425 lines
16 KiB
Python
425 lines
16 KiB
Python
import operator
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def environment_co2(param):
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"""
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二氧化碳
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Parameters:
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param dict 数据库数据
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Returns:
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result dict 清洗好的数据
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"""
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# Params
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income_data = param['公司当年收入（万元）']
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three_year_data = sorted(param['环境问卷']['近三年公司数据'], key=operator.itemgetter('年份'), reverse=False)
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# Returns
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result = dict()
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def date_range():
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"""
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评价周期年度区间
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Parameters:
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param dict 环境问卷
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Returns:
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result str 区间数据
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"""
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year_begin = three_year_data[0]['年份']
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year_end = three_year_data[2]['年份']
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res = year_begin + '-' + year_end
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return res
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def co2_emissions(year_param, income):
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"""
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公司年度总二氧化碳排放
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Parameters:
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year_param dict 年度环境问卷数据
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Returns:
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result str 该年度二氧化碳排放总量
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"""
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total = list()
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total.append(round(year_param['公司当年消耗的原煤（千克）'] * 1.9003, 2))
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total.append(round(year_param['公司当年消耗的焦炭（千克）'] * 2.8604, 2))
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total.append(round(year_param['公司当年消耗的原油（升）'] * 0.86 * 3.0202, 2))
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total.append(round(year_param['公司当年消耗的燃料油（升）'] * 0.86 * 3.1705, 2))
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total.append(round(year_param['公司当年消耗的汽油（升）'] * 0.73 * 2.9251, 2))
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total.append(round(year_param['公司当年消耗的煤油（升）'] * 0.82 * 3.0179, 2))
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total.append(round(year_param['公司当年消耗的柴油（升）'] * 0.85 * 3.0959, 2))
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total.append(round(year_param['公司当年消耗的液化石油气（千克）'] * 3.1013, 2))
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total.append(round(year_param['公司当年消耗的天然气（立方米）'] * 2.1622, 2))
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total.append(round(year_param['公司当年消耗的煤气（立方米）'] * 0.7100, 2))
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total.append(round(year_param['公司当年消耗的电（千瓦时）'] * 0.6101, 2))
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# 每年排放总量
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amount = sum(total)
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res = dict()
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res['amount'] = amount
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# 每年每万元收入二氧化碳排放量
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# res['money_amount'] = round(amount / income, 2)
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num = 2
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while round(amount / income, num) == 0.0:
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num += 1
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res['money_amount'] = round(amount / income, num+1)
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return res
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def calculate_three_year_data():
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"""
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计算三年数据并转为字符串
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Parameters:
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'-'
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Returns:
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result str 三年数据用顿号隔开
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"""
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res = dict()
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year_co2 = list()
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year_thousand_co2 = list()
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for index in range(len(three_year_data)):
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co2_res = co2_emissions(three_year_data[index], income_data[three_year_data[index]['年份']])
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year_co2.append(co2_res['amount'])
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year_thousand_co2.append(co2_res['money_amount'])
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# 列表中元素类型float转str
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year_co2_new = [str(x) for x in year_co2]
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year_thousand_new = [str(x) for x in year_thousand_co2]
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# Returns-part1
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res['part_01'] = dict()
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res['part_01']['date_range'] = date_range()
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res['part_01']['co2_emissions'] = '、'.join(year_co2_new)
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# part2
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res['part_02'] = dict()
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res['part_02']['date_range'] = date_range()
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res['part_02']['co2_emissions'] = '、'.join(year_thousand_new)
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res['part_02']['year_02'] = three_year_data[1]['年份']
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res['part_02']['year_03'] = three_year_data[2]['年份']
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res['part_02']['year01_on_year02'] = round((year_thousand_co2[1]/year_thousand_co2[0] - 1) * 100, 2)
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res['part_02']['year02_on_year03'] = round((year_thousand_co2[2]/year_thousand_co2[1] - 1) * 100, 2)
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res['part_02']['industry_indicators'] = None
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res['part_02']['industry_indicators_average'] = None
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res['part_02']['industry_indicators_median'] = None
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res['part_02']['median_comparison'] = None
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return res
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result['part_01'] = calculate_three_year_data()['part_01']
