Pyecharts笔记(2)-直角坐标系图表(Bar)

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50.Bar：柱状图/条形图

https://pyecharts.org/#/zh-cn/rectangular_charts

• class pyecharts.charts.Bar(RectChart)

class Bar(# 初始化配置项，参考 `global_options.InitOpts`init_opts: opts.InitOpts = opts.InitOpts()
)

• func pyecharts.charts.Bar.add_yaxis

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,# 是否启用图例 hover 时的联动高亮is_legend_hover_link: bool = True,# 系列 label 颜色color: Optional[str] = None,# 是否显示柱条的背景色。通过 backgroundStyle 配置背景样式。is_show_background: bool = False,# 每一个柱条的背景样式。需要将 showBackground 设置为 true 时才有效。background_style: types.Union[types.BarBackground, dict, None] = 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,# 柱条的宽度，不设时自适应。# 可以是绝对值例如 40 或者百分数例如 '60%'。百分数基于自动计算出的每一类目的宽度。# 在同一坐标系上，此属性会被多个 'bar' 系列共享。此属性应设置于此坐标系中最后一个 'bar' 系列上才会生效，并且是对此坐标系中所有 'bar' 系列生效。bar_width: types.Union[types.Numeric, str] = None,# 柱条的最大宽度。比 barWidth 优先级高。bar_max_width: types.Union[types.Numeric, str] = None,# 柱条的最小宽度。在直角坐标系中，默认值是 1。否则默认值是 null。比 barWidth 优先级高。bar_min_width: types.Union[types.Numeric, str] = None,# 柱条最小高度，可用于防止某数据项的值过小而影响交互。bar_min_height: types.Numeric = 0,# 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] = "30%",# 是否开启大数据量优化，在数据图形特别多而出现卡顿时候可以开启。# 开启后配合 largeThreshold 在数据量大于指定阈值的时候对绘制进行优化。# 缺点：优化后不能自定义设置单个数据项的样式。is_large: bool = False,# 开启绘制优化的阈值。large_threshold: types.Numeric = 400,# 使用 dimensions 定义 series.data 或者 dataset.source 的每个维度的信息。# 注意：如果使用了 dataset，那么可以在 dataset.source 的第一行/列中给出 dimension 名称。# 于是就不用在这里指定 dimension。# 但是，如果在这里指定了 dimensions，那么 ECharts 不再会自动从 dataset.source 的第一行/列中获取维度信息。dimensions: types.Union[types.Sequence, None] = None,# 当使用 dataset 时，seriesLayoutBy 指定了 dataset 中用行还是列对应到系列上，也就是说，系列“排布”到 dataset 的行还是列上。可取值：# 'column'：默认，dataset 的列对应于系列，从而 dataset 中每一列是一个维度（dimension）。# 'row'：dataset 的行对应于系列，从而 dataset 中每一行是一个维度（dimension）。series_layout_by: str = "column",# 如果 series.data 没有指定，并且 dataset 存在，那么就会使用 dataset。# datasetIndex 指定本系列使用那个 dataset。dataset_index: types.Numeric = 0,# 是否裁剪超出坐标系部分的图形。柱状图：裁掉所有超出坐标系的部分，但是依然保留柱子的宽度is_clip: bool = True,# 柱状图所有图形的 zlevel 值。z_level: types.Numeric = 0,# 柱状图组件的所有图形的z值。控制图形的前后顺序。# z值小的图形会被z值大的图形覆盖。# z相比zlevel优先级更低，而且不会创建新的 Canvas。z: types.Numeric = 2,# 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,
)

• BarItem：柱状图数据项

class BarItem(# 数据项名称。name: Optional[str] = None,# 单个数据项的数值。value: Optional[Numeric] = None,# 单个柱条文本的样式设置，参考 `series_options.LabelOpts`。label_opts: Union[LabelOpts, dict, None] = None,# 图元样式配置项，参考 `series_options.ItemStyleOpts`itemstyle_opts: Union[ItemStyleOpts, dict, None] = None,# 提示框组件配置项，参考 `series_options.TooltipOpts`tooltip_opts: Union[TooltipOpts, dict, None] = None,
)

• BarBackgroundStyleOpts：柱状图背景样式配置

class BarBackgroundStyleOpts(# 柱条的颜色。color: str = "rgba(180, 180, 180, 0.2)",# 柱条的描边颜色。border_color: str = "#000",# 柱条的描边宽度，默认不描边。border_width: Numeric = 0,# 柱条的描边类型，默认为实线，支持 'dashed', 'dotted'。border_type: str = "solid",# 圆角半径，单位px，支持传入数组分别指定 4 个圆角半径。 如:# barBorderRadius: 5, // 统一设置四个角的圆角大小# barBorderRadius: [5, 5, 0, 0] //（顺时针左上，右上，右下，左下）bar_border_radius: Union[Numeric, Sequence] = 0,# 图形阴影的模糊大小。# 该属性配合 shadowColor,shadowOffsetX, shadowOffsetY 一起设置图形的阴影效果。shadow_blur: Optional[Numeric] = None,# 阴影颜色。支持的格式同color。shadow_color: Optional[str] = None,# 阴影水平方向上的偏移距离。shadow_offset_x: Numeric = 0,# 阴影垂直方向上的偏移距离。shadow_offset_y: Numeric = 0,# 图形透明度。支持从 0 到 1 的数字，为 0 时不绘制该图形。opacity: Optional[Numeric] = None,
)

