def add_yaxis(# 系列名称，用于 tooltip 的显示，legend 的图例筛选。series_name: str,# 系列数据y_axis: Sequence[Numeric, opts.BarItem, dict],# 是否选中图例is_selected: bool = True,# 使用的 x 轴的 index，在单个图表实例中存在多个 x 轴的时候有用。xaxis_index: Optional[Numeric] = None,# 使用的 y 轴的 index，在单个图表实例中存在多个 y 轴的时候有用。yaxis_index: Optional[Numeric] = None,# 系列 label 颜色color: Optional[str] = None,# 数据堆叠，同个类目轴上系列配置相同的stack值可以堆叠放置。stack: Optional[str] = None,# 同一系列的柱间距离，默认为类目间距的 20%，可设固定值category_gap: Union[Numeric, str] = "20%",# 不同系列的柱间距离，为百分比（如 '30%'，表示柱子宽度的 30%）。# 如果想要两个系列的柱子重叠，可以设置 gap 为 '-100%'。这在用柱子做背景的时候有用。gap: Optional[str] = None,# 标签配置项，参考 `series_options.LabelOpts`label_opts: Union[opts.LabelOpts, dict] = opts.LabelOpts(),# 标记点配置项，参考 `series_options.MarkPointOpts`markpoint_opts: Union[opts.MarkPointOpts, dict, None] = None,# 标记线配置项，参考 `series_options.MarkLineOpts`markline_opts: Union[opts.MarkLineOpts, dict, None] = None,# 提示框组件配置项，参考 `series_options.TooltipOpts`tooltip_opts: Union[opts.TooltipOpts, dict, None] = None,# 图元样式配置项，参考 `series_options.ItemStyleOpts`itemstyle_opts: Union[opts.ItemStyleOpts, dict, None] = None,# 可以定义 data 的哪个维度被编码成什么。encode: types.Union[types.JSFunc, dict, None] = None,)

堆积柱状图

from pyecharts import options as optsfrom pyecharts.charts import Barfrom mons.utils import JsCodefrom pyecharts.globals import ThemeType# #数据的结构list2 = [{"value": 12, "percent": 12 / (12 + 3)}, # 12+3 ===> 12{"value": 23, "percent": 23 / (23 + 21)},{"value": 33, "percent": 33 / (33 + 5)},{"value": 3, "percent": 3 / (3 + 52)},{"value": 33, "percent": 33 / (33 + 43)},]list3 = [{"value": 3, "percent": 3 / (12 + 3)}, # 12+3 ===> 3{"value": 21, "percent": 21 / (23 + 21)},{"value": 5, "percent": 5 / (33 + 5)},{"value": 52, "percent": 52 / (3 + 52)},{"value": 43, "percent": 43 / (33 + 43)},]# list2=[0.8,0.2,0.3,0.5]# list3=[0.4,0.6,0.3,0.2]c = (# 初始化配置项(主题)Bar(init_opts=opts.InitOpts(theme=ThemeType.MACARONS)).add_xaxis([1, 2, 3, 4, 5])# 堆积柱状图# category_gap 同一系列的柱间距离，默认为类目间距的 20%，可设固定值# gap 不同系列的柱间距离.add_yaxis("product1", list2, stack="stack1", category_gap="50%").add_yaxis("product2", list3, stack="stack1", category_gap="50%")# 系统配置项.set_series_opts(label_opts=opts.LabelOpts(position="left",formatter=JsCode("function(x){return Number(x.data.percent * 100).toFixed() + '%';}"),)).render("C:/stack_bar_percent.html"))

from pyecharts import options as optsfrom pyecharts.charts import Barfrom pyecharts.faker import Fakerfrom pyecharts.globals import ThemeTypec = (Bar(init_opts=opts.InitOpts(theme=ThemeType.LIGHT)).add_xaxis(Faker.choose()).add_yaxis("商家A", Faker.values(), stack="stack1").add_yaxis("商家B", Faker.values(), stack="stack1").set_series_opts(label_opts=opts.LabelOpts(is_show=False)).set_global_opts(title_opts=opts.TitleOpts(title="Bar-堆叠数据（全部）")).render("C:/bar_stack0.html"))

from pyecharts import options as optsfrom pyecharts.charts import Barfrom pyecharts.faker import Fakerfrom pyecharts.globals import ThemeTypec = (Bar(init_opts=opts.InitOpts(theme=ThemeType.LIGHT)).add_xaxis(Faker.choose()).add_yaxis("商家A", Faker.values(), stack="stack1").add_yaxis("商家B", Faker.values(), stack="stack1").add_yaxis("商家C", Faker.values()).set_series_opts(label_opts=opts.LabelOpts(is_show=False)).set_global_opts(title_opts=opts.TitleOpts(title="Bar-堆叠数据（部分）")).render("C:/bar_stack1.html"))

