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import pandas as pd
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from pyecharts.charts import Line,Pie,Bar,WordCloud
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from pyecharts import options as opts
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# 读取Excel文件
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df = pd.read_excel('携程餐厅数据.xlsx', skiprows=[1]) # 跳过第一行无效数据
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cuisine_column = '菜系'
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score_column = '评分'
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# 计算各菜系的评分平均分
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cuisine_scores = df.groupby(cuisine_column)[score_column].mean().reset_index()
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cuisine_scores.columns = ['菜系', '平均分']
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# 使用Pyecharts绘制折线图
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line = Line()
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line.add_xaxis(cuisine_scores['菜系'].tolist())
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line.add_yaxis("平均分", cuisine_scores['平均分'].tolist())
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# 设置图表标题、工具提示等
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line.set_global_opts(
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title_opts=opts.TitleOpts(title="各菜系评分平均分折线图"),
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tooltip_opts=opts.TooltipOpts(trigger="axis", axis_pointer_type="cross"),
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xaxis_opts=opts.AxisOpts(type_="category", boundary_gap=False),
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yaxis_opts=opts.AxisOpts(type_="value")
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)
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# 渲染图表到HTML文件
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line.render('cuisine_scores_percent.html')
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# 计算各菜系的消费次数之和（即评论总数之和）
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cuisine_counts = df.groupby('菜系')['评论总数'].sum().reset_index()
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cuisine_counts.columns = ['菜系', '消费次数']
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# 使用Pyecharts绘制饼图
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pie = (
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Pie()
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.add(
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"",
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[list(z) for z in zip(cuisine_counts['菜系'], cuisine_counts['消费次数'])],
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radius=["40%", "75%"], # 设置饼图的内外半径
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label_opts=opts.LabelOpts(formatter="{b}: {c} ({d}%)"), # 标签格式，包括菜系名称、消费次数和百分比
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)
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.set_global_opts(title_opts=opts.TitleOpts(title="各菜系消费次数占比"))
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# 不需要在这里再设置 label_opts，因为它已经在 add 方法中设置过了
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)
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# 渲染图表到HTML文件
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pie.render('cuisine_consumption_pie_chart.html')
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# 计算每个菜系的人均消费总和和平均消费（假设每个菜系有多条记录）
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cuisine_sums = df.groupby('菜系')['人均消费'].sum()
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cuisine_counts = df.groupby('菜系')['人均消费'].count()
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cuisine_averages = cuisine_sums / cuisine_counts
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# 转换为DataFrame以便使用
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cuisine_df = cuisine_averages.reset_index()
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cuisine_df.columns = ['菜系', '平均消费']
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# 绘制柱状图
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bar = Bar()
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bar.add_xaxis(cuisine_df['菜系'].tolist())
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bar.add_yaxis('平均消费', cuisine_df['平均消费'].tolist())
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# 设置全局配置项
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bar.set_global_opts(
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title_opts=opts.TitleOpts(title='各菜系人均消费占比柱状图'),
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xaxis_opts=opts.AxisOpts(name='菜系'),
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yaxis_opts=opts.AxisOpts(name='平均消费'),
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toolbox_opts=opts.ToolboxOpts()
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)
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# 渲染图表到HTML文件（可以在浏览器中打开查看）
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bar.render('cuisine_average_consumption.html')
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