143 lines
5.8 KiB
Python
143 lines
5.8 KiB
Python
import json
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from pyecharts import options as opts
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from pyecharts.charts import Bar, Line
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from pyecharts.globals import CurrentConfig
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from Config.Config import ONLINE_HOST
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CurrentConfig.ONLINE_HOST = ONLINE_HOST
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class RuYuanZaiYuanModel:
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@staticmethod
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def load_student_data():
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try:
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# 加载招生数据(入园人数)
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with open("./Data/ZhaoShengCount.json", "r", encoding="utf-8") as f:
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enrollment_data = json.load(f)
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# 加载在校生数据(在园人数)
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with open("./Data/ZaiXiaoShengCount.json", "r", encoding="utf-8") as f:
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in_school_data = json.load(f)
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return enrollment_data, in_school_data
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except Exception as e:
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print(f"读取学生数据出错: {e}")
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return [], []
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@staticmethod
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def generate_preschool_education_config():
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# 获取学前教育相关数据
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enrollment_data, in_school_data = RuYuanZaiYuanModel.load_student_data()
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# 提取云南省级数据
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yunnan_enroll = next((item for item in enrollment_data if item["area_name"] == "云南省"), None)
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if not yunnan_enroll:
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return {}
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# # 构建学前教育数据
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urban_data = [] # 城区数据
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town_data = [] # 镇区数据
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rural_data = [] # 乡村数据
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total_enroll = [] # 总入园数
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# 提取年份数据(2015-2024)
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years = [str(year) for year in range(2015, 2025)]
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for year in years:
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enroll_data = yunnan_enroll["education_data"]["preschool"].get(year, {})
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urban_data.append(enroll_data.get("urban", 0) / 10000) # 转换为万人
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town_data.append(enroll_data.get("town", 0) / 10000) # 转换为万人
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rural_data.append(enroll_data.get("rural", 0) / 10000) # 转换为万人
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# 计算总和作为总入园数，而非使用文件中的total字段
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calculated_total = enroll_data.get("urban", 0) + enroll_data.get("town", 0) + enroll_data.get("rural", 0)
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total_enroll.append(calculated_total / 10000) # 转换为万人
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# 添加2022年基数的粉色折线
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base_year = "2022"
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# 找到2022年在years中的索引位置
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base_index = years.index(base_year) if base_year in years else 0
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# 获取2022年的总入园数作为基数
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base_value = total_enroll[base_index] if base_index < len(total_enroll) else 0
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# 创建2022年基数折线数据（2022-2024年）
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base_2022_line = []
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for i, year in enumerate(years):
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# 只在2022年及之后显示基数线
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if i >= base_index:
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base_2022_line.append(base_value)
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else:
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base_2022_line.append(None) # 2022年之前不显示
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data = {"xAxis_data": years,
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"series_data_0": urban_data, # 城区
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"series_data_1": town_data, # 镇区
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"series_data_2": rural_data, # 乡村
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"series_data_3": total_enroll, # 总入园数
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"series_data_4": base_2022_line # 2022年基数
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}
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return data
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@staticmethod
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def generate_in_school_education_config():
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# 获取学前教育相关数据
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enrollment_data, in_school_data = RuYuanZaiYuanModel.load_student_data()
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# 提取云南省级数据
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yunnan_in_school = next((item for item in in_school_data if item["area_name"] == "云南省"), None)
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if not yunnan_in_school:
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return {}
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# 提取年份数据(2015-2024)
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years = [str(year) for year in range(2015, 2025)]
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# 构建学前教育数据
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urban_data = [] # 城区数据
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town_data = [] # 镇区数据
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rural_data = [] # 乡村数据
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total_in_school = [] # 总在园数
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for year in years:
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# 将education_data改为student_data
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in_school_year_data = yunnan_in_school["student_data"]["preschool"].get(year, {})
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# 先获取原始数据
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urban_val = in_school_year_data.get("urban", 0)
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town_val = in_school_year_data.get("town", 0)
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rural_val = in_school_year_data.get("rural", 0)
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# 转换为万人并添加到各自列表
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urban_data.append(urban_val / 10000) # 转换为万人
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town_data.append(town_val / 10000) # 转换为万人
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rural_data.append(rural_val / 10000) # 转换为万人
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# 计算总和并转换为万人
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calculated_total = (urban_val + town_val + rural_val) / 10000 # 先计算总和再转换为万人
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total_in_school.append(calculated_total)
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# 添加2022年基数的粉色折线
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base_year = "2022"
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# 找到2022年在years中的索引位置
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base_index = years.index(base_year) if base_year in years else 0
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# 获取2022年的总在园数作为基数
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base_value = total_in_school[base_index] if base_index < len(total_in_school) else 0
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# 创建2022年基数折线数据（2022-2024年）
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base_2022_line = []
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for i, year in enumerate(years):
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# 只在2022年及之后显示基数线
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if i >= base_index:
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base_2022_line.append(base_value)
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else:
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base_2022_line.append(None) # 2022年之前不显示
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data = {
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"data1": ["城区", "镇区", "乡村", "总在园数", "2022年基数"],
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"data2": years,
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"data3": urban_data,
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"data4": town_data,
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"data5": rural_data,
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"data6": total_in_school,
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"data7": base_2022_line
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}
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return data
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