50.1 Bar - Stack_bar_percent

链接

from pyecharts import options as opts
from pyecharts.charts import Bar
from pyecharts.commons.utils import JsCode
from pyecharts.globals import ThemeTypelist2 = [{"value": 12, "percent": 12 / (12 + 3)},{"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)},{"value": 21, "percent": 21 / (23 + 21)},{"value": 5, "percent": 5 / (33 + 5)},{"value": 52, "percent": 52 / (3 + 52)},{"value": 43, "percent": 43 / (33 + 43)},
]c = (Bar(init_opts=opts.InitOpts(theme=ThemeType.LIGHT)).add_xaxis([1, 2, 3, 4, 5]).add_yaxis("product1", list2, stack="stack1", category_gap="50%").add_yaxis("product2", list3, stack="stack1", category_gap="50%").set_series_opts(label_opts=opts.LabelOpts(position="right",formatter=JsCode("function(x){return Number(x.data.percent * 100).toFixed() + '%';}"),)).render("stack_bar_percent.html")
)

50.2 Bar - Bar_rotate_xaxis_label

链接

from pyecharts import options as opts
from pyecharts.charts import Barc = (Bar().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", [10, 20, 30, 40, 50, 40]).add_yaxis("商家B", [20, 10, 40, 30, 40, 50]).set_global_opts(xaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(rotate=-15)),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("bar_rotate_xaxis_label.html")
)

50.3 Bar - Bar_stack0

链接

from pyecharts import options as opts
from pyecharts.charts import Bar
from pyecharts.faker import Fakerc = (Bar().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("bar_stack0.html")
)

？50.4 Bar - Finance_indices_2002（略）

链接

50.5 Bar - Bar_base_dict_config

链接

from pyecharts.charts import Bar
from pyecharts.faker import Faker
from pyecharts.globals import ThemeTypec = (Bar({"theme": ThemeType.MACARONS}).add_xaxis(Faker.choose()).add_yaxis("商家A", Faker.values()).add_yaxis("商家B", Faker.values()).set_global_opts(title_opts={"text": "Bar-通过 dict 进行配置", "subtext": "我也是通过 dict 进行配置的"}).render("bar_base_dict_config.html")
)

50.6 Bar - Bar_with_brush

链接

from pyecharts import options as opts
from pyecharts.charts import Bar
from pyecharts.faker import Fakerc = (Bar().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("bar_with_brush.html")
)

50.7 Bar - Bar_datazoom_slider

链接

from pyecharts import options as opts
from pyecharts.charts import Bar
from pyecharts.faker import Fakerc = (Bar().add_xaxis(Faker.days_attrs).add_yaxis("商家A", Faker.days_values).set_global_opts(title_opts=opts.TitleOpts(title="Bar-DataZoom（slider-水平）"),datazoom_opts=opts.DataZoomOpts(),).render("bar_datazoom_slider.html")
)

50.8 Bar - Bar_toolbox

链接

from pyecharts import options as opts
from pyecharts.charts import Bar
from pyecharts.faker import Fakerc = (Bar().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(),legend_opts=opts.LegendOpts(is_show=False),).render("bar_toolbox.html")
)

50.9 Bar - Bar_waterfall_plot

链接

from pyecharts.charts import Bar
from pyecharts import options as optsx_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]
y_in = [900, 345, 393, "-", "-", 135, 178, 286, "-", "-", "-"]
y_out = ["-", "-", "-", 108, 154, "-", "-", "-", 119, 361, 203]bar = (Bar().add_xaxis(xaxis_data=x_data).add_yaxis(series_name="",yaxis_data=y_total,stack="总量",itemstyle_opts=opts.ItemStyleOpts(color="rgba(0,0,0,0)"),).add_yaxis(series_name="收入", yaxis_data=y_in, stack="总量").add_yaxis(series_name="支出", yaxis_data=y_out, stack="总量").set_global_opts(yaxis_opts=opts.AxisOpts(type_="value")).render("bar_waterfall_plot.html")
)

50.10 Bar - Mixed_bar_and_line

链接

import pyecharts.options as opts
from pyecharts.charts import Bar, Line"""
Gallery 使用 pyecharts 1.1.0
参考地址: https://www.echartsjs.com/examples/editor.html?c=mix-line-bar目前无法实现的功能:1、暂无
"""x_data = ["1月", "2月", "3月", "4月", "5月", "6月", "7月", "8月", "9月", "10月", "11月", "12月"]bar = (Bar(init_opts=opts.InitOpts(width="1600px", height="800px")).add_xaxis(xaxis_data=x_data).add_yaxis(series_name="蒸发量",yaxis_data=[2.0,4.9,7.0,23.2,25.6,76.7,135.6,162.2,32.6,20.0,6.4,3.3,],label_opts=opts.LabelOpts(is_show=False),).add_yaxis(series_name="降水量",yaxis_data=[2.6,5.9,9.0,26.4,28.7,70.7,175.6,182.2,48.7,18.8,6.0,2.3,],label_opts=opts.LabelOpts(is_show=False),).extend_axis(yaxis=opts.AxisOpts(name="温度",type_="value",min_=0,max_=25,interval=5,axislabel_opts=opts.LabelOpts(formatter="{value} °C"),)).set_global_opts(tooltip_opts=opts.TooltipOpts(is_show=True, trigger="axis", axis_pointer_type="cross"),xaxis_opts=opts.AxisOpts(type_="category",axispointer_opts=opts.AxisPointerOpts(is_show=True, type_="shadow"),),yaxis_opts=opts.AxisOpts(name="水量",type_="value",min_=0,max_=250,interval=50,axislabel_opts=opts.LabelOpts(formatter="{value} ml"),axistick_opts=opts.AxisTickOpts(is_show=True),splitline_opts=opts.SplitLineOpts(is_show=True),),)
)line = (Line().add_xaxis(xaxis_data=x_data).add_yaxis(series_name="平均温度",yaxis_index=1,y_axis=[2.0, 2.2, 3.3, 4.5, 6.3, 10.2, 20.3, 23.4, 23.0, 16.5, 12.0, 6.2],label_opts=opts.LabelOpts(is_show=False),)
)bar.overlap(line).render("mixed_bar_and_line.html")

