.CENTER # 对齐
  1123. paragraph.paragraph_format.line_spacing = 1 # 段落行间距
  1124. # 处理样式 遍历所有的段落 修改字体
  1125. # 遍历并打印每个段落的文本
  1126. paragraphs = doc.paragraphs
  1127. for paragraph in paragraphs:
  1128. for run in paragraph.runs:
  1129. run.font.color.rgb = RGBColor(0, 0, 0)
  1130. run.font.name = 'Times New Roman'
  1131. run.font.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  1132. # 保存Word文档
  1133. doc.save(f'{mkdir_path}/{areaName}-{type}审核报告.docx')
  1134. # 生成一般化学性指标审核报告
  1135. def getChemicalIndicators(data,type, changeFileUrl, saveFileUrl, check_1_data,
  1136. check_3_data,
  1137. check_5_data,
  1138. check_8_data, # 样品编号替换为编号
  1139. check_10_data,
  1140. check_12_data,
  1141. check_14_data):
  1142. # 生成报告
  1143. name = os.path.basename(changeFileUrl)
  1144. n = name.split('.')
  1145. areaName = n[0].replace('数据', '')
  1146. # 生成一个新的文件夹用于存放审核报告相关的数据
  1147. nowTime = time.strftime("%Y-%m-%d %H时%M分%S秒", time.localtime())
  1148. dir_name = f'{areaName}-{type}数据审核报告'
  1149. mkdir_path = saveFileUrl + '/' + dir_name + nowTime
  1150. if not os.path.exists(mkdir_path):
  1151. os.mkdir(mkdir_path)
  1152. # 根据选择的路径读取数据
  1153. cheemicalData = data[indexClassificationList[type]]
  1154. report.getFrequencyImage(cheemicalData, mkdir_path)
  1155. cheemicalData['序号'] = data['序号']
  1156. cheemicalData['原样品编号'] = data['原样品编号']
  1157. cheemicalData['样品编号'] = data['样品编号']
  1158. cheemicalData['地理位置'] = data['地理位置']
  1159. cheemicalData['母质'] = data['母质']
  1160. cheemicalData['土壤类型'] = data['土壤类型']
  1161. cheemicalData['土地利用类型'] = data['土地利用类型']
  1162. # cheemicalData['土壤质地'] = data['土壤质地']
  1163. cheemicalData['原样品编号'] = cheemicalData['原样品编号'].astype(str)
  1164. # checkData = pd.read_excel(changeFileUrl, sheet_name='检测方法')
  1165. # 上面这个地址,可以纯递给函数中,用于保存表格和图片
  1166. # 调用函数 开始生成报告相关内容
  1167. # 表1相关数据
  1168. typeData = report.getSimpleNum(cheemicalData)
  1169. lenNum_1 = len(typeData['sData'])
  1170. lenNum_1_f = len(typeData['allData'])
  1171. table_1_data = pd.DataFrame({
  1172. '类型': typeData['sData'].index,
  1173. '数量': typeData['sData'],
  1174. '合计': [typeData['sData'].sum() for _ in range(lenNum_1)]
  1175. })
  1176. # 表2数据
  1177. table_2_data = report.getDataComplete(cheemicalData)
  1178. table_2_data = table_2_data.reset_index()
  1179. table_2_data.columns = ['指标名称', '实测数量', '应测数量']
  1180. # 表3数据
  1181. # table_3_data = report.checkMethod(checkData, mkdir_path)
  1182. # 数据修约 表4
  1183. report.getNum(cheemicalData, mkdir_path)
  1184. # 数据填报项审核 表5
  1185. report.dataReportResult(cheemicalData, mkdir_path)
  1186. # 表6数据 土壤质地类型不一致
  1187. middData = data[['原样品编号', '样品编号']].astype(str)
  1188. middData['编号'] = middData['原样品编号']
  1189. del middData['原样品编号']
  1190. check_1_data = pd.merge(check_1_data, middData, how='left', on='编号')
  1191. check_1_data = check_1_data.replace(np.nan, '')
  1192. # typeNotSame = check_1_data[check_1_data['土壤质地'] != check_1_data['土壤类型(判断)']]
  1193. # table_6_data = typeNotSame[['编号', '样品编号', '土壤质地', '土壤类型(判断)']]
  1194. allNeedData = pd.DataFrame({})
  1195. allNeedData['原样品编号'] = check_1_data['编号']
  1196. getSimpleDataNumber = pd.merge(allNeedData, data[['原样品编号', '样品编号']], how='left', on="原样品编号")
  1197. allNeedData['样品编号'] = getSimpleDataNumber['样品编号']
  1198. allNeedData['土地利用类型'] = check_1_data['土地利用类型']
  1199. allNeedData['审核结果'] = check_5_data['审核结果'] + check_8_data['审核结果']
  1200. allNeedData['外业'] = ['' for _ in range(len(check_1_data))]
  1201. table_7_data = allNeedData[allNeedData['审核结果'] != '']
  1202. del table_7_data['审核结果']
  1203. # 写进表格
  1204. with pd.ExcelWriter(f'{mkdir_path}/超阈值样品统计表.xlsx', engine='openpyxl') as writer:
  1205. table_7_data.to_excel(writer, index=False, sheet_name='超阈值数据')
  1206. # 表8数据
  1207. table_8_data = report.getPHData(cheemicalData, mkdir_path)
  1208. report.cationExchangeCapacity(cheemicalData, mkdir_path)
  1209. report.changeCation(cheemicalData, mkdir_path)
  1210. report.manyTypes(cheemicalData, mkdir_path)
  1211. # 有效态异常数据
  1212. errObj = report.orderData(data)
  1213. # 表13 所有存疑数据
  1214. with pd.ExcelWriter(f'{mkdir_path}/数据审核过程存疑数据一览表.xlsx', engine='openpyxl') as writer:
  1215. allNeedData[allNeedData['审核结果'] != ''].to_excel(writer, index=False, sheet_name='存疑数据')
  1216. # 附表: 频度分析图
  1217. # report.getFrequencyImage(cheemicalData, mkdir_path)
  1218. table_f_2_data = report.getFrequencyInformation(data, mkdir_path)
  1219. # 新建一个文档
  1220. doc = Document()
  1221. # 添加标题
  1222. doc.add_heading(f"{areaName}第三次全国土壤普查数据审核报告", level=0)
  1223. # 添加一级标题
  1224. doc.add_heading('一、数据完整性审核', level=1)
  1225. doc.add_heading('1、土地利用类型与检测指标符合性审核', level=2)
  1226. # 插入表格1
  1227. paragraph_1 = doc.add_paragraph()
  1228. paragraph_1.add_run(f"表1:{areaName}三普样品数量统计表(表层)").bold = True
  1229. # 设置居中
  1230. paragraph_1.alignment = WD_ALIGN_PARAGRAPH.CENTER
  1231. table_1 = doc.add_table(rows=lenNum_1 + 1, cols=3, style='Light Shading Accent 1')
  1232. table_1.alignment = WD_TABLE_ALIGNMENT.CENTER
  1233. # 遍历表格 插入数据
  1234. # 遍历表格的所有单元格,并填充内容
  1235. for i, row in enumerate(table_1.rows):