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result['part_02'] = calculate_three_year_data()['part_02']
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return result
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def environment_energy(param):
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"""
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能耗
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Parameters:
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param dict 数据库数据
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Returns:
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result dict 清洗好的数据
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"""
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# Params
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income_data = param['公司当年收入（万元）']
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three_year_data = sorted(param['环境问卷']['近三年公司数据'], key=operator.itemgetter('年份'), reverse=False)
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# Returns
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result = dict()
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def date_range():
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"""
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评价周期年度区间
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Parameters:
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param dict 环境问卷
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Returns:
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result str 区间数据
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"""
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year_begin = three_year_data[0]['年份']
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year_end = three_year_data[2]['年份']
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res = year_begin + '-' + year_end
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return res
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def ten_thousand_yuan_energy(year_param, income):
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"""
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公司年度能耗
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Parameters:
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year_param dict 年度环境问卷数据
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Returns:
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result str 该年度二氧化碳排放总量
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"""
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total = list()
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total.append(round(year_param['公司当年消耗的原煤（千克）'] * 20.9080, 2))
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total.append(round(year_param['公司当年消耗的焦炭（千克）'] * 28.4350, 2))
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total.append(round(year_param['公司当年消耗的原油（升）'] * 0.86 * 41.8160, 2))
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total.append(round(year_param['公司当年消耗的燃料油（升）'] * 0.86 * 41.8160, 2))
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total.append(round(year_param['公司当年消耗的汽油（升）'] * 0.73 * 43.0700, 2))
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total.append(round(year_param['公司当年消耗的煤油（升）'] * 0.82 * 43.0700, 2))
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total.append(round(year_param['公司当年消耗的柴油（升）'] * 0.85 * 42.6520, 2))
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total.append(round(year_param['公司当年消耗的液化石油气（千克）'] * 50.1790, 2))
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total.append(round(year_param['公司当年消耗的天然气（立方米）'] * 38.9310, 2))
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total.append(round(year_param['公司当年消耗的煤气（立方米）'] * 17.0000, 2))
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total.append(round(year_param['公司当年消耗的电（千瓦时）'] * 11.8400, 2))
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amount = sum(total)
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res = dict()
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res['amount'] = amount
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num = 2
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while round(amount / income, num) == 0.0:
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num += 1
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res['money_amount'] = round(amount / income, num + 1)
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return res
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def calculate_three_year_data():
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"""
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计算三年数据并转为字符串
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Parameters:
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'-'
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Returns:
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result str 三年数据用顿号隔开
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"""
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res = dict()
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year_energy = list()
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year_thousand_energy = list()
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for index in range(len(three_year_data)):
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energy_res = ten_thousand_yuan_energy(three_year_data[index], income_data[three_year_data[index]['年份']])
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year_energy.append(energy_res['amount'])
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year_thousand_energy.append(energy_res['money_amount'])
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# 列表中元素类型float转str
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year_energy_new = [str(x) for x in year_energy]
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year_thousand_energy_new = [str(x) for x in year_thousand_energy]
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# Returns-part1
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res['part_01'] = dict()
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res['part_01']['date_range'] = date_range()
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res['part_01']['energy_consumption'] = '、'.join(year_energy_new)
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# part2
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res['part_02'] = dict()
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res['part_02']['date_range'] = date_range()
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res['part_02']['energy_consumption'] = '、'.join(year_thousand_energy_new)
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res['part_02']['year_02'] = three_year_data[1]['年份']
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res['part_02']['year_03'] = three_year_data[2]['年份']
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res['part_02']['year01_on_year02'] = round((year_thousand_energy[1]/year_thousand_energy[0] - 1) * 100, 2)
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res['part_02']['year02_on_year03'] = round((year_thousand_energy[2]/year_thousand_energy[1] - 1) * 100, 2)
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res['part_02']['industry_indicators'] = None
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res['part_02']['industry_indicators_average'] = None
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res['part_02']['industry_indicators_median'] = None
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res['part_02']['median_comparison'] = None
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return res
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result['part_01'] = calculate_three_year_data()['part_01']
