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import logging
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import pymysql
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import subprocess
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import numpy as np
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from matplotlib import pyplot as plt
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#%matplotlib inline
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from tkinter import Tk
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from pyecharts import options as _opts
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from pyecharts.charts import Bar
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logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
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#db_config={'host':'127.0.0.1','user':'root','password':'mysql>hyx123','db':'airquility','charset':'utf8'}
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#ptimelist=[]
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#cilist=[]
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#data_dict=dict(zip(ptimelist,cilist))
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jan_list = []
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feb_list = []
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mar_list = []
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apr_list = []
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may_list = []
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ptime_list = []
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def get_data(db_config):
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"""
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从数据库中获取ptime和ci数据。
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:param db_config: 数据库配置字典
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:return: 包含ptime和ci的元组列表
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"""
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# 存储ptime数据的列表
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try:
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with pymysql.connect(**db_config) as conn:
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logging.info("数据库连接成功")
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with conn.cursor() as cursor:
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# 使用单个查询以提高性能
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sql_ptime = "SELECT ptime FROM May"
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cursor.execute(sql_ptime)
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data_ptime = cursor.fetchall()
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ptime_list = [row['ptime'] for row in data_ptime if 'ptime' in row]
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sql_may = "SELECT pm FROM may"
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cursor.execute(sql_may)
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data_may = cursor.fetchall()
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may_list = [row['pm'] for row in data_may if 'pm' in row]
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sql_feb="SELECT pm FROM feb"
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cursor.execute(sql_feb)
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data_feb=cursor.fetchall()
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#print(data_ci)
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feb_list = [row['pm'] for row in data_feb if 'pm' in row]
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sql_jan = "SELECT pm FROM jan"
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cursor.execute(sql_jan)
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data_jan = cursor.fetchall()
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# print(data_ci)
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jan_list = [row['pm'] for row in data_jan if 'pm' in row]
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sql_mar = "SELECT pm FROM mar"
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cursor.execute(sql_mar)
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data_mar = cursor.fetchall()
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# print(data_ci)
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mar_list = [row['pm'] for row in data_mar if 'pm' in row]
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sql_apr = "SELECT pm FROM apr"
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cursor.execute(sql_apr)
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data_apr = cursor.fetchall()
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# print(data_ci)
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apr_list = [row['pm'] for row in data_apr if 'pm' in row]
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return ptime_list, may_list, feb_list, jan_list, mar_list, apr_list
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except pymysql.err.OperationalError as e:
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logging.error(f"数据库操作失败: {e}")
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# 根据具体场景，可以选择返回空列表、抛出异常或返回特定错误码
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return [], [], [], [], [], []
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def average(str_list):
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if not str_list: # 检查列表是否为空
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return 0 # 或者根据需要处理，比如返回None或者抛出异常
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num_list = [float(item) for item in str_list] # 假设可能有浮点数
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return sum(num_list) / len(num_list)
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def visualize_data(ptime_list, may_list, feb_list, jan_list, mar_list, apr_list):
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"""
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可视化数据。
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:param ptime_list: ptime数据列表
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:param ci_list: ci数据列表
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:param column_to_plot: 需要绘制的列名
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"""
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if not may_list or not feb_list or not jan_list:
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logging.error("数据为空，无法进行可视化")
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return
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#y_list=[]
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#for i in range(4,8):
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# y_list.append(i)
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x = np.arange(26)
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bar_width = 0.2
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# 调用函数并打印结果
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jan_value = average(jan_list)
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feb_value = average(feb_list)
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may_value = average(may_list)
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mar_value = average(mar_list)
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apr_value = average(apr_list)
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# 创建图形对象
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fig = plt.figure("average_pm2.5")
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#plt.title('每月pm2.5平均指数')
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# 创建子图
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ax = fig.add_axes([0, 0, 1, 1])
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# 让饼状图变成圆形
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ax.axis('equal')
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# 准备数据
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#labels = ['jan', 'feb', 'may','mar','apr']
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#num_data = [jan_value, feb_value, may_value, mar_value, apr_value]
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plt.figure(figsize=(15, 10), dpi=80)
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plt.bar(ptime_list, apr_value, tick_label=ptime_list, width=bar_width)
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plt.bar(x + bar_width, may_value, width=bar_width)
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# 饼状图之间的间隙大小
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#explode = (0.02, 0.03, 0.02, 0.01, 0.01)
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# 画饼
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#ax.pie(num_data, labels=labels, autopct='%1.1f%%', explode=explode)
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plt.show()
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if __name__ == "__main__":
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db_config = {
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"host": '127.0.0.1',
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"user": "root",
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"password": 'mysql>hyx123',
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"db": 'airquility',
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"charset": 'utf8',
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"cursorclass": pymysql.cursors.DictCursor
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}
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ptime_list, may_list, feb_list, jan_list, mar_list, apr_list= get_data(db_config)
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visualize_data(ptime_list, may_list, feb_list, jan_list, mar_list, apr_list)
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#print(pymysql.__version__)
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'''
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window= Tk()
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window.title("每日空气质量")
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window.geometry("300x200")
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#Label(window, text="图表已生成为air_quality_index.html").pack()
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window.mainloop()
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'''
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