  1236. for j, cell in enumerate(row.cells):
  1237. # 获取单元格中的段落对象
  1238. paragraph = cell.paragraphs[0]
  1239. if i == 0:
  1240. r = paragraph.add_run(str(table_1_data.columns[j]))
  1241. r.font.bold = True
  1242. else:
  1243. r = paragraph.add_run(str(table_1_data.iloc[i - 1, j]))
  1244. r.font.size = Pt(10.5)
  1245. r.font.name = 'Times New Roman'
  1246. r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  1247. paragraph.alignment = WD_PARAGRAPH_ALIGNMENT.CENTER
  1248. paragraph.paragraph_format.alignment = WD_TABLE_ALIGNMENT.CENTER # 对齐
  1249. paragraph.paragraph_format.line_spacing = 1 # 段落行间距
  1250. # 合并单元格 合并第3列的第二行和第三行
  1251. if lenNum_1 > 1:
  1252. table_1.cell(2, 2).text = ''
  1253. table_1.cell(1, 2).merge(table_1.cell(2, 2))
  1254. ############test##############
  1255. doc.add_heading('2、指标名称与实际检测样品数量完整性审核', level=2)
  1256. # 插入表格2
  1257. paragraph_2 = doc.add_paragraph()
  1258. paragraph_2.add_run(f'表2:{areaName}指标名称与实际检测样品数量统计表').bold = True
  1259. table_2 = doc.add_table(rows=len(table_2_data) + 1, cols=3, style='Light Shading Accent 1')
  1260. paragraph_2.alignment = WD_ALIGN_PARAGRAPH.CENTER
  1261. table_2.alignment = WD_TABLE_ALIGNMENT.CENTER
  1262. for i, row in enumerate(table_2.rows):
  1263. for j, cell in enumerate(row.cells):
  1264. # 获取单元格中的段落对象
  1265. paragraph = cell.paragraphs[0]
  1266. if i == 0:
  1267. r = paragraph.add_run(str(table_2_data.columns[j]))
  1268. r.font.bold = True
  1269. else:
  1270. r = paragraph.add_run(str(table_2_data.iloc[i - 1, j]))
  1271. paragraph.alignment = WD_PARAGRAPH_ALIGNMENT.CENTER
  1272. paragraph.paragraph_format.alignment = WD_TABLE_ALIGNMENT.CENTER # 对齐
  1273. paragraph.paragraph_format.line_spacing = 1 # 段落行间距
  1274. r.font.size = Pt(10.5)
  1275. r.font.name = 'Times New Roman'
  1276. r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  1277. doc.add_heading('二、数据规范性审核', level=1)
  1278. doc.add_heading('1、数据填报规范性审核', level=2)
  1279. # 插入表3
  1280. paragraph_3 = doc.add_paragraph()
  1281. paragraph_3.add_run(f'表3:{areaName}土壤检测数据检测方法填报审核结果表').bold = True
  1282. # table_3 = doc.add_table(rows=2, cols=2)
  1283. paragraph_3.alignment = WD_ALIGN_PARAGRAPH.CENTER
  1284. # table_3.alignment = WD_TABLE_ALIGNMENT.CENTER
  1285. # 写入数据 这里数据写不下 嵌入链接
  1286. doc.add_heading('为避免数据量过多无法显示,请至数据保存文件夹中查看数据表:检测方法审核结果.xlsx', level=4)
  1287. doc.add_heading('2、数值修约规范性审核', level=2)
  1288. # 插入表4
  1289. paragraph_4 = doc.add_paragraph()
  1290. paragraph_4.add_run(f'表4:{areaName}土壤检测数据数值修约结果表').bold = True
  1291. # table_4 = doc.add_table(rows=2, cols=2)
  1292. paragraph_4.alignment = WD_ALIGN_PARAGRAPH.CENTER
  1293. # table_4.alignment = WD_TABLE_ALIGNMENT.CENTER
  1294. doc.add_heading('为避免数据量过多无法显示,请至数据保存文件夹中查看数据表:数值修约审核.xlsx', level=4)
  1295. # 填入数据 这里数据也放不下 嵌入链接
  1296. doc.add_heading('3、数据未检出的填报规范性审核', level=2)
  1297. # 插入表5
  1298. paragraph_5 = doc.add_paragraph()
  1299. paragraph_5.add_run(f'表5:{areaName}土壤检测数据未检出项填报审核结果表').bold = True
  1300. # table_5 = doc.add_table(rows=2, cols=2)
  1301. paragraph_5.alignment = WD_ALIGN_PARAGRAPH.CENTER
  1302. # table_5.alignment = WD_TABLE_ALIGNMENT.CENTER
  1303. # 写入数据 这里数据也放不下 嵌入链接
  1304. doc.add_heading('为避免数据量过多无法显示,请至数据保存文件夹中查看数据表:数据填报项审核结果.xlsx', level=4)
  1305. # doc.add_heading('4、土壤质地填报规范性审核', level=2)
  1306. # 插入表6
  1307. # paragraph_6 = doc.add_paragraph()
  1308. # paragraph_6.add_run(f'表6:{areaName}土壤质地填报审核结果表').bold = True
  1309. # table_6 = doc.add_table(rows=len(table_6_data) + 1, cols=4, style='Light Shading Accent 1')
  1310. # paragraph_6.alignment = WD_ALIGN_PARAGRAPH.CENTER
  1311. # table_6.alignment = WD_TABLE_ALIGNMENT.CENTER
  1312. # # 提取结果表中数据
  1313. # # 写入数据 土壤质地类型不一致的数据提取出来
  1314. # for i, row in enumerate(table_6.rows):
  1315. # for j, cell in enumerate(row.cells):
  1316. # # 获取单元格中的段落对象
  1317. # paragraph = cell.paragraphs[0]
  1318. # if i == 0:
  1319. # r = paragraph.add_run(str(table_6_data.columns[j]))
  1320. # r.font.bold = True
  1321. # else:
  1322. # r = paragraph.add_run(str(table_6_data.iloc[i - 1, j]))
  1323. # paragraph.alignment = WD_PARAGRAPH_ALIGNMENT.CENTER
  1324. # paragraph.paragraph_format.alignment = WD_TABLE_ALIGNMENT.CENTER # 对齐
  1325. # paragraph.paragraph_format.line_spacing = 1 # 段落行间距
  1326. # r.font.size = Pt(10.5)
  1327. # r.font.name = 'Times New Roman'
  1328. # r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  1329. doc.add_heading('三、数据合理性审核', level=1)
  1330. doc.add_heading('1、阈值法审核', level=2)
  1331. # 插入表格
  1332. paragraph_7 = doc.add_paragraph()
  1333. paragraph_7.add_run(f'表6:{areaName}土壤检测数据超阈值样品统计表').bold = True
  1334. # table_7 = doc.add_table(rows=2, cols=2)
  1335. # paragraph_7.alignment = WD_ALIGN_PARAGRAPH.CENTER
  1336. # table_7.alignment = WD_TABLE_ALIGNMENT.CENTER
  1337. # 写入数据 点击查看数据 这里也不一定写的下 最好是嵌入链接
  1338. doc.add_heading('为避免数据量过多无法显示,请至数据保存文件夹中查看数据表:数据审核过程存疑数据一览表.xlsx', level=4)
  1339. # todo 合并所有数据 审核结果不为空的数据 写入表格保存到指定文件夹
  1340. doc.add_heading('2、极值法审核', level=2)
  1341. doc.add_heading('(1)pH', level=3)
  1342. # 插入ph分布图
  1343. if os.path.isfile(f'{mkdir_path}/PH值分布图.png'):
