225 lines
8.6 KiB
Python
225 lines
8.6 KiB
Python
import json
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import random
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from datetime import datetime, timedelta
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from DBHelper.MongoHelperInstance import DB_GUA
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class CommonUtils(object):
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# 生成新的企业ID，如果该ID存在，则重新生成
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@staticmethod
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def make_new_cid():
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def random_cid(num):
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"""随机企业ID"""
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choices = 'ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789'
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salt = ''
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for i in range(num):
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salt += random.choice(choices)
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return salt
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new_cid = random_cid(8)
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case = DB_GUA.find_single_column(
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"管理端",
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"企业数据",
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{"企业ID": new_cid},
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"企业ID"
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) is not None
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while case:
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new_cid = random_cid(8)
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return new_cid
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class ExcelParserUtil(object):
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# 转换excel日期
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@staticmethod
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def trans_date_fmt_1(days):
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if type(days) == str: # 特殊情况：比如某些高管信息出生日期只有年份，则返回年份
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return days
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else:
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delta = timedelta(days=days) # 将1899-12-30转化为可以计算的时间格式并加上要转化的日期戳
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_date = datetime.strptime('1899/12/30', '%Y/%m/%d') + delta
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return datetime.strftime(_date, '%Y年%m月%d日')
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# 转换excel日期
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@staticmethod
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def trans_date_fmt_2(days):
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delta = timedelta(days=days)
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# 将1899-12-30转化为可以计算的时间格式并加上要转化的日期戳
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_date = datetime.strptime('1899/12/30', '%Y/%m/%d') + delta
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return datetime.strftime(_date, '%Y-%m-%d')
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# 转换excel日期
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@staticmethod
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def trans_date_fmt_3(_date):
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""""""
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# 删除列表中所有''
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@staticmethod
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def list_remove_blank(_list):
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while '' in _list:
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_list.remove('')
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return _list
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# 列表中的''转换为None
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@staticmethod
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def list_to_none(_list):
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return list(map(lambda x: None if x == '' else x, _list))
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# 列表中的float类型数据都保留2位小数
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@staticmethod
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def list_decimal(_list):
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return list(map(lambda _v: round(_v, 2) if isinstance(_v, float) else _v, _list))
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# 列表中的float类型数据都转为为int类型
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@staticmethod
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def list_to_int(_list):
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return list(map(lambda _v: int(_v) if isinstance(_v, float) else _v, _list))
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class ExcelSheetParser(object):
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def __init__(self, sheet):
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self._sheet = sheet
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# 解析企业信息
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def parse_sheet1(self):
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# 表头
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cols_tag = self._sheet.col_values(1)
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cols_tag.pop(0)
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# 表值
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cols_val = self._sheet.col_values(2)
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cols_val.pop(0)
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# 参保人数
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cols_val[16] = int(cols_val[16]) if type(cols_val[16]) == float else cols_val[16]
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# 数组中的空字符串转为None
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list_0 = ExcelParserUtil.list_to_none(cols_val)
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# 数组中的float类型数据都保留2位小数
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list_1 = ExcelParserUtil.list_decimal(list_0)
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# 拼接
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data = json.loads(json.dumps(dict(zip(cols_tag, list_1))))
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# 转换日期
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data['成立日期'] = ExcelParserUtil.trans_date_fmt_1(data['成立日期'])
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return data
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# 解析高管信息、股东信息
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def parse_sheet2(self):
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# 高管信息
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cols_tag1 = self._sheet.row_values(1)[1:7]
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n_rows1 = len(ExcelParserUtil.list_remove_blank(self._sheet.col_values(1)[2:]))
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return_data1 = []
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for i in range(2, n_rows1 + 2):
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list_0 = ExcelParserUtil.list_to_none(self._sheet.row_values(i)[1:7])
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list_1 = ExcelParserUtil.list_decimal(list_0)
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# 出生日期
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list_1[3] = ExcelParserUtil.trans_date_fmt_1(list_1[3])
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data = json.loads(json.dumps(dict(zip(cols_tag1, list_1))))
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return_data1.append(data)
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# 股东信息
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cols_tag2 = self._sheet.row_values(1)[8:]
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n_rows2 = len(ExcelParserUtil.list_remove_blank(self._sheet.col_values(8)[2:]))
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return_data2 = []