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result['part_02'] = calculate_three_year_data()['part_02']
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return result
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def environment_standard_coal(param):
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"""
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标准煤
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Parameters:
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param dict 数据库数据
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Returns:
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result dict 清洗好的数据
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"""
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# Params
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income_data = param['公司当年收入（万元）']
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three_year_data = sorted(param['环境问卷']['近三年公司数据'], key=operator.itemgetter('年份'), reverse=False)
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# Returns
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result = dict()
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def date_range():
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"""
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评价周期年度区间
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Parameters:
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param dict 环境问卷
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Returns:
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result str 区间数据
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"""
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year_begin = three_year_data[0]['年份']
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year_end = three_year_data[2]['年份']
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res = year_begin + '-' + year_end
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return res
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def standard_coal(year_param, income):
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"""
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能耗折算标准煤
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Parameters:
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year_param dict 年度环境问卷数据
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Returns:
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result str 该年度二氧化碳排放总量
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"""
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total = list()
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total.append(round(year_param['公司当年消耗的原煤（千克）'] * 0.7143, 2))
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total.append(round(year_param['公司当年消耗的焦炭（千克）'] * 0.9714, 2))
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total.append(round(year_param['公司当年消耗的原油（升）'] * 0.86 * 1.4286, 2))
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total.append(round(year_param['公司当年消耗的燃料油（升）'] * 0.86 * 1.4286, 2))
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total.append(round(year_param['公司当年消耗的汽油（升）'] * 0.73 * 1.4714, 2))
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total.append(round(year_param['公司当年消耗的煤油（升）'] * 0.82 * 1.4714, 2))
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total.append(round(year_param['公司当年消耗的柴油（升）'] * 0.85 * 1.4571, 2))
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total.append(round(year_param['公司当年消耗的液化石油气（千克）'] * 1.7143, 2))
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total.append(round(year_param['公司当年消耗的天然气（立方米）'] * 1.3300, 2))
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total.append(round(year_param['公司当年消耗的煤气（立方米）'] * 0.5700, 2))
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total.append(round(year_param['公司当年消耗的电（千瓦时）'] * 0.4040, 2))
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amount = sum(total)
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res = dict()
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res['amount'] = amount
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num = 2
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while round(amount / income, num) == 0.0:
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num += 1
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res['money_amount'] = round(amount / income, num + 1)
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return res
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def calculate_three_year_data():
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"""
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计算三年数据并转为字符串
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Parameters:
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'-'
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Returns:
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result str 三年数据用顿号隔开
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"""
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res = dict()
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year_standard_coal = list()
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year_thousand_standard_coal = list()
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for index in range(len(three_year_data)):
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standard_coal_res = standard_coal(three_year_data[index], income_data[three_year_data[index]['年份']])
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year_standard_coal.append(standard_coal_res['amount'])
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year_thousand_standard_coal.append(standard_coal_res['money_amount'])
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# 列表中元素类型float转str
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year_standard_coal_new = [str(x) for x in year_standard_coal]
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year_thousand_standard_coal_new = [str(x) for x in year_thousand_standard_coal]
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# Returns-part1
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res['part_01'] = dict()
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res['part_01']['date_range'] = date_range()
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res['part_01']['energy_consumption'] = '、'.join(year_standard_coal_new)
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# part2
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res['part_02'] = dict()
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res['part_02']['date_range'] = date_range()
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res['part_02']['energy_consumption'] = '、'.join(year_thousand_standard_coal_new)
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return res
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result['part_01'] = calculate_three_year_data()['part_01']
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result['part_02'] = calculate_three_year_data()['part_02']
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return result
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def environment_consume_water(param):
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"""
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耗水
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Parameters:
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param dict 数据库数据
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Returns:
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result dict 清洗好的数据
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"""
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# Params
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income_data = param['公司当年收入（万元）']
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three_year_data = sorted(param['环境问卷']['近三年公司数据'], key=operator.itemgetter('年份'), reverse=False)