  1344. doc.add_picture(f'{mkdir_path}/PH值分布图.png', width=Inches(6.0))
  1345. paragraph_t_1 = doc.add_paragraph()
  1346. paragraph_t_1.add_run(f'图1:pH值分布情况').bold = True
  1347. paragraph_t_1.alignment = WD_ALIGN_PARAGRAPH.CENTER
  1348. # 插入频度统计表
  1349. paragraph_8 = doc.add_paragraph()
  1350. paragraph_8.add_run('表7:pH数据统计表').bold = True
  1351. table_8 = doc.add_table(rows=6, cols=2, style='Light Shading Accent 1')
  1352. t_8 = table_8_data['频度分析']
  1353. t_8 = t_8.reset_index()
  1354. t_8.columns = ['指标', '数据']
  1355. paragraph_8.alignment = WD_ALIGN_PARAGRAPH.CENTER
  1356. table_8.alignment = WD_TABLE_ALIGNMENT.CENTER
  1357. for i, row in enumerate(table_8.rows):
  1358. for j, cell in enumerate(row.cells):
  1359. # 获取单元格中的段落对象
  1360. paragraph = cell.paragraphs[0]
  1361. if i == 0:
  1362. r = paragraph.add_run(str(t_8.columns[j]))
  1363. r.font.bold = True
  1364. else:
  1365. r = paragraph.add_run(str(t_8.iloc[i - 1, j]))
  1366. r.font.size = Pt(10.5)
  1367. r.font.name = 'Times New Roman'
  1368. r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  1369. paragraph.alignment = WD_PARAGRAPH_ALIGNMENT.CENTER
  1370. paragraph.paragraph_format.alignment = WD_TABLE_ALIGNMENT.CENTER # 对齐
  1371. paragraph.paragraph_format.line_spacing = 1 # 段落行间距
  1372. # 插入异常数据提取表格 todo 这里数据多的话也可能写不下 最好是嵌入一下
  1373. if not table_8_data['异常数据'].empty:
  1374. paragraph_9 = doc.add_paragraph()
  1375. paragraph_9.add_run('表8:pH异常数据统计表').bold = True
  1376. table_9 = doc.add_table(rows=len(table_8_data['异常数据']) + 1, cols=6, style='Light Shading Accent 1')
  1377. t_9 = table_8_data['异常数据']
  1378. paragraph_9.alignment = WD_ALIGN_PARAGRAPH.CENTER
  1379. table_9.alignment = WD_TABLE_ALIGNMENT.CENTER
  1380. for i, row in enumerate(table_9.rows):
  1381. for j, cell in enumerate(row.cells):
  1382. # 获取单元格中的段落对象
  1383. paragraph = cell.paragraphs[0]
  1384. if i == 0:
  1385. r = paragraph.add_run(str(t_9.columns[j]))
  1386. r.font.bold = True
  1387. else:
  1388. r = paragraph.add_run(str(t_9.iloc[i - 1, j]))
  1389. r.font.size = Pt(10.5)
  1390. r.font.name = 'Times New Roman'
  1391. r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  1392. paragraph.alignment = WD_PARAGRAPH_ALIGNMENT.CENTER
  1393. paragraph.paragraph_format.alignment = WD_TABLE_ALIGNMENT.CENTER # 对齐
  1394. paragraph.paragraph_format.line_spacing = 1 # 段落行间距
  1395. doc.add_heading('3、指标综合分析', level=2)
  1396. # 阳离子交换量与交换性盐总量关系
  1397. if os.path.isfile(f'{mkdir_path}/阳离子交换量与交换性盐基总量相关关系.png'):
  1398. doc.add_picture(f'{mkdir_path}/阳离子交换量与交换性盐基总量相关关系.png', width=Inches(6.0))
  1399. paragraph_t_8 = doc.add_paragraph()
  1400. paragraph_t_8.add_run(f'图8:阳离子交换量与交换性盐总量关系图').bold = True
  1401. paragraph_t_8.alignment = WD_ALIGN_PARAGRAPH.CENTER
  1402. # 交换性盐总量与交换性盐相关关系
  1403. if os.path.isfile(f'{mkdir_path}/交换性盐基总量与交换性盐相关关系(pH小于等于7.5).png'):
  1404. doc.add_picture(f'{mkdir_path}/交换性盐基总量与交换性盐相关关系(pH小于等于7.5).png', width=Inches(6.0))
  1405. paragraph_t_9 = doc.add_paragraph()
  1406. paragraph_t_9.add_run(f'图9:交换性盐基总量和交换性钙镁钠钾分项指标关系(pH≤7.5)').bold = True
  1407. paragraph_t_9.alignment = WD_ALIGN_PARAGRAPH.CENTER
  1408. if os.path.isfile(f'{mkdir_path}/交换性盐基总量与交换性盐相关关系(pH大于7.5).png'):
  1409. doc.add_picture(f'{mkdir_path}/交换性盐基总量与交换性盐相关关系(pH大于7.5).png', width=Inches(6.0))
  1410. paragraph_t_10 = doc.add_paragraph()
  1411. paragraph_t_10.add_run(f'图10:交换性盐基总量和交换性钙镁钠钾分项指标关系(pH大于7.5)').bold = True
  1412. paragraph_t_10.alignment = WD_ALIGN_PARAGRAPH.CENTER
  1413. # 水溶性盐、电导率、离子总量
  1414. if os.path.isfile(f'{mkdir_path}/全盐量分布图.png'):
  1415. doc.add_picture(f'{mkdir_path}/全盐量分布图.png', width=Inches(6.0))
  1416. paragraph_t_11 = doc.add_paragraph()
  1417. paragraph_t_11.add_run(f'图11:全盐量分布图').bold = True
  1418. paragraph_t_11.alignment = WD_ALIGN_PARAGRAPH.CENTER
  1419. if os.path.isfile(f'{mkdir_path}/全盐量与电导率相关性分析图.png'):
  1420. doc.add_picture(f'{mkdir_path}/全盐量与电导率相关性分析图.png', width=Inches(6.0))
  1421. paragraph_t_12 = doc.add_paragraph()
  1422. paragraph_t_12.add_run(f'图12:全盐量与电导率相关性分析图').bold = True
  1423. paragraph_t_12.alignment = WD_ALIGN_PARAGRAPH.CENTER
  1424. if os.path.isfile(f'{mkdir_path}/离子总量与水溶性盐总量关系图.png'):
  1425. doc.add_picture(f'{mkdir_path}/离子总量与水溶性盐总量关系图.png', width=Inches(6.0))
  1426. paragraph_t_13 = doc.add_paragraph()
  1427. paragraph_t_13.add_run(f'图13:水溶性盐总量与离子总量关系分析图').bold = True
  1428. paragraph_t_13.alignment = WD_ALIGN_PARAGRAPH.CENTER
  1429. # 这里添加新增的剖面数据指标 添加异常数据表和折线图
  1430. # if not errObj['errData'].empty:
  1431. # errData = errObj['errData']
  1432. # errName = errObj['errName']
  1433. # errName.insert(0, '原样品编号')
  1434. # paragraph_12 = doc.add_paragraph()
  1435. # paragraph_12.add_run('表9:有效态元素异常样品统计表').bold = True
  1436. # table_12 = doc.add_table(rows=len(errData)+1, cols=len(errName), style='Light Shading Accent 1')
  1437. # paragraph_12.alignment = WD_ALIGN_PARAGRAPH.CENTER
  1438. # table_12.alignment = WD_TABLE_ALIGNMENT.CENTER
  1439. # for i, row in enumerate(table_12.rows):
  1440. # for j, cell in enumerate(row.cells):
  1441. # # 获取单元格中的段落对象
  1442. # paragraph = cell.paragraphs[0]
  1443. # if i == 0:
