折线图
折线图 基本demo
import pyecharts.options as opts
from pyecharts.charts import Line
c = (
Line()
.add_xaxis(["衬衫", "毛衣", "领带", "裤子", "风衣", "高跟鞋", "袜子"])
.add_yaxis('商家A', [114, 55, 27, 101, 125, 27, 105])
.add_yaxis('商家B',[57, 134, 137, 129, 145, 60, 49])
.set_global_opts(title_opts=opts.TitleOpts(title="Line-基本示例"))
)
c.render_notebook()
折线图 如果有空数据连接
import pyecharts.options as opts
from pyecharts.charts import Line
c = (
Line()
.add_xaxis(["衬衫", "毛衣", "领带", "裤子", "风衣", "高跟鞋", "袜子"])
.add_yaxis('商家A', [114, 55, 27, 101, 125, None, 105],is_connect_nones=True)
.add_yaxis('商家B',[57, 134, 137, 129, 145, 60, 49],is_connect_nones=True)
.set_global_opts(title_opts=opts.TitleOpts(title="Line连接空数据"))
)
c.render_notebook()
平滑曲线展示
import pyecharts.options as opts
from pyecharts.charts import Line
c = (
Line()
.add_xaxis(["衬衫", "毛衣", "领带", "裤子", "风衣", "高跟鞋", "袜子"])
.add_yaxis('商家A', [114, 55, 27, 101, 125, None, 105], is_smooth=True,is_connect_nones=True)
.add_yaxis('商家B',[57, 134, 137, 129, 145, 60, 49], is_smooth=True)
.set_global_opts(title_opts=opts.TitleOpts(title="Line-smooth"))
)
c.render_notebook()
面积图:
import pyecharts.options as opts
from pyecharts.charts import Line
c = (
Line()
.add_xaxis(["衬衫", "毛衣", "领带", "裤子", "风衣", "高跟鞋", "袜子"])
.add_yaxis('商家A', [114, 55, 27, 101, 125, 27, 105], areastyle_opts=opts.AreaStyleOpts(opacity=0.5))
.add_yaxis('商家B',[57, 134, 137, 129, 145, 60, 49], areastyle_opts=opts.AreaStyleOpts(opacity=0.5))
.set_global_opts(title_opts=opts.TitleOpts(title="Line-基本示例"))
)
c.render_notebook()
line 面积图 (紧贴y轴) 曲线表示
import pyecharts.options as opts
from pyecharts.charts import Line
c = (
Line()
.add_xaxis(["衬衫", "毛衣", "领带", "裤子", "风衣", "高跟鞋", "袜子"])
.add_yaxis('商家A', [114, 55, 27, 101, 125, 27, 105],is_smooth=True, areastyle_opts=opts.AreaStyleOpts(opacity=0.5))
.add_yaxis('商家B',[57, 134, 137, 129, 145, 60, 49], is_smooth=True, areastyle_opts=opts.AreaStyleOpts(opacity=0.5))
.set_global_opts(title_opts=opts.TitleOpts(title="Line-基本示例"),
xaxis_opts=opts.AxisOpts(
axistick_opts=opts.AxisTickOpts(is_align_with_label=True),
is_scale=False,
boundary_gap=False,
) )
).set_series_opts(
areastyle_opts=opts.AreaStyleOpts(opacity=0.5),
label_opts=opts.LabelOpts(is_show=False),
)
c.render_notebook()
对数轴显示 等比
import pyecharts.options as opts
from pyecharts.charts import Line
c = (
Line()
.add_xaxis(xaxis_data=["一", "二", "三", "四", "五", "六", "七", "八", "九"])
.add_yaxis(
"2 的指数",
y_axis=[1, 2, 4, 8, 16, 32, 64, 128, 256],
linestyle_opts=opts.LineStyleOpts(width=2),
)
.add_yaxis(
"3 的指数",
y_axis=[1, 3, 9, 27, 81, 247, 741, 2223, 6669],
linestyle_opts=opts.LineStyleOpts(width=2),
)
.set_global_opts(
title_opts=opts.TitleOpts(title="Line-对数轴示例"),
xaxis_opts=opts.AxisOpts(name="x"),
yaxis_opts=opts.AxisOpts(
type_="log",
name="y",
splitline_opts=opts.SplitLineOpts(is_show=True),
is_scale=True,
),
)
)
c.render_notebook()
line-markline 平均值
import pyecharts.options as opts
from pyecharts.charts import Line
c = (
Line()
.add_xaxis(["衬衫", "毛衣", "领带", "裤子", "风衣", "高跟鞋", "袜子"])
.add_yaxis(
"商家A",
[114, 55, 27, 101, 125, 27, 105],
markline_opts=opts.MarkLineOpts(data=[opts.MarkLineItem(type_="average")]),
)
.add_yaxis(
"商家B",
[57, 134, 137, 129, 145, 60, 49],
markline_opts=opts.MarkLineOpts(data=[opts.MarkLineItem(type_="average")]),
)
.set_global_opts(title_opts=opts.TitleOpts(title="Line-MarkLine"))
)
c.render_notebook()
混合使用折线图 最大值,最小值 平均值(着重标注)
import pyecharts.options as opts
from pyecharts.charts import Line
c = (
Line()
.add_xaxis(["衬衫", "毛衣", "领带", "裤子", "风衣", "高跟鞋", "袜子"])
.add_yaxis(
"商家A",
[114, 55, 27, 101, 125, 27, 105],
# markline_opts=opts.MarkLineOpts(data=[opts.MarkLineItem(type_="average")]),
markline_opts=opts.MarkLineOpts(data=[opts.MarkLineItem(type_="average")]),
markpoint_opts=opts.MarkPointOpts(data=[opts.MarkPointItem(type_="max"),opts.MarkPointItem(type_="min")]), #点出来
)
.add_yaxis(
"商家B",
[57, 134, 137, 129, 145, 60, 49],
markline_opts=opts.MarkLineOpts(data=[opts.MarkLineItem(type_="max")]),
)
.set_global_opts(title_opts=opts.TitleOpts(title="Line-MarkLine"))
)
c.render_notebook()
来源:oschina
链接:https://my.oschina.net/u/4392911/blog/4302697