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import pandas as pd
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from pyecharts import options as opts
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from pyecharts.charts import Pie, Bar, Timeline
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js = pd.read_csv('changsha天气.csv', encoding='gbk')
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js['日期'] = js['日期'].apply(lambda x: pd.to_datetime(x))
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js['month'] = js['日期'].dt.month
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js_agg1 = js.groupby(['month', '天气']).size().reset_index()
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js_agg1.columns = ['month', 'tianqi', 'count']
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print(js_agg1[js_agg1['month'] == 1][['tianqi', 'count']] \
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.sort_values(by='count', ascending=False).values.tolist())
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#实例化一个时间序列的对象
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timeline = Timeline()
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#播放参数:设置时间间隔1s 单位是：ms(毫秒)
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timeline.add_schema(play_interval=1000)
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#循环遍历df_agg['month']里的唯一值
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for month in js_agg1['month'].unique():
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data1 = (
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js_agg1[js_agg1['month'] == month][['tianqi', 'count']]
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.sort_values(by='count', ascending=True)
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.values.tolist()
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)
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# print(data) #绘制柱状图
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bar1 = Bar()
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# x轴是天气名称
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bar1.add_xaxis([x[0] for x in data1])
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# y轴是各天气出现次数
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bar1.add_yaxis('天气情况', [x[1] for x in data1])
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# 让柱状图横着放
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bar1.reversal_axis()
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# 将计数标签放在图形右边
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bar1.set_series_opts(label_opts=opts.LabelOpts(position='right'))
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# 设置下图表的名字
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bar1.set_global_opts(title_opts=opts.TitleOpts(title='长沙2023年每月天气变化'))
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# 将设置好的bar对象放置到时间轮播图中，并且标签选择月份 格式为：数字月
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timeline.add(bar1, f'{month}月')
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timeline.render('长沙天气轮播图.html')
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