  1444. # r = paragraph.add_run(str(errData[errName].columns[j]))
  1445. # r.font.bold = True
  1446. # else:
  1447. # r=paragraph.add_run(str(errData[errName].iloc[i-1, j]))
  1448. #
  1449. # r.font.size = Pt(10.5)
  1450. # r.font.name = 'Times New Roman'
  1451. # r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  1452. # paragraph.alignment = WD_PARAGRAPH_ALIGNMENT.CENTER
  1453. # paragraph.paragraph_format.alignment = WD_TABLE_ALIGNMENT.CENTER # 对齐
  1454. # paragraph.paragraph_format.line_spacing = 1 # 段落行间距
  1455. # else:
  1456. # paragraph_12 = doc.add_paragraph()
  1457. # paragraph_12.add_run('表9:有效态元素异常样品统计表').bold = True
  1458. # paragraph_12_info = doc.add_paragraph()
  1459. # paragraph_12_info.add_run('无异常数据')
  1460. # paragraph_12.alignment = WD_ALIGN_PARAGRAPH.CENTER
  1461. # paragraph_12_info.alignment = WD_ALIGN_PARAGRAPH.CENTER
  1462. # 新增剖面指标 显示异常有效态数据折线图及
  1463. if os.path.isfile(f'{mkdir_path}/有效态指标异常统计图.png'):
  1464. doc.add_picture(f'{mkdir_path}/有效态指标异常统计图.png', width=Inches(6.0))
  1465. paragraph_t_14 = doc.add_paragraph()
  1466. paragraph_t_14.add_run(f'图14:有效态指标异常统计图').bold = True
  1467. paragraph_t_14.alignment = WD_ALIGN_PARAGRAPH.CENTER
  1468. doc.add_heading('四、审核存疑数据', level=1)
  1469. paragraph_12 = doc.add_paragraph()
  1470. paragraph_12.add_run(f'表9:数据审核过程存疑数据一览表').bold = True
  1471. paragraph_12.alignment = WD_ALIGN_PARAGRAPH.CENTER
  1472. doc.add_heading('为避免数据量过多无法显示,请至数据保存文件夹中查看数据表:数据审核过程存疑数据一览表.xlsx', level=4)
  1473. doc.add_heading('五、附表', level=1)
  1474. doc.add_heading('附表1:某区三普样品数量统计表(表层)', level=2)
  1475. # 插入附表1
  1476. table_1_f = doc.add_table(rows=lenNum_1 + 1, cols=3, style='Light Shading Accent 1')
  1477. table_1_f.alignment = WD_TABLE_ALIGNMENT.CENTER
  1478. # 遍历表格 插入数据
  1479. # 遍历表格的所有单元格,并填充内容
  1480. for i, row in enumerate(table_1_f.rows):
  1481. for j, cell in enumerate(row.cells):
  1482. # 获取单元格中的段落对象
  1483. paragraph = cell.paragraphs[0]
  1484. if i == 0:
  1485. r = paragraph.add_run(str(table_1_data.columns[j]))
  1486. r.font.bold = True
  1487. else:
  1488. r = paragraph.add_run(str(table_1_data.iloc[i - 1, j]))
  1489. r.font.size = Pt(10.5)
  1490. r.font.name = 'Times New Roman'
  1491. r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  1492. paragraph.alignment = WD_PARAGRAPH_ALIGNMENT.CENTER
  1493. paragraph.paragraph_format.alignment = WD_TABLE_ALIGNMENT.CENTER # 对齐
  1494. paragraph.paragraph_format.line_spacing = 1 # 段落行间距
  1495. # 合并单元格 合并第3列的第二行和第三行
  1496. if lenNum_1 > 1:
  1497. table_1_f.cell(2, 2).text = ''
  1498. table_1_f.cell(1, 2).merge(table_1_f.cell(2, 2))
  1499. doc.add_heading('附表2:各指标频度分析表', level=2)
  1500. # 插入表格 写入数据
  1501. table_f_2_data = table_f_2_data.replace(np.nan, '')
  1502. makeInfoTable(table_f_2_data, doc)
  1503. # table_f_2 = doc.add_table(rows=len(table_f_2_data) + 1, cols=6, style='Light Shading Accent 1')
  1504. # for i, row in enumerate(table_f_2.rows):
  1505. # for j, cell in enumerate(row.cells):
  1506. # # 获取单元格中的段落对象
  1507. # paragraph = cell.paragraphs[0]
  1508. # if i == 0:
  1509. # r = paragraph.add_run(str(table_f_2_data.columns[j]))
  1510. # r.font.bold = True
  1511. # else:
  1512. # r = paragraph.add_run(str(table_f_2_data.iloc[i - 1, j]))
  1513. # r.font.size = Pt(10.5)
  1514. # r.font.name = 'Times New Roman'
  1515. # r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  1516. # paragraph.alignment = WD_PARAGRAPH_ALIGNMENT.CENTER
  1517. # paragraph.paragraph_format.alignment = WD_TABLE_ALIGNMENT.CENTER # 对齐
  1518. # paragraph.paragraph_format.line_spacing = 1 # 段落行间距
  1519. # doc.add_heading('为避免数据量过多无法显示,请至数据保存文件夹中查看数据表:频度分析表.xlsx', level=4)
  1520. doc.add_heading('附表3:各指标频度分析图', level=2)
  1521. # 插入频度信息的图形
  1522. if os.path.isfile(f'{mkdir_path}/pH分析图.png'):
  1523. doc.add_picture(f'{mkdir_path}/pH分析图.png', width=Inches(6.0))
  1524. if os.path.isfile(f'{mkdir_path}/电导率分析图.png'):
  1525. doc.add_picture(f'{mkdir_path}/电导率分析图.png', width=Inches(6.0))
  1526. if os.path.isfile(f'{mkdir_path}/交换性钙分析图.png'):
  1527. doc.add_picture(f'{mkdir_path}/交换性钙分析图.png', width=Inches(6.0))
  1528. if os.path.isfile(f'{mkdir_path}/交换性钾分析图.png'):
  1529. doc.add_picture(f'{mkdir_path}/交换性钾分析图.png', width=Inches(6.0))
  1530. if os.path.isfile(f'{mkdir_path}/交换性镁分析图.png'):
  1531. doc.add_picture(f'{mkdir_path}/交换性镁分析图.png', width=Inches(6.0))
  1532. if os.path.isfile(f'{mkdir_path}/交换性钠分析图.png'):
  1533. doc.add_picture(f'{mkdir_path}/交换性钠分析图.png', width=Inches(6.0))
  1534. if os.path.isfile(f'{mkdir_path}/交换性盐基总量分析图.png'):
  1535. doc.add_picture(f'{mkdir_path}/交换性盐基总量分析图.png', width=Inches(6.0))
  1536. if os.path.isfile(f'{mkdir_path}/全盐量分析图.png'):
  1537. doc.add_picture(f'{mkdir_path}/全盐量分析图.png', width=Inches(6.0))
  1538. if os.path.isfile(f'{mkdir_path}/阳离子交换量分析图.png'):
  1539. doc.add_picture(f'{mkdir_path}/阳离子交换量分析图.png', width=Inches(6.0))
  1540. # 新增的剖面指标
  1541. if os.path.isfile(f'{mkdir_path}/全硫分析图.png'):
  1542. doc.add_picture(f'{mkdir_path}/全硫分析图.png', width=Inches(6.0))
  1543. if os.path.isfile(f'{mkdir_path}/全硅分析图.png'):