50.11 Bar - Bar_stack1

链接

from pyecharts import options as opts
from pyecharts.charts import Bar
from pyecharts.faker import Fakerc = (Bar().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("bar_stack1.html")
)

50.12 Bar - Bar_xyaxis_name

链接

from pyecharts import options as opts
from pyecharts.charts import Bar
from pyecharts.faker import Fakerc = (Bar().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-XY 轴名称"),yaxis_opts=opts.AxisOpts(name="我是 Y 轴"),xaxis_opts=opts.AxisOpts(name="我是 X 轴"),).render("bar_xyaxis_name.html")
)

50.13 Bar - Bar_base_with_custom_background_image

链接

from pyecharts import options as opts
from pyecharts.charts import Bar
from pyecharts.commons.utils import JsCode
from pyecharts.faker import Fakerc = (Bar(init_opts=opts.InitOpts(bg_color={"type": "pattern", "image": JsCode("img"), "repeat": "no-repeat"})).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-背景图基本示例",subtitle="我是副标题",title_textstyle_opts=opts.TextStyleOpts(color="white"),))
)
c.add_js_funcs("""var img = new Image(); img.src = 'https://s2.ax1x.com/2019/07/08/ZsS0fK.jpg';"""
)
c.render("bar_base_with_custom_background_image.html")

50.14 Bar - Bar_chart_display_delay（动画延迟效果暂时没有加入到代码中）

链接

import pyecharts.options as opts
from pyecharts.charts import Bar"""
Gallery 使用 pyecharts 1.1.0
参考地址: https://www.echartsjs.com/examples/editor.html?c=bar-animation-delay目前无法实现的功能:1、动画延迟效果暂时没有加入到代码中
"""category = ["类目{}".format(i) for i in range(0, 100)]
red_bar = [0,-8.901463875624668,-17.025413764148556,-24.038196249566663,-29.66504684804471,-33.699527649688676,-36.00971978255796,-36.541005056170455,-35.31542466107655,-32.427752866005996,-28.038563739693934,-22.364693082297347,-15.667600860943732,-8.240217424060843,-0.3929067389459173,7.560799717904647,15.318054209871054,22.599523033552096,29.16065418543528,34.800927952557615,39.37074152590451,42.77569739999406,44.97819140223978,45.99632376477021,45.900279829731865,44.806440199911805,42.86957840395034,40.2735832137877,37.22119936652441,33.92331243435557,30.588309963978517,27.412031986865767,24.56878097935778,22.203796820272576,20.427519715115604,19.311867685884827,18.888649906111855,19.150128087782186,20.051630602288828,21.516023200879346,23.439750867099516,25.700091656548704,28.163208735293757,30.692553648214542,33.1571635093161,35.439407573791215,37.44177367693234,39.09234039030659,40.34865356244595,41.19981246258526,41.66666666666667,41.80012531240646,41.67768039516203,41.39834040182826,41.07625507973403,40.833382300579814,40.79160029175877,41.06470032034727,41.75070457358366,42.924940903672564,44.63427081999565,46.89281122872821,49.679416561286956,52.93709961387478,56.574470884754874,60.46917221906629,64.47317623531558,68.41972346252496,72.1315793340836,75.43021771943799,78.14548044723074,80.12522637371026,81.24447108408411,81.41353029256493,80.58471628367427,78.75719600392792,75.97969924353211,72.35086229880064,68.01710226438443,63.16803467673056,58.029567166714706,52.854918421647554,47.91391949819902,43.48104807503482,39.82272085822884,37.18442111754884,35.778264289169215,35.77160292258658,37.27724241244461,40.345781666728996,44.96051012913295,51.035187614675685,58.41491053964701,66.8801325453253,76.15376513468516,85.91114110149952,95.79248672571518,105.41742429574506,114.40092042993717,122.37001313784816,
]
blue_bar = [-50,-47.18992898088751,-42.54426104547181,-36.290773900754886,-28.71517529663627,-20.146937097399626,-10.94374119697364,-1.4752538113770308,7.893046603320797,16.81528588241657,24.979206795219028,32.11821023962515,38.02096119056733,42.53821720798438,45.58667093073836,47.14973738101559,47.275355710354944,46.07100702178889,43.6962693226927,40.35333240268025,36.275975292575026,31.71756381888028,26.938653692729076,22.194784893913152,17.725026430574392,13.741778696752679,10.422266555457615,7.902063853319403,6.270884006107842,5.570756810898967,5.796594266992678,6.899033489892203,8.7893381290192,11.346045936704996,14.42297348773613,17.858132851517098,21.483081596548438,25.132218074866262,28.651548555679597,31.906490373810854,34.788333671419466,37.21906041552118,39.154309232933485,40.58437366457342,41.5332247510366,42.05565130942339,42.23270781895,42.165745792772285,41.969375711588256,41.76375960543808,41.66666666666667,41.7857343479728,42.21136481847887,43.01065209435119,44.22268037417866,45.855461823273586,47.88469584957917,50.25443606443524,52.879650371477126,55.650558977584225,58.43853958732492,61.10330341815434,63.500974294013034,65.49264961151306,66.95298925309743,67.77836838841961,67.89414332224722,67.26061575374229,65.87733853082335,63.785482681031894,61.068077697490004,57.84804048526095,54.284018163297375,50.564180830851214,46.89820707575337,43.50780217852947,40.616171775045245,38.4369379107128,37.16302649485318,36.95607267600796,37.93688225696513,40.17745279877072,43.694998595987045,48.44834150353593,54.33692802801367,61.20261650152743,68.83425165632042,76.97491319735354,85.33159602026458,93.58695857541488,101.4126683297632,108.48378461530217,114.49355390682695,119.16795429637915,122.27931702317058,123.65837448506679,123.20413594805603,120.89107255501017,116.7731992576505,110.98476877890735,
](Bar(init_opts=opts.InitOpts(width="1600px", height="800px")).add_xaxis(xaxis_data=category).add_yaxis(series_name="bar", yaxis_data=red_bar, label_opts=opts.LabelOpts(is_show=False)).add_yaxis(series_name="bar2",yaxis_data=blue_bar,label_opts=opts.LabelOpts(is_show=False),).set_global_opts(title_opts=opts.TitleOpts(title="柱状图动画延迟"),xaxis_opts=opts.AxisOpts(splitline_opts=opts.SplitLineOpts(is_show=False)),yaxis_opts=opts.AxisOpts(axistick_opts=opts.AxisTickOpts(is_show=True),splitline_opts=opts.SplitLineOpts(is_show=True),),).render("bar_chart_display_delay.html")
)