旋转X轴标签

from pyecharts import options as optsfrom pyecharts.charts import Barfrom pyecharts.faker import Fakerfrom pyecharts.globals import ThemeTypec = (Bar({"theme": ThemeType.MACARONS}).add_xaxis(["名字很长的X轴标签1","名字很长的X轴标签2","名字很长的X轴标签3","名字很长的X轴标签4","名字很长的X轴标签5","名字很长的X轴标签6",]).add_yaxis("商家A", Faker.values()).add_yaxis("商家B", Faker.values())#全局配置项.set_global_opts(#设置x轴 （轴标签旋转-15度（顺时针））xaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(rotate=-15)),#标题配置项title_opts=opts.TitleOpts(title="Bar-旋转X轴标签", subtitle="解决标签名字过长的问题"),).render("C:/bar_rotate_xaxis_label.html"))

Bar-Brush示例

from pyecharts import options as optsfrom pyecharts.charts import Barfrom pyecharts.faker import Fakerfrom pyecharts.globals import ThemeTypec = (Bar(init_opts=opts.InitOpts(theme=ThemeType.LIGHT)).add_xaxis(Faker.choose()).add_yaxis("商家A", Faker.values()).add_yaxis("商家B", Faker.values()).set_global_opts(title_opts=opts.TitleOpts(title="Bar-Brush示例", subtitle="我是副标题"),brush_opts=opts.BrushOpts(),).render("C:/bar_with_brush.html"))

数据缩放滑块

from pyecharts import options as optsfrom pyecharts.charts import Barfrom pyecharts.faker import Fakerfrom pyecharts.globals import ThemeTypec = (Bar(init_opts=opts.InitOpts(theme=ThemeType.LIGHT))#初始化.add_xaxis(Faker.days_attrs) #0天-29天.add_yaxis("商家A", Faker.days_values) #全局配置项.set_global_opts(title_opts=opts.TitleOpts(title="Bar-DataZoom（slider-水平）"),#设置数据缩放滑块datazoom_opts=opts.DataZoomOpts(),).render("C:/bar_datazoom_slider.html"))

工具箱

from pyecharts import options as optsfrom pyecharts.charts import Barfrom pyecharts.faker import Fakerfrom pyecharts.globals import ThemeTypec = (Bar(init_opts=opts.InitOpts(theme=ThemeType.LIGHT)).add_xaxis(Faker.choose()).add_yaxis("商家A", Faker.values()).add_yaxis("商家B", Faker.values()).set_global_opts(title_opts=opts.TitleOpts(title="Bar-显示 ToolBox"),toolbox_opts=opts.ToolboxOpts(),#工具箱legend_opts=opts.LegendOpts(is_show=False),).render("bar_toolbox.html"))

柱状瀑布图

from pyecharts.charts import Barfrom pyecharts import options as optsfrom pyecharts.globals import ThemeTypex_data = [f"11月{str(i)}日" for i in range(1, 12)]y_total = [0, 900, 1245, 1530, 1376, 1376, 1511, 1689, 1856, 1495, 1292] #总的y_in = [900, 345, 393, "-", "-", 135, 178, 286, "-", "-", "-"] #收入（正）y_out = ["-", "-", "-", 108, 154, "-", "-", "-", 119, 361, 203] #支出（负）bar = (Bar(init_opts=opts.InitOpts(theme=ThemeType.LIGHT)).add_xaxis(xaxis_data=x_data)#总量.add_yaxis(series_name="",yaxis_data=y_total,stack="总量", #堆积图itemstyle_opts=opts.ItemStyleOpts(color="rgba(0,0,0,0)"),#图元样式配置项，图形的颜色)#收入.add_yaxis(series_name="收入", yaxis_data=y_in, stack="总量")#支出.add_yaxis(series_name="支出", yaxis_data=y_out, stack="总量").set_global_opts(yaxis_opts=opts.AxisOpts(type_="value")) #设置y轴.render("C:/bar_waterfall_plot.html"))