  1544. doc.add_picture(f'{mkdir_path}/全硅分析图.png', width=Inches(6.0))
  1545. if os.path.isfile(f'{mkdir_path}/全钙分析图.png'):
  1546. doc.add_picture(f'{mkdir_path}/全钙分析图.png', width=Inches(6.0))
  1547. if os.path.isfile(f'{mkdir_path}/全镁分析图.png'):
  1548. doc.add_picture(f'{mkdir_path}/全镁分析图.png', width=Inches(6.0))
  1549. if os.path.isfile(f'{mkdir_path}/全铝分析图.png'):
  1550. doc.add_picture(f'{mkdir_path}/全铝分析图.png', width=Inches(6.0))
  1551. if os.path.isfile(f'{mkdir_path}/全铁分析图.png'):
  1552. doc.add_picture(f'{mkdir_path}/全铁分析图.png', width=Inches(6.0))
  1553. if os.path.isfile(f'{mkdir_path}/全锰分析图.png'):
  1554. doc.add_picture(f'{mkdir_path}/全锰分析图.png', width=Inches(6.0))
  1555. if os.path.isfile(f'{mkdir_path}/全铜分析图.png'):
  1556. doc.add_picture(f'{mkdir_path}/全铜分析图.png', width=Inches(6.0))
  1557. if os.path.isfile(f'{mkdir_path}/全锌分析图.png'):
  1558. doc.add_picture(f'{mkdir_path}/全锌分析图.png', width=Inches(6.0))
  1559. if os.path.isfile(f'{mkdir_path}/全硼分析图.png'):
  1560. doc.add_picture(f'{mkdir_path}/全硼分析图.png', width=Inches(6.0))
  1561. if os.path.isfile(f'{mkdir_path}/全钼分析图.png'):
  1562. doc.add_picture(f'{mkdir_path}/全钼分析图.png', width=Inches(6.0))
  1563. if os.path.isfile(f'{mkdir_path}/全锌分析图.png'):
  1564. doc.add_picture(f'{mkdir_path}/全锌分析图.png', width=Inches(6.0))
  1565. if os.path.isfile(f'{mkdir_path}/碳酸钙分析图.png'):
  1566. doc.add_picture(f'{mkdir_path}/碳酸钙分析图.png', width=Inches(6.0))
  1567. if os.path.isfile(f'{mkdir_path}/游离铁分析图.png'):
  1568. doc.add_picture(f'{mkdir_path}/游离铁分析图.png', width=Inches(6.0))
  1569. doc.add_heading('附表4:数值修约标准', level=2)
  1570. # 读取数据 插入表格 写入数据
  1571. numData = pd.read_excel('./img/数值修约要求.xlsx', sheet_name='Sheet1')
  1572. table_2_f = doc.add_table(rows=len(numData) + 1, cols=2, style='Light Shading Accent 1')
  1573. table_2_f.alignment = WD_TABLE_ALIGNMENT.CENTER
  1574. for i, row in enumerate(table_2_f.rows):
  1575. for j, cell in enumerate(row.cells):
  1576. # 获取单元格中的段落对象
  1577. paragraph = cell.paragraphs[0]
  1578. if i == 0:
  1579. r = paragraph.add_run(str(numData.columns[j]))
  1580. r.font.bold = True
  1581. else:
  1582. r = paragraph.add_run(str(numData.iloc[i - 1, j]))
  1583. r.font.size = Pt(10.5)
  1584. r.font.name = 'Times New Roman'
  1585. r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  1586. paragraph.alignment = WD_PARAGRAPH_ALIGNMENT.CENTER
  1587. paragraph.paragraph_format.alignment = WD_TABLE_ALIGNMENT.CENTER # 对齐
  1588. paragraph.paragraph_format.line_spacing = 1 # 段落行间距
  1589. # 处理样式 遍历所有的段落 修改字体
  1590. # 遍历并打印每个段落的文本
  1591. paragraphs = doc.paragraphs
  1592. for paragraph in paragraphs:
  1593. for run in paragraph.runs:
  1594. run.font.color.rgb = RGBColor(0, 0, 0)
  1595. run.font.name = 'Times New Roman'
  1596. run.font.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  1597. # run.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  1598. # 保存Word文档
  1599. doc.save(f'{mkdir_path}/{areaName}审核报告.docx')
  1600. # 生成重金属指标审核报告
  1601. def getHeavyMetalIndicators(data, type, changeFileUrl, saveFileUrl, check_1_data,
  1602. check_3_data,
  1603. check_5_data,
  1604. check_8_data, # 样品编号替换为编号
  1605. check_10_data,
  1606. check_12_data,
  1607. check_14_data):
  1608. # 生成报告
  1609. name = os.path.basename(changeFileUrl)
  1610. n = name.split('.')
  1611. areaName = n[0].replace('数据', '')
  1612. # 生成一个新的文件夹用于存放审核报告相关的数据
  1613. nowTime = time.strftime("%Y-%m-%d %H时%M分%S秒", time.localtime())
  1614. dir_name = f'{areaName}-{type}数据审核报告'
  1615. mkdir_path = saveFileUrl + '/' + dir_name + nowTime
  1616. if not os.path.exists(mkdir_path):
  1617. os.mkdir(mkdir_path)
  1618. heavyMetaData = data[indexClassificationList[type]]
  1619. report.getFrequencyImage(heavyMetaData, mkdir_path)
  1620. heavyMetaData['序号'] = data['序号']
  1621. heavyMetaData['原样品编号'] = data['原样品编号']
  1622. heavyMetaData['样品编号'] = data['样品编号']
  1623. heavyMetaData['地理位置'] = data['地理位置']
  1624. heavyMetaData['母质'] = data['母质']
  1625. heavyMetaData['土壤类型'] = data['土壤类型']
  1626. heavyMetaData['土地利用类型'] = data['土地利用类型']
  1627. # heavyMetaData['土壤质地'] = data['土壤质地']
  1628. heavyMetaData['原样品编号'] = heavyMetaData['原样品编号'].astype(str)
  1629. # checkData = pd.read_excel(changeFileUrl, sheet_name='检测方法')
  1630. # 上面这个地址,可以纯递给函数中,用于保存表格和图片
  1631. # 调用函数 开始生成报告相关内容
  1632. # 表1相关数据
  1633. typeData = report.getSimpleNum(heavyMetaData)
  1634. lenNum_1 = len(typeData['sData'])
  1635. lenNum_1_f = len(typeData['allData'])
  1636. table_1_data = pd.DataFrame({
  1637. '类型': typeData['sData'].index,
  1638. '数量': typeData['sData'],
  1639. '合计': [typeData['sData'].sum() for _ in range(lenNum_1)]
  1640. })
  1641. # 表2数据
  1642. table_2_data = report.getDataComplete(heavyMetaData)
  1643. table_2_data = table_2_data.reset_index()
  1644. table_2_data.columns = ['指标名称', '实测数量', '应测数量']
  1645. # 表3数据
  1646. # table_3_data = report.checkMethod(checkData, mkdir_path)
  1647. # 数据修约 表4
  1648. report.getNum(heavyMetaData, mkdir_path)
  1649. # 数据填报项审核 表5
  1650. report.dataReportResult(heavyMetaData, mkdir_path)
  1651. # 表6数据 土壤质地类型不一致
  1652. middData = heavyMetaData[['原样品编号', '样品编号']].astype(str)