50.15 Bar - Bar_datazoom_slider_vertical

链接

from pyecharts import options as opts
from pyecharts.charts import Bar
from pyecharts.faker import Fakerc = (Bar().add_xaxis(Faker.days_attrs).add_yaxis("商家A", Faker.days_values, color=Faker.rand_color()).set_global_opts(title_opts=opts.TitleOpts(title="Bar-DataZoom（slider-垂直）"),datazoom_opts=opts.DataZoomOpts(orient="vertical"),).render("bar_datazoom_slider_vertical.html")
)

50.16 Bar - Bar_histogram_color

链接

from pyecharts import options as opts
from pyecharts.charts import Bar
from pyecharts.faker import Fakerx = Faker.dogs + Faker.animal
xlen = len(x)
y = []
for idx, item in enumerate(x):if idx <= xlen / 2:y.append(opts.BarItem(name=item,value=(idx + 1) * 10,itemstyle_opts=opts.ItemStyleOpts(color="#749f83"),))else:y.append(opts.BarItem(name=item,value=(xlen + 1 - idx) * 10,itemstyle_opts=opts.ItemStyleOpts(color="#d48265"),))c = (Bar().add_xaxis(x).add_yaxis("series0", y, category_gap=0, color=Faker.rand_color()).set_global_opts(title_opts=opts.TitleOpts(title="Bar-直方图（颜色区分）")).render("bar_histogram_color.html")
)

50.17 Bar - Bar_yaxis_formatter

链接

from pyecharts import options as opts
from pyecharts.charts import Bar
from pyecharts.faker import Fakerc = (Bar().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-Y 轴 formatter"),yaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(formatter="{value} /月")),).render("bar_yaxis_formatter.html")
)

50.18 Bar - Bar_markpoint_type

链接

from pyecharts import options as opts
from pyecharts.charts import Bar
from pyecharts.faker import Fakerc = (Bar().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-MarkPoint（指定类型）")).set_series_opts(label_opts=opts.LabelOpts(is_show=False),markpoint_opts=opts.MarkPointOpts(data=[opts.MarkPointItem(type_="max", name="最大值"),opts.MarkPointItem(type_="min", name="最小值"),opts.MarkPointItem(type_="average", name="平均值"),]),).render("bar_markpoint_type.html")
)

50.19 Bar - Multiple_y_axes

链接

import pyecharts.options as opts
from pyecharts.charts import Bar, Line"""
Gallery 使用 pyecharts 1.0.0
参考地址: https://www.echartsjs.com/examples/editor.html?c=multiple-y-axis目前无法实现的功能:1、暂无
"""colors = ["#5793f3", "#d14a61", "#675bba"]
x_data = ["1月", "2月", "3月", "4月", "5月", "6月", "7月", "8月", "9月", "10月", "11月", "12月"]
legend_list = ["蒸发量", "降水量", "平均温度"]
evaporation_capacity = [2.0,4.9,7.0,23.2,25.6,76.7,135.6,162.2,32.6,20.0,6.4,3.3,
]
rainfall_capacity = [2.6,5.9,9.0,26.4,28.7,70.7,175.6,182.2,48.7,18.8,6.0,2.3,
]
average_temperature = [2.0, 2.2, 3.3, 4.5, 6.3, 10.2, 20.3, 23.4, 23.0, 16.5, 12.0, 6.2]bar = (Bar(init_opts=opts.InitOpts(width="1680px", height="800px")).add_xaxis(xaxis_data=x_data).add_yaxis(series_name="蒸发量",yaxis_data=evaporation_capacity,yaxis_index=0,color=colors[1],).add_yaxis(series_name="降水量", yaxis_data=rainfall_capacity, yaxis_index=1, color=colors[0]).extend_axis(yaxis=opts.AxisOpts(name="蒸发量",type_="value",min_=0,max_=250,position="right",axisline_opts=opts.AxisLineOpts(linestyle_opts=opts.LineStyleOpts(color=colors[1])),axislabel_opts=opts.LabelOpts(formatter="{value} ml"),)).extend_axis(yaxis=opts.AxisOpts(type_="value",name="温度",min_=0,max_=25,position="left",axisline_opts=opts.AxisLineOpts(linestyle_opts=opts.LineStyleOpts(color=colors[2])),axislabel_opts=opts.LabelOpts(formatter="{value} °C"),splitline_opts=opts.SplitLineOpts(is_show=True, linestyle_opts=opts.LineStyleOpts(opacity=1)),)).set_global_opts(yaxis_opts=opts.AxisOpts(type_="value",name="降水量",min_=0,max_=250,position="right",offset=80,axisline_opts=opts.AxisLineOpts(linestyle_opts=opts.LineStyleOpts(color=colors[0])),axislabel_opts=opts.LabelOpts(formatter="{value} ml"),),tooltip_opts=opts.TooltipOpts(trigger="axis", axis_pointer_type="cross"),)
)line = (Line().add_xaxis(xaxis_data=x_data).add_yaxis(series_name="平均温度", y_axis=average_temperature, yaxis_index=2, color=colors[2])
)bar.overlap(line).render("multiple_y_axes.html")