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for i in range(2, n_rows2 + 2):
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list_0 = ExcelParserUtil.list_to_none(self._sheet.row_values(i)[8:])
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list_1 = ExcelParserUtil.list_decimal(list_0)
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data = json.loads(json.dumps(dict(zip(cols_tag2, list_1))))
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return_data2.append(data)
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return return_data1, return_data2
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# 解析经营情况
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def parse_sheet3(self):
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cols_tag = self._sheet.col_values(1)[1:]
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return_data = []
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for i in range(2, 6):
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list_0 = ExcelParserUtil.list_to_none(self._sheet.col_values(i)[1:])
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list_1 = ExcelParserUtil.list_decimal(list_0)
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# 解析返回数据
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parsed_data = dict()
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# 报告期
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parsed_data["报告期"] = list_1[0]
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# 资产负债表
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parsed_data["资产负债表"] = json.loads(json.dumps(dict(zip(cols_tag[43:67], list_1[43:67]))))
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# 利润表
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parsed_data["利润表"] = json.loads(json.dumps(dict(zip(cols_tag[28:43], list_1[28:43]))))
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# 补充数据表
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parsed_data["补充数据表"] = json.loads(json.dumps(dict(zip(cols_tag[1:28], list_1[1:28]))))
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return_data.append(parsed_data)
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return return_data
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# 解析客户信息
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def parse_sheet4(self):
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cols_tag = self._sheet.row_values(1)[1:]
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cols_tag[0] = "报告期"
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n_rows = len(ExcelParserUtil.list_remove_blank(self._sheet.col_values(1)[2:]))
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return_data = []
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for i in range(2, n_rows + 2):
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list_0 = ExcelParserUtil.list_to_none(self._sheet.row_values(i)[1:])
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list_1 = ExcelParserUtil.list_decimal(list_0)
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data = json.loads(json.dumps(dict(zip(cols_tag, list_1))))
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data['担保起始日'] = ExcelParserUtil.trans_date_fmt_2(data['担保起始日'])
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data['担保截止日'] = ExcelParserUtil.trans_date_fmt_2(data['担保截止日'])
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return_data.append(data)
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return return_data
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# 解析区域分布、行业分布
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def parse_sheet5(self):
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cols_tag = self._sheet.row_values(1)[1:]
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cols_tag[0] = "报告期"
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n_rows = len(ExcelParserUtil.list_remove_blank(self._sheet.col_values(1)[2:]))
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return_data = []
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for i in range(2, n_rows + 2):
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list_0 = ExcelParserUtil.list_to_none(self._sheet.row_values(i)[1:])
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list_1 = ExcelParserUtil.list_decimal(list_0)
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data = json.loads(json.dumps(dict(zip(cols_tag, list_1))))
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return_data.append(data)
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return return_data
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# 解析担保金额分布
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def parse_sheet6(self):
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_keys = ["金额<=100w", "100w<金额<=500w", "500w<金额<=1000w", "1000w<金额<=3000w", "3000w<金额<=5000w", "5000w<金额<=8000w", "8000w<金额<=10000w", "金额>10000w", "合计"]
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_dict_list = list()
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for c in range(2, 13, 3): # c: col_num
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_year = self._sheet.col_values(c)[1]
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_dict = {"报告期": _year}
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for s in range(0, 3): # s: step
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_values = ExcelParserUtil.list_to_none(self._sheet.col_values(c+s)[3:13])
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_name = self._sheet.col_values(c+s)[2]
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if _name == "担保责任余额":
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_values = ExcelParserUtil.list_decimal(_values)
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else:
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_values = ExcelParserUtil.list_to_int(_values)
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_dict[_name] = json.loads(json.dumps(dict(zip(_keys, _values))))
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_dict_list.append(_dict)
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return _dict_list
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# 解析资产负债表
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def parse_sheet7(self):
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cols_tag = self._sheet.col_values(1)[1:]
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return_data = []
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for i in range(2, 6):
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list_0 = ExcelParserUtil.list_to_none(self._sheet.col_values(i)[1:])
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list_1 = ExcelParserUtil.list_decimal(list_0)
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data = json.loads(json.dumps(dict(zip(cols_tag, list_1))))
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data.pop('流动资产:')
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data.pop('非流动资产:')
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data.pop('流动负债:')
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data.pop('非流动负债:')
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data.pop('所有者权益:')
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return_data.append(data)
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return return_data
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# 解析利润表
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def parse_sheet8(self):
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cols_tag = list(map(lambda x: x.strip().replace('减：', '').replace('加：', ''), self._sheet.col_values(1)[1:]))
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return_data = []
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for i in range(2, 6):
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list_0 = ExcelParserUtil.list_to_none(self._sheet.col_values(i)[1:])
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list_1 = ExcelParserUtil.list_decimal(list_0)
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data = json.loads(json.dumps(dict(zip(cols_tag, list_1))))
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return_data.append(data)
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return return_data
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