  1653. middData['编号'] = middData['原样品编号']
  1654. del middData['原样品编号']
  1655. check_1_data = pd.merge(check_1_data, middData, how='left', on='编号')
  1656. check_1_data = check_1_data.replace(np.nan, '')
  1657. # typeNotSame = check_1_data[check_1_data['土壤质地'] != check_1_data['土壤类型(判断)']]
  1658. # table_6_data = typeNotSame[['编号', '样品编号', '土壤质地', '土壤类型(判断)']]
  1659. allNeedData = pd.DataFrame({})
  1660. allNeedData['原样品编号'] = check_1_data['编号']
  1661. getSimpleDataNumber = pd.merge(allNeedData, heavyMetaData[['原样品编号', '样品编号']], how='left', on="原样品编号")
  1662. allNeedData['样品编号'] = getSimpleDataNumber['样品编号']
  1663. allNeedData['土地利用类型'] = check_1_data['土地利用类型']
  1664. allNeedData['审核结果'] = check_14_data['审核结果']
  1665. allNeedData['外业'] = ['' for _ in range(len(check_1_data))]
  1666. table_7_data = allNeedData[allNeedData['审核结果'] != '']
  1667. del table_7_data['审核结果']
  1668. # 写进表格
  1669. with pd.ExcelWriter(f'{mkdir_path}/超阈值样品统计表.xlsx', engine='openpyxl') as writer:
  1670. table_7_data.to_excel(writer, index=False, sheet_name='超阈值数据')
  1671. # 表8数据
  1672. table_8_data = report.getPHData(heavyMetaData, mkdir_path)
  1673. # 表12数据 重金属超标
  1674. caOverData = pd.merge(check_1_data[['编号', '土地利用类型']], check_14_data[
  1675. ['编号', 'pH', '镉mg/kg', '汞mg/kg', '砷mg/kg', '铅mg/kg', '铬mg/kg', '镍mg/kg', '审核结果']], how='outer',
  1676. on=['编号'])
  1677. caOverData['原样品编号'] = caOverData['编号']
  1678. caOverData = pd.merge(caOverData, heavyMetaData[['原样品编号', '样品编号']], how='left', on='原样品编号')
  1679. first_column = caOverData.pop('样品编号')
  1680. caOverData.insert(0, '样品编号', first_column)
  1681. caOverData_need = caOverData[caOverData['审核结果'] != '']
  1682. # 写进表格
  1683. with pd.ExcelWriter(f'{mkdir_path}/重金属超筛选值情况统计.xlsx', engine='openpyxl') as writer:
  1684. caOverData_need.to_excel(writer, index=False, sheet_name='重金属超筛选值情况统计')
  1685. # 表13 所有存疑数据
  1686. with pd.ExcelWriter(f'{mkdir_path}/数据审核过程存疑数据一览表.xlsx', engine='openpyxl') as writer:
  1687. allNeedData[allNeedData['审核结果'] != ''].to_excel(writer, index=False, sheet_name='存疑数据')
  1688. # 附表: 频度分析图
  1689. # report.getFrequencyImage(heavyMetaData, mkdir_path)
  1690. table_f_2_data = report.getFrequencyInformation(data, mkdir_path)
  1691. # 新建一个文档
  1692. doc = Document()
  1693. # 添加标题
  1694. doc.add_heading(f"{areaName}第三次全国土壤普查数据审核报告", level=0)
  1695. # 添加一级标题
  1696. doc.add_heading('一、数据完整性审核', level=1)
  1697. doc.add_heading('1、土地利用类型与检测指标符合性审核', level=2)
  1698. # 插入表格1
  1699. paragraph_1 = doc.add_paragraph()
  1700. paragraph_1.add_run(f"表1:{areaName}三普样品数量统计表(表层)").bold = True
  1701. # 设置居中
  1702. paragraph_1.alignment = WD_ALIGN_PARAGRAPH.CENTER
  1703. table_1 = doc.add_table(rows=lenNum_1 + 1, cols=3, style='Light Shading Accent 1')
  1704. table_1.alignment = WD_TABLE_ALIGNMENT.CENTER
  1705. # 遍历表格 插入数据
  1706. # 遍历表格的所有单元格,并填充内容
  1707. for i, row in enumerate(table_1.rows):
  1708. for j, cell in enumerate(row.cells):
  1709. # 获取单元格中的段落对象
  1710. paragraph = cell.paragraphs[0]
  1711. if i == 0:
  1712. r = paragraph.add_run(str(table_1_data.columns[j]))
  1713. r.font.bold = True
  1714. else:
  1715. r = paragraph.add_run(str(table_1_data.iloc[i - 1, j]))
  1716. r.font.size = Pt(10.5)
  1717. r.font.name = 'Times New Roman'
  1718. r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  1719. paragraph.alignment = WD_PARAGRAPH_ALIGNMENT.CENTER
  1720. paragraph.paragraph_format.alignment = WD_TABLE_ALIGNMENT.CENTER # 对齐
  1721. paragraph.paragraph_format.line_spacing = 1 # 段落行间距
  1722. # 合并单元格 合并第3列的第二行和第三行
  1723. if lenNum_1 > 1:
  1724. table_1.cell(2, 2).text = ''
  1725. table_1.cell(1, 2).merge(table_1.cell(2, 2))
  1726. ############test##############
  1727. doc.add_heading('2、指标名称与实际检测样品数量完整性审核', level=2)
  1728. # 插入表格2
  1729. paragraph_2 = doc.add_paragraph()
  1730. paragraph_2.add_run(f'表2:{areaName}指标名称与实际检测样品数量统计表').bold = True
  1731. table_2 = doc.add_table(rows=len(table_2_data) + 1, cols=3, style='Light Shading Accent 1')
  1732. paragraph_2.alignment = WD_ALIGN_PARAGRAPH.CENTER
  1733. table_2.alignment = WD_TABLE_ALIGNMENT.CENTER
  1734. for i, row in enumerate(table_2.rows):
  1735. for j, cell in enumerate(row.cells):
  1736. # 获取单元格中的段落对象
  1737. paragraph = cell.paragraphs[0]
  1738. if i == 0:
  1739. r = paragraph.add_run(str(table_2_data.columns[j]))
  1740. r.font.bold = True
  1741. else:
  1742. r = paragraph.add_run(str(table_2_data.iloc[i - 1, j]))
  1743. paragraph.alignment = WD_PARAGRAPH_ALIGNMENT.CENTER
  1744. paragraph.paragraph_format.alignment = WD_TABLE_ALIGNMENT.CENTER # 对齐
  1745. paragraph.paragraph_format.line_spacing = 1 # 段落行间距
  1746. r.font.size = Pt(10.5)
  1747. r.font.name = 'Times New Roman'
  1748. r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  1749. doc.add_heading('二、数据规范性审核', level=1)
  1750. doc.add_heading('1、数据填报规范性审核', level=2)
  1751. # 插入表3
  1752. paragraph_3 = doc.add_paragraph()
  1753. paragraph_3.add_run(f'表3:{areaName}土壤检测数据检测方法填报审核结果表').bold = True
  1754. # table_3 = doc.add_table(rows=2, cols=2)
  1755. paragraph_3.alignment = WD_ALIGN_PARAGRAPH.CENTER