50.20 Bar - Bar_custom_bar_color

链接

from pyecharts import options as opts
from pyecharts.charts import Bar
from pyecharts.commons.utils import JsCode
from pyecharts.faker import Fakercolor_function = """function (params) {if (params.value > 0 && params.value < 50) {return 'red';} else if (params.value > 50 && params.value < 100) {return 'blue';}return 'green';}"""
c = (Bar().add_xaxis(Faker.choose()).add_yaxis("商家A",Faker.values(),itemstyle_opts=opts.ItemStyleOpts(color=JsCode(color_function)),).add_yaxis("商家B",Faker.values(),itemstyle_opts=opts.ItemStyleOpts(color=JsCode(color_function)),).add_yaxis("商家C",Faker.values(),itemstyle_opts=opts.ItemStyleOpts(color=JsCode(color_function)),).set_global_opts(title_opts=opts.TitleOpts(title="Bar-自定义柱状颜色")).render("bar_custom_bar_color.html")
)

50.21 Bar - Bar_different_series_gap

链接

from pyecharts import options as opts
from pyecharts.charts import Bar
from pyecharts.faker import Fakerc = (Bar().add_xaxis(Faker.choose()).add_yaxis("商家A", Faker.values(), gap="0%").add_yaxis("商家B", Faker.values(), gap="0%").set_global_opts(title_opts=opts.TitleOpts(title="Bar-不同系列柱间距离")).render("bar_different_series_gap.html")
)

50.22 Bar - Bar_markline_type

链接

from pyecharts import options as opts
from pyecharts.charts import Bar
from pyecharts.faker import Fakerc = (Bar().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-MarkLine（指定类型）")).set_series_opts(label_opts=opts.LabelOpts(is_show=False),markline_opts=opts.MarkLineOpts(data=[opts.MarkLineItem(type_="min", name="最小值"),opts.MarkLineItem(type_="max", name="最大值"),opts.MarkLineItem(type_="average", name="平均值"),]),)
)

？50.23 Bar - Bar_border_radius

链接

from pyecharts import options as opts
from pyecharts.charts import Bar
from pyecharts.commons.utils import JsCode
from pyecharts.faker import Fakerc = (Bar().add_xaxis(Faker.choose()).add_yaxis("商家A", Faker.values(), category_gap="60%").set_series_opts(itemstyle_opts={"normal": {"color": JsCode("""new echarts.graphic.LinearGradient(0, 0, 0, 1, [{offset: 0,color: 'rgba(0, 244, 255, 1)'}, {offset: 1,color: 'rgba(0, 77, 167, 1)'}], false)"""),"barBorderRadius": [30, 30, 30, 30],"shadowColor": "rgb(0, 160, 221)",}}).set_global_opts(title_opts=opts.TitleOpts(title="Bar-渐变圆柱")).render("bar_border_radius.html")
)

50.24 Bar - Bar_same_series_gap

链接

from pyecharts import options as opts
from pyecharts.charts import Bar
from pyecharts.faker import Fakerc = (Bar().add_xaxis(Faker.choose()).add_yaxis("商家A", Faker.values(), category_gap="80%").set_global_opts(title_opts=opts.TitleOpts(title="Bar-单系列柱间距离")).render("bar_same_series_gap.html")
)

50.25 Bar - Bar_datazoom_inside

链接

from pyecharts import options as opts
from pyecharts.charts import Bar
from pyecharts.faker import Fakerc = (Bar().add_xaxis(Faker.days_attrs).add_yaxis("商家A", Faker.days_values, color=Faker.rand_color()).set_global_opts(title_opts=opts.TitleOpts(title="Bar-DataZoom（inside）"),datazoom_opts=opts.DataZoomOpts(type_="inside"),).render("bar_datazoom_inside.html")
)

50.26 Bar - Bar_is_selected

链接

from pyecharts import options as opts
from pyecharts.charts import Bar
from pyecharts.faker import Fakerc = (Bar().add_xaxis(Faker.choose()).add_yaxis("商家A", Faker.values()).add_yaxis("商家B", Faker.values(), is_selected=False).set_global_opts(title_opts=opts.TitleOpts(title="Bar-默认取消显示某 Series")).render("bar_is_selected.html")
)

50.27 Bar - Bar_reversal_axis

链接

from pyecharts import options as opts
from pyecharts.charts import Bar
from pyecharts.faker import Fakerc = (Bar().add_xaxis(Faker.choose()).add_yaxis("商家A", Faker.values()).add_yaxis("商家B", Faker.values()).reversal_axis().set_series_opts(label_opts=opts.LabelOpts(position="right")).set_global_opts(title_opts=opts.TitleOpts(title="Bar-翻转 XY 轴")).render("bar_reversal_axis.html")
)

50.28 Bar - Bar_markpoint_custom

链接

from pyecharts import options as opts
from pyecharts.charts import Bar
from pyecharts.faker import Fakerx, y = Faker.choose(), Faker.values()
c = (Bar().add_xaxis(x).add_yaxis("商家A",y,markpoint_opts=opts.MarkPointOpts(data=[opts.MarkPointItem(name="自定义标记点", coord=[x[2], y[2]], value=y[2])]),).add_yaxis("商家B", Faker.values()).set_global_opts(title_opts=opts.TitleOpts(title="Bar-MarkPoint（自定义）")).set_series_opts(label_opts=opts.LabelOpts(is_show=False)).render("bar_markpoint_custom.html")
)