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# Returns
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result = dict()
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def date_range():
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"""
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评价周期年度区间
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Parameters:
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param dict 环境问卷
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Returns:
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result str 区间数据
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"""
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year_begin = three_year_data[0]['年份']
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year_end = three_year_data[2]['年份']
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res = year_begin + '-' + year_end
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return res
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def calculate_three_year_data():
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"""
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计算三年数据并转为字符串
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Parameters:
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'-'
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Returns:
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result str 三年数据用顿号隔开
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"""
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res = dict()
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year_consume_water = list()
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year_thousand_consume_water = list()
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for index in range(len(three_year_data)):
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year_consume_water.append(three_year_data[index]['公司当年耗水（吨）'])
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year_thousand_consume_water.append(round(three_year_data[index]['公司当年耗水（吨）'] / income_data[three_year_data[index]['年份']]))
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# 列表中元素类型float转str
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year_consume_water_new = [str(x) for x in year_consume_water]
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year_thousand_consume_water_new = [str(x) for x in year_thousand_consume_water]
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# Returns-part1
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res['part_01'] = dict()
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res['part_01']['date_range'] = date_range()
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res['part_01']['consume_water'] = '、'.join(year_consume_water_new)
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# part2
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res['part_02'] = dict()
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res['part_02']['date_range'] = date_range()
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res['part_02']['consume_water'] = '、'.join(year_thousand_consume_water_new)
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res['part_02']['year_02'] = three_year_data[1]['年份']
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res['part_02']['year_03'] = three_year_data[2]['年份']
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try:
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res['part_02']['year01_on_year02'] = round((year_thousand_consume_water[1]/year_thousand_consume_water[0]-1) * 100, 2)
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res['part_02']['year02_on_year03'] = round((year_thousand_consume_water[2]/year_thousand_consume_water[1]-1) * 100, 2)
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except ZeroDivisionError:
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res['part_02']['year01_on_year02'] = '0'
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res['part_02']['year02_on_year03'] = '0'
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res['part_02']['industry_indicators'] = None
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res['part_02']['industry_indicators_average'] = None
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res['part_02']['industry_indicators_median'] = None
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res['part_02']['median_comparison'] = None
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return res
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result['part_01'] = calculate_three_year_data()['part_01']
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result['part_02'] = calculate_three_year_data()['part_02']
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return result
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def environment_green_business(param):
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"""
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绿色业务收入
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Parameters:
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param dict 数据库数据
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Returns:
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result dict 清洗好的数据
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"""
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# Params
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income_data = param['公司当年收入（万元）']
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three_year_data = sorted(param['环境问卷']['近三年公司数据'], key=operator.itemgetter('年份'), reverse=False)
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# Returns
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result = dict()
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if three_year_data[2]['公司当年绿色业务收入（万元）——包括不限于清洁能源、清洁交通、绿色建筑、清洁技术等'] == 0:
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result['describe'] = False
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else:
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year = three_year_data[2]['年份']
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share = round(three_year_data[2]['公司当年绿色业务收入（万元）——包括不限于清洁能源、清洁交通、绿色建筑、清洁技术等'] / income_data[three_year_data[2]['年份']], 2)
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result['describe'] = '绿色业务收入占比（%）——公司在{year_03}年绿色业务收入占比为{revenue_share}，这提升了公司的环境得分。'.format(year_03=year, revenue_share=share)
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return result
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def environment_punish(param):
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"""
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处罚
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Parameters:
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param dict 数据库数据
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Returns:
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result dict 清洗好的数据
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"""
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# Params
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data = param['环境问卷']
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# Returns
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result = dict()
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if data['其他类型问卷'][4][0] == '是':
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result['describe'] = False
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else:
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result['describe'] = '处罚——公司在近三年因环境问题受到监管处罚，这影响了公司的环境得分。'
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return result
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