  1756. # table_3.alignment = WD_TABLE_ALIGNMENT.CENTER
  1757. # 写入数据 这里数据写不下 嵌入链接
  1758. doc.add_heading('为避免数据量过多无法显示,请至数据保存文件夹中查看数据表:检测方法审核结果.xlsx', level=4)
  1759. doc.add_heading('2、数值修约规范性审核', level=2)
  1760. # 插入表4
  1761. paragraph_4 = doc.add_paragraph()
  1762. paragraph_4.add_run(f'表4:{areaName}土壤检测数据数值修约结果表').bold = True
  1763. # table_4 = doc.add_table(rows=2, cols=2)
  1764. paragraph_4.alignment = WD_ALIGN_PARAGRAPH.CENTER
  1765. # table_4.alignment = WD_TABLE_ALIGNMENT.CENTER
  1766. doc.add_heading('为避免数据量过多无法显示,请至数据保存文件夹中查看数据表:数值修约审核.xlsx', level=4)
  1767. # 填入数据 这里数据也放不下 嵌入链接
  1768. doc.add_heading('3、数据未检出的填报规范性审核', level=2)
  1769. # 插入表5
  1770. paragraph_5 = doc.add_paragraph()
  1771. paragraph_5.add_run(f'表5:{areaName}土壤检测数据未检出项填报审核结果表').bold = True
  1772. # table_5 = doc.add_table(rows=2, cols=2)
  1773. paragraph_5.alignment = WD_ALIGN_PARAGRAPH.CENTER
  1774. # table_5.alignment = WD_TABLE_ALIGNMENT.CENTER
  1775. # 写入数据 这里数据也放不下 嵌入链接
  1776. doc.add_heading('为避免数据量过多无法显示,请至数据保存文件夹中查看数据表:数据填报项审核结果.xlsx', level=4)
  1777. # doc.add_heading('4、土壤质地填报规范性审核', level=2)
  1778. # # 插入表6
  1779. # paragraph_6 = doc.add_paragraph()
  1780. # paragraph_6.add_run(f'表6:{areaName}土壤质地填报审核结果表').bold = True
  1781. # table_6 = doc.add_table(rows=len(table_6_data) + 1, cols=4, style='Light Shading Accent 1')
  1782. # paragraph_6.alignment = WD_ALIGN_PARAGRAPH.CENTER
  1783. # table_6.alignment = WD_TABLE_ALIGNMENT.CENTER
  1784. # # 提取结果表中数据
  1785. # # 写入数据 土壤质地类型不一致的数据提取出来
  1786. # for i, row in enumerate(table_6.rows):
  1787. # for j, cell in enumerate(row.cells):
  1788. # # 获取单元格中的段落对象
  1789. # paragraph = cell.paragraphs[0]
  1790. # if i == 0:
  1791. # r = paragraph.add_run(str(table_6_data.columns[j]))
  1792. # r.font.bold = True
  1793. # else:
  1794. # r = paragraph.add_run(str(table_6_data.iloc[i - 1, j]))
  1795. # paragraph.alignment = WD_PARAGRAPH_ALIGNMENT.CENTER
  1796. # paragraph.paragraph_format.alignment = WD_TABLE_ALIGNMENT.CENTER # 对齐
  1797. # paragraph.paragraph_format.line_spacing = 1 # 段落行间距
  1798. # r.font.size = Pt(10.5)
  1799. # r.font.name = 'Times New Roman'
  1800. # r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  1801. doc.add_heading('三、数据合理性审核', level=1)
  1802. doc.add_heading('1、阈值法审核', level=2)
  1803. # 插入表格
  1804. paragraph_7 = doc.add_paragraph()
  1805. paragraph_7.add_run(f'表6:{areaName}土壤检测数据超阈值样品统计表').bold = True
  1806. # table_7 = doc.add_table(rows=2, cols=2)
  1807. # paragraph_7.alignment = WD_ALIGN_PARAGRAPH.CENTER
  1808. # table_7.alignment = WD_TABLE_ALIGNMENT.CENTER
  1809. # 写入数据 点击查看数据 这里也不一定写的下 最好是嵌入链接
  1810. doc.add_heading('为避免数据量过多无法显示,请至数据保存文件夹中查看数据表:数据审核过程存疑数据一览表.xlsx', level=4)
  1811. # todo 合并所有数据 审核结果不为空的数据 写入表格保存到指定文件夹
  1812. doc.add_heading('2、极值法审核', level=2)
  1813. doc.add_heading('(1)pH', level=3)
  1814. # 插入ph分布图
  1815. if os.path.isfile(f'{mkdir_path}/pH值分布图.png'):
  1816. doc.add_picture(f'{mkdir_path}/pH值分布图.png', width=Inches(6.0))
  1817. paragraph_t_1 = doc.add_paragraph()
  1818. paragraph_t_1.add_run(f'图1:pH值分布情况').bold = True
  1819. paragraph_t_1.alignment = WD_ALIGN_PARAGRAPH.CENTER
  1820. # 插入频度统计表
  1821. paragraph_8 = doc.add_paragraph()
  1822. paragraph_8.add_run('表7:pH数据统计表').bold = True
  1823. table_8 = doc.add_table(rows=6, cols=2, style='Light Shading Accent 1')
  1824. t_8 = table_8_data['频度分析']
  1825. t_8 = t_8.reset_index()
  1826. t_8.columns = ['指标', '数据']
  1827. paragraph_8.alignment = WD_ALIGN_PARAGRAPH.CENTER
  1828. table_8.alignment = WD_TABLE_ALIGNMENT.CENTER
  1829. for i, row in enumerate(table_8.rows):
  1830. for j, cell in enumerate(row.cells):
  1831. # 获取单元格中的段落对象
  1832. paragraph = cell.paragraphs[0]
  1833. if i == 0:
  1834. r = paragraph.add_run(str(t_8.columns[j]))
  1835. r.font.bold = True
  1836. else:
  1837. r = paragraph.add_run(str(t_8.iloc[i - 1, j]))
  1838. r.font.size = Pt(10.5)
  1839. r.font.name = 'Times New Roman'
  1840. r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  1841. paragraph.alignment = WD_PARAGRAPH_ALIGNMENT.CENTER
  1842. paragraph.paragraph_format.alignment = WD_TABLE_ALIGNMENT.CENTER # 对齐
  1843. paragraph.paragraph_format.line_spacing = 1 # 段落行间距
  1844. # 插入异常数据提取表格 todo 这里数据多的话也可能写不下 最好是嵌入一下
  1845. if not table_8_data['异常数据'].empty:
  1846. paragraph_9 = doc.add_paragraph()
  1847. paragraph_9.add_run('表8:pH异常数据统计表').bold = True
  1848. table_9 = doc.add_table(rows=len(table_8_data['异常数据']) + 1, cols=6, style='Light Shading Accent 1')
  1849. t_9 = table_8_data['异常数据']
  1850. paragraph_9.alignment = WD_ALIGN_PARAGRAPH.CENTER
  1851. table_9.alignment = WD_TABLE_ALIGNMENT.CENTER
  1852. for i, row in enumerate(table_9.rows):
  1853. for j, cell in enumerate(row.cells):
  1854. # 获取单元格中的段落对象
  1855. paragraph = cell.paragraphs[0]
  1856. if i == 0:
  1857. r = paragraph.add_run(str(t_9.columns[j]))
  1858. r.font.bold = True
  1859. else:
  1860. r = paragraph.add_run(str(t_9.iloc[i - 1, j]))
  1861. r.font.size = Pt(10.5)
  1862. r.font.name = 'Times New Roman'
  1863. r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  1864. paragraph.alignment = WD_PARAGRAPH_ALIGNMENT.CENTER