50.29 Bar - Bar_base_with_animation

链接

from pyecharts import options as opts
from pyecharts.charts import Bar
from pyecharts.faker import Fakerc = (Bar(init_opts=opts.InitOpts(animation_opts=opts.AnimationOpts(animation_delay=1000, animation_easing="elasticOut"))).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-动画配置基本示例", subtitle="我是副标题")).render("bar_base_with_animation.html")
)

50.30 Bar - Bar_histogram

链接

from pyecharts import options as opts
from pyecharts.charts import Bar
from pyecharts.faker import Fakerc = (Bar().add_xaxis(Faker.choose()).add_yaxis("商家A", Faker.values(), category_gap=0, color=Faker.rand_color()).set_global_opts(title_opts=opts.TitleOpts(title="Bar-直方图")).render("bar_histogram.html")
)

50.31 Bar - Bar_markline_custom

链接

from pyecharts import options as opts
from pyecharts.charts import Bar
from pyecharts.faker import Fakerc = (Bar().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-MarkLine（自定义）")).set_series_opts(label_opts=opts.LabelOpts(is_show=False),markline_opts=opts.MarkLineOpts(data=[opts.MarkLineItem(y=50, name="yAxis=50")]),).render("bar_markline_custom.html")
)

50.32 Bar - Bar_base

链接

from pyecharts import options as opts
from pyecharts.charts import Bar
from pyecharts.faker import Fakerc = (Bar().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-基本示例", subtitle="我是副标题")).render("bar_base.html")
)

50.33 Bar - Bar_datazoom_both

链接

from pyecharts import options as opts
from pyecharts.charts import Bar
from pyecharts.faker import Fakerc = (Bar().add_xaxis(Faker.days_attrs).add_yaxis("商家A", Faker.days_values, color=Faker.rand_color()).set_global_opts(title_opts=opts.TitleOpts(title="Bar-DataZoom（slider+inside）"),datazoom_opts=[opts.DataZoomOpts(), opts.DataZoomOpts(type_="inside")],).render("bar_datazoom_both.html")
)

51.Bar实践项目

51.1 Bar - Bar_markpoint_custom：add_yaxis()的markpoint_opts=opts.MarkPointOpts()会让set_series_opts()的markpoint_opts=opts.MarkPointOpts()失效

链接
链接

def Bar_markpoint_type2():x = ['河马', '蟒蛇', '老虎', '大象', '兔子', '熊猫', '狮子']y1 = [66, 39, 35, 85, 107, 126, 105]y2 = [89, 86, 116, 51, 137, 76, 146]c = (Bar().add_xaxis(x).add_yaxis("商家A", y1, gap="0%",category_gap="80%").add_yaxis("商家B", y2, gap="0%",category_gap="80%",markpoint_opts=opts.MarkPointOpts(data=[opts.MarkPointItem(name="自定义标记点1", coord=[x[2], y2[2]], value=y2[2])]),)#.reversal_axis().set_global_opts(title_opts=opts.TitleOpts(title="Bar_markpoint_type2"),datazoom_opts=opts.DataZoomOpts(),).set_series_opts(label_opts=opts.LabelOpts(is_show=False),##### add_yaxis()的markpoint_opts=opts.MarkPointOpts()会让set_series_opts()的markpoint_opts=opts.MarkPointOpts()失效######markpoint_opts=opts.MarkPointOpts(#    data=[#        opts.MarkPointItem(type_="max", name="最大值"),#        opts.MarkPointItem(type_="min", name="最小值"),#        opts.MarkPointItem(type_="average", name="平均值"),#    ]#),markline_opts=opts.MarkLineOpts(data=[opts.MarkLineItem(type_="min", name="最小值"),opts.MarkLineItem(type_="max", name="最大值"),opts.MarkLineItem(type_="average", name="平均值"),]),)
)return c

51.2 Bar综合例子1

def Stack_bar_percent():list2 = [{"value": 50, "percent": 50 / (50 + 0)},{"value": 34, "percent": 34 / (34 + 37)},]list3 = [{"value": 0, "percent": 0 / (50 + 0)},{"value": 37, "percent": 37 / (34 + 37)},]list4 = [{"value": 50, "percent": 50 / (50 + 0)},{"value": 34, "percent": 34 / (34 + 37)},]list5 = [{"value": 0, "percent": 0 / (50 + 0)},{"value": 37, "percent": 37 / (34 + 37)},]c = (Bar(init_opts=opts.InitOpts(theme=ThemeType.LIGHT,bg_color={"type": "pattern", "image": JsCode("img"), "repeat": "no-repeat"})).add_xaxis(['2020','2021']).add_yaxis("火炬职院1-stack", list2, stack="stack1", category_gap="50%").add_yaxis("电子科大1", list3, stack="stack1", category_gap="50%",is_selected=False).add_yaxis("火炬职院2", list4, stack="stack0", category_gap="50%").add_yaxis("电子科大2", list5, stack="stack0", category_gap="50%").set_series_opts(label_opts=opts.LabelOpts(position="right",formatter=JsCode("function(x){return Number(x.data.percent * 100).toFixed() + '%';}"),)).set_global_opts(title_opts=TitleOpts(title='报名人数对比'),xaxis_opts=opts.AxisOpts(name='我是X轴',axislabel_opts=opts.LabelOpts(rotate=-15)),yaxis_opts=opts.AxisOpts(name='我是Y轴',axislabel_opts=opts.LabelOpts(formatter="{value} /人")),brush_opts=opts.BrushOpts(),datazoom_opts=opts.DataZoomOpts(orient="vertical"),))c.add_js_funcs("""var img = new Image(); img.src = 'https://gimg2.baidu.com/image_search/src=http%3A%2F%2Fgdown.baidu.com%2Fimg%2F0%2F200_200%2F1c7d0637ca01803040e087fb44e47654.png&refer=http%3A%2F%2Fgdown.baidu.com&app=2002&size=f9999,10000&q=a80&n=0&g=0n&fmt=jpeg?sec=1632878374&t=508cb059ea0f1889a532d817c67bc76b';""")return c