  1865. paragraph.paragraph_format.alignment = WD_TABLE_ALIGNMENT.CENTER # 对齐
  1866. paragraph.paragraph_format.line_spacing = 1 # 段落行间距
  1867. doc.add_heading('4、指标综合分析', level=2)
  1868. doc.add_heading('表9:重金属超筛选值情况统计', level=4)
  1869. # todo 获取重金属数据
  1870. doc.add_heading('四、审核存疑数据', level=1)
  1871. paragraph_12 = doc.add_paragraph()
  1872. paragraph_12.add_run(f'表10:数据审核过程存疑数据一览表').bold = True
  1873. paragraph_12.alignment = WD_ALIGN_PARAGRAPH.CENTER
  1874. doc.add_heading('为避免数据量过多无法显示,请至数据保存文件夹中查看数据表:数据审核过程存疑数据一览表.xlsx', level=4)
  1875. doc.add_heading('五、附表', level=1)
  1876. doc.add_heading('附表1:某区三普样品数量统计表(表层)', level=2)
  1877. # 插入附表1
  1878. table_1_f = doc.add_table(rows=lenNum_1 + 1, cols=3, style='Light Shading Accent 1')
  1879. table_1_f.alignment = WD_TABLE_ALIGNMENT.CENTER
  1880. # 遍历表格 插入数据
  1881. # 遍历表格的所有单元格,并填充内容
  1882. for i, row in enumerate(table_1_f.rows):
  1883. for j, cell in enumerate(row.cells):
  1884. # 获取单元格中的段落对象
  1885. paragraph = cell.paragraphs[0]
  1886. if i == 0:
  1887. r = paragraph.add_run(str(table_1_data.columns[j]))
  1888. r.font.bold = True
  1889. else:
  1890. r = paragraph.add_run(str(table_1_data.iloc[i - 1, j]))
  1891. r.font.size = Pt(10.5)
  1892. r.font.name = 'Times New Roman'
  1893. r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  1894. paragraph.alignment = WD_PARAGRAPH_ALIGNMENT.CENTER
  1895. paragraph.paragraph_format.alignment = WD_TABLE_ALIGNMENT.CENTER # 对齐
  1896. paragraph.paragraph_format.line_spacing = 1 # 段落行间距
  1897. # 合并单元格 合并第3列的第二行和第三行
  1898. if lenNum_1 > 1:
  1899. table_1_f.cell(2, 2).text = ''
  1900. table_1_f.cell(1, 2).merge(table_1_f.cell(2, 2))
  1901. doc.add_heading('附表2:各指标频度分析表', level=2)
  1902. # 插入表格 写入数据
  1903. table_f_2_data = table_f_2_data.replace(np.nan, '')
  1904. makeInfoTable(table_f_2_data, doc)
  1905. # table_f_2 = doc.add_table(rows=len(table_f_2_data) + 1, cols=6, style='Light Shading Accent 1')
  1906. # for i, row in enumerate(table_f_2.rows):
  1907. # for j, cell in enumerate(row.cells):
  1908. # # 获取单元格中的段落对象
  1909. # paragraph = cell.paragraphs[0]
  1910. # if i == 0:
  1911. # r = paragraph.add_run(str(table_f_2_data.columns[j]))
  1912. # r.font.bold = True
  1913. # else:
  1914. # r = paragraph.add_run(str(table_f_2_data.iloc[i - 1, j]))
  1915. # r.font.size = Pt(10.5)
  1916. # r.font.name = 'Times New Roman'
  1917. # r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  1918. # paragraph.alignment = WD_PARAGRAPH_ALIGNMENT.CENTER
  1919. # paragraph.paragraph_format.alignment = WD_TABLE_ALIGNMENT.CENTER # 对齐
  1920. # paragraph.paragraph_format.line_spacing = 1 # 段落行间距
  1921. # doc.add_heading('为避免数据量过多无法显示,请至数据保存文件夹中查看数据表:频度分析表.xlsx', level=4)
  1922. doc.add_heading('附表3:各指标频度分析图', level=2)
  1923. # 插入频度信息的图形
  1924. if os.path.isfile(f'{mkdir_path}/pH分析图.png'):
  1925. doc.add_picture(f'{mkdir_path}/pH分析图.png', width=Inches(6.0))
  1926. if os.path.isfile(f'{mkdir_path}/总镉分析图.png'):
  1927. doc.add_picture(f'{mkdir_path}/总镉分析图.png', width=Inches(6.0))
  1928. if os.path.isfile(f'{mkdir_path}/总铬分析图.png'):
  1929. doc.add_picture(f'{mkdir_path}/总铬分析图.png', width=Inches(6.0))
  1930. if os.path.isfile(f'{mkdir_path}/总汞分析图.png'):
  1931. doc.add_picture(f'{mkdir_path}/总汞分析图.png', width=Inches(6.0))
  1932. if os.path.isfile(f'{mkdir_path}/总镍分析图.png'):
  1933. doc.add_picture(f'{mkdir_path}/总镍分析图.png', width=Inches(6.0))
  1934. if os.path.isfile(f'{mkdir_path}/总砷分析图.png'):
  1935. doc.add_picture(f'{mkdir_path}/总砷分析图.png', width=Inches(6.0))
  1936. if os.path.isfile(f'{mkdir_path}/总铅分析图.png'):
  1937. doc.add_picture(f'{mkdir_path}/总铅分析图.png', width=Inches(6.0))
  1938. doc.add_heading('附表4:数值修约标准', level=2)
  1939. # 读取数据 插入表格 写入数据
  1940. numData = pd.read_excel('./img/数值修约要求.xlsx', sheet_name='Sheet1')
  1941. table_2_f = doc.add_table(rows=len(numData) + 1, cols=2, style='Light Shading Accent 1')
  1942. table_2_f.alignment = WD_TABLE_ALIGNMENT.CENTER
  1943. for i, row in enumerate(table_2_f.rows):
  1944. for j, cell in enumerate(row.cells):
  1945. # 获取单元格中的段落对象
  1946. paragraph = cell.paragraphs[0]
  1947. if i == 0:
  1948. r = paragraph.add_run(str(numData.columns[j]))
  1949. r.font.bold = True
  1950. else:
  1951. r = paragraph.add_run(str(numData.iloc[i - 1, j]))
  1952. r.font.size = Pt(10.5)
  1953. r.font.name = 'Times New Roman'
  1954. r.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  1955. paragraph.alignment = WD_PARAGRAPH_ALIGNMENT.CENTER
  1956. paragraph.paragraph_format.alignment = WD_TABLE_ALIGNMENT.CENTER # 对齐
  1957. paragraph.paragraph_format.line_spacing = 1 # 段落行间距
  1958. # 处理样式 遍历所有的段落 修改字体
  1959. # 遍历并打印每个段落的文本
  1960. paragraphs = doc.paragraphs
  1961. for paragraph in paragraphs:
  1962. for run in paragraph.runs:
  1963. run.font.color.rgb = RGBColor(0, 0, 0)
  1964. run.font.name = 'Times New Roman'
  1965. run.font.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  1966. # run.element.rPr.rFonts.set(qn('w:eastAsia'), u'仿宋_GB2312')
  1967. # 保存Word文档
  1968. doc.save(f'{mkdir_path}/{areaName}-{type}审核报告.docx')