51.3 Bar综合例子2

def Bar_markpoint_type():color_function = """function (params) {if (params.value > 0 && params.value < 50) {return 'red';} else if (params.value > 50 && params.value < 100) {return 'blue';}return 'green';}"""x = ['河马', '蟒蛇', '老虎', '大象', '兔子', '熊猫', '狮子']y1 = [66, 39, 35, 85, 107, 126, 105]y2 = [89, 86, 116, 51, 137, 76, 146]c = (Bar().add_xaxis(x).add_yaxis("商家A", y1, gap="0%",category_gap="80%", itemstyle_opts=opts.ItemStyleOpts(color=JsCode(color_function))).add_yaxis("商家B", y2, gap="0%",category_gap="80%",markpoint_opts=opts.MarkPointOpts(data=[opts.MarkPointItem(name="自定义标记点1", coord=[x[2], y2[2]], value=y2[2])]),itemstyle_opts=opts.ItemStyleOpts(color=JsCode(color_function)))#.reversal_axis().set_global_opts(title_opts=opts.TitleOpts(title="Bar-MarkPoint（指定类型）"),datazoom_opts=opts.DataZoomOpts(type_="inside"),).set_series_opts(label_opts=opts.LabelOpts(is_show=False),markpoint_opts=opts.MarkPointOpts(data=[opts.MarkPointItem(type_="max", name="最大值"),#opts.MarkPointItem(type_="min", name="最小值"),#opts.MarkPointItem(type_="average", name="平均值"),]),markline_opts=opts.MarkLineOpts(data=[opts.MarkLineItem(type_="min", name="最小值"),opts.MarkLineItem(type_="max", name="最大值"),opts.MarkLineItem(type_="average", name="平均值"),]),)
)return c

51.4 Bar综合例子3

def Bar_markpoint_type2():x = ['河马', '蟒蛇', '老虎', '大象', '兔子', '熊猫', '狮子']y1 = [66, 39, 35, 85, 107, 126, 105]y2 = [89, 86, 116, 51, 137, 76, 146]c = (Bar().add_xaxis(x).add_yaxis("商家A", y1, gap="0%",category_gap="80%").add_yaxis("商家B", y2, gap="0%",category_gap="80%",markpoint_opts=opts.MarkPointOpts(data=[opts.MarkPointItem(name="自定义标记点1", coord=[x[2], y2[2]], value=y2[2])]),)#.reversal_axis().set_global_opts(title_opts=opts.TitleOpts(title="Bar_markpoint_type2"),datazoom_opts=[opts.DataZoomOpts(), opts.DataZoomOpts(type_="inside")],).set_series_opts(label_opts=opts.LabelOpts(is_show=False),##### add_yaxis()的markpoint_opts=opts.MarkPointOpts()会让set_series_opts()的markpoint_opts=opts.MarkPointOpts()失效######markpoint_opts=opts.MarkPointOpts(#    data=[#        opts.MarkPointItem(type_="max", name="最大值"),#        opts.MarkPointItem(type_="min", name="最小值"),#        opts.MarkPointItem(type_="average", name="平均值"),#    ]#),markline_opts=opts.MarkLineOpts(data=[opts.MarkLineItem(type_="min", name="最小值"),opts.MarkLineItem(type_="max", name="最大值"),opts.MarkLineItem(type_="average", name="平均值"),opts.MarkLineItem(y=100, name="yAxis=100"),]),)
)return c

51.5 Bar综合例子4

def Bar_waterfall_plot_B():#x_data = [f"{str(i)}月" for i in range(1, 13)]x_data = ["1月期初","1月入职","1月离职","2月入职","2月离职","3月入职","3月离职","4月入职","4月离职","5月入职","5月离职","6月入职","6月离职"]y_total = ["-", 4131,4134,4134,4107,4107,4076,4076,4037,4037,4025,4025,4016]y_in =    [4131,22,  "-", 13,"-",  65,   "-", 69,  "-",84,  "-",  67, "-"]y_out =   ["-", "-", 19,  "-",40,  "-",  96,  "-", 108,"-",  96,  "-",76]bar = (Bar().add_xaxis(xaxis_data=x_data)# add_yaxis()的yaxis_data要变成y_axis.add_yaxis(series_name="",y_axis=y_total,stack="总量",itemstyle_opts=opts.ItemStyleOpts(color="rgba(0,0,0,0)"),).add_yaxis(series_name="入职", y_axis=y_in, stack="总量").add_yaxis(series_name="离职", y_axis=y_out, stack="总量").set_global_opts(title_opts=opts.TitleOpts(title="瀑布图：new"),xaxis_opts=opts.AxisOpts(splitline_opts=opts.SplitLineOpts(is_show=False),axislabel_opts=opts.LabelOpts(rotate=-45)),yaxis_opts=opts.AxisOpts(type_="value",axistick_opts=opts.AxisTickOpts(is_show=True),splitline_opts=opts.SplitLineOpts(is_show=True),# 增加坐标轴的刻度值最小值设定min_='3950'),))return bar

51.6 Bar综合例子5

def Mixed_bar_and_line_ZZ():x_data = ["1月", "2月", "3月", "4月", "5月", "6月", "7月", "8月", "9月", "10月", "11月", "12月"]bar = (Bar(init_opts=opts.InitOpts(width="800px", height="400px")).add_xaxis(xaxis_data=x_data).add_yaxis(series_name="入职人数",y_axis=[22,13,65,69,84,67],label_opts=opts.LabelOpts(is_show=False),).add_yaxis(series_name="离职人数",y_axis=[19,40,96,108,96,76],label_opts=opts.LabelOpts(is_show=False),).extend_axis(yaxis=opts.AxisOpts(name="总人数",type_="value",min_=3500,max_=4200,interval=100,axislabel_opts=opts.LabelOpts(formatter="{value}"),)).set_global_opts(title_opts = opts.TitleOpts(title='ZZ图表'),tooltip_opts=opts.TooltipOpts(is_show=True, trigger="axis", axis_pointer_type="cross"),xaxis_opts=opts.AxisOpts(name="月份",name_location = "center",type_="category",axispointer_opts=opts.AxisPointerOpts(is_show=True, type_="shadow"),),yaxis_opts=opts.AxisOpts(name="变动人力",type_="value",min_=0,#max_=100,interval=10,axislabel_opts=opts.LabelOpts(formatter="{value}"),axistick_opts=opts.AxisTickOpts(is_show=True),splitline_opts=opts.SplitLineOpts(is_show=True),),))line = (Line().add_xaxis(xaxis_data=x_data).add_yaxis(series_name="在职人数",yaxis_index=1,y_axis=[4131, 4144, 4105, 4079, 4058, 4065],label_opts=opts.LabelOpts(is_show=False),))bar.overlap(line)return bar

51.7 Bar综合例子6：看多y轴的要点

注意看多y轴的要点

def Mixed_bar_and_line():x_data = ["1月", "2月", "3月", "4月", "5月", "6月", "7月", "8月", "9月", "10月", "11月", "12月"]bar = (Bar(init_opts=opts.InitOpts(width="900px", height="400px")).add_xaxis(xaxis_data=x_data).add_yaxis(series_name="蒸发量",y_axis=[2.0,4.9,7.0,23.2,25.6,76.7,135.6,162.2,32.6,20.0,6.4,3.3,],label_opts=opts.LabelOpts(is_show=False),).add_yaxis(series_name="降水量",y_axis=[2.6,5.9,9.0,26.4,28.7,70.7,175.6,182.2,48.7,18.8,6.0,2.3,],label_opts=opts.LabelOpts(is_show=False),).extend_axis(yaxis=opts.AxisOpts(name="温度",type_="value",min_=0,max_=25,interval=5,#多y轴的要点position="right",axislabel_opts=opts.LabelOpts(formatter="{value} °C"),)).extend_axis(yaxis=opts.AxisOpts(name="温度2",type_="value",min_=0,max_=25,interval=5,#多y轴的要点offset=40,position="right",axislabel_opts=opts.LabelOpts(formatter="{value} °C"),)).set_global_opts(title_opts = opts.TitleOpts(title='降水量图表'),tooltip_opts=opts.TooltipOpts(is_show=True, trigger="axis", axis_pointer_type="cross"),xaxis_opts=opts.AxisOpts(name="月份",name_location = "center",type_="category",axispointer_opts=opts.AxisPointerOpts(is_show=True, type_="shadow"),),yaxis_opts=opts.AxisOpts(name="降水量",type_="value",min_=0,max_=250,interval=50,#多y轴的要点position="left",axislabel_opts=opts.LabelOpts(formatter="{value} ml"),axistick_opts=opts.AxisTickOpts(is_show=True),splitline_opts=opts.SplitLineOpts(is_show=True),),))line = (Line().add_xaxis(xaxis_data=x_data).add_yaxis(series_name="平均温度",yaxis_index=1,y_axis=[2.0, 2.2, 3.3, 4.5, 6.3, 10.2, 20.3, 23.4, 23.0, 16.5, 12.0, 6.2],label_opts=opts.LabelOpts(is_show=False),))bar.overlap(line)return bar

51.8 Bar综合例子7：append()来添加opts.BarItem()以区别各条的颜色

• 最简单的例子

def Bar_histogram_season():x = ['哈士奇', '萨摩耶', '泰迪', '金毛', '牧羊犬', '吉娃娃', '柯基', '河马', '蟒蛇', '老虎', '大象', '兔子', '熊猫', '狮子']z = [10,20,30,40,50,60,70,80,90,100,110,100,90,80]c = (Bar().add_xaxis(x).add_yaxis("series0", z, category_gap=0).set_global_opts(title_opts=opts.TitleOpts(title="Bar-直方图"))#.render("bar_histogram_color.html"))return c

• 复杂一点的例子

def Bar_histogram_season2():x = ['哈士奇', '萨摩耶', '泰迪', '金毛', '牧羊犬', '吉娃娃', '柯基', '河马', '蟒蛇', '老虎', '大象', '兔子', '熊猫', '狮子']z = [10,20,30,40,50,60,70,80,90,100,110,100,90,80]y = []for idx, ivalue in enumerate(z):if ivalue > 80:y.append(opts.BarItem(name=x[idx],value=ivalue,itemstyle_opts=opts.ItemStyleOpts(color="#749f83"),))else:y.append(opts.BarItem(name=x[idx],value=ivalue,itemstyle_opts=opts.ItemStyleOpts(color="#d48265"),))c = (Bar().add_xaxis(x).add_yaxis("series0", y, category_gap=0).set_global_opts(title_opts=opts.TitleOpts(title="Bar-直方图"))#.render("bar_histogram_color.html"))return c