1.基本折線圖

import? ?pyecharts.options? ?as? ? opts

from? ? pyecharts.charts? ? import? Line

x=['星期一','星期二','星期三','星期四','星期五','星期七','星期日']

y=[100,200,300,400,500,400,300]

line=(

Line()

.set_global_opts(

tooltip_opts=opts.TooltipOpts(is_show=False),

xaxis_opts=opts.AxisOpts(type_="category"),

yaxis_opts=opts.AxisOpts(

type_="value",

axistick_opts=opts.AxisTickOpts(is_show=True),

splitline_opts=opts.SplitLineOpts(is_show=True),

),

)

.add_xaxis(xaxis_data=x)

.add_yaxis(

series_name="基本折線圖",

y_axis=y,

symbol="emptyCircle",

is_symbol_show=True,

label_opts=opts.LabelOpts(is_show=False),

)

)

line.render_notebook()

series_name：圖形名稱

?y_axis：數(shù)據(jù)?

symbol：標(biāo)記的圖形，

pyecharts提供的類型包括'circle','rect','roundRect','triangle','diamond','pin','arrow','none'，也可以通過'image://url'設(shè)置為圖片，其中 URL 為圖片的鏈接。is_symbol_show：是否顯示 symbol

2.連接空數(shù)據(jù)（折線圖）

有時(shí)候我們要分析的數(shù)據(jù)存在空缺值，需要進(jìn)行處理才能畫出折線圖

import? ?pyecharts.options? ? as? ?opts

from? ? pyecharts.charts? ?import? ?Line

x=['星期一','星期二','星期三','星期四','星期五','星期七','星期日']

y=[100,200,300,400,None,400,300]

line=(

Line()

.add_xaxis(xaxis_data=x)

.add_yaxis(

series_name="連接空數(shù)據(jù)（折線圖）",

y_axis=y,

is_connect_nones=True

)

.set_global_opts(title_opts=opts.TitleOpts(title="Line-連接空數(shù)據(jù)"))

)

line.render_notebook()

3.多條折線重疊

import? ? pyecharts.options? ?as? ?opts

from? ? pyecharts.charts? ? import? ?Line

x=['星期一','星期二','星期三','星期四','星期五','星期七','星期日']

y1=[100,200,300,400,100,400,300]

y2=[200,300,200,100,200,300,400]

line=(

Line()

.add_xaxis(xaxis_data=x)

.add_yaxis(series_name="y1線",y_axis=y1,symbol="arrow",is_symbol_show=True)

.add_yaxis(series_name="y2線",y_axis=y2)

.set_global_opts(title_opts=opts.TitleOpts(title="Line-多折線重疊"))

)

line.render_notebook()

4.平滑曲線折線圖

import? ?pyecharts.options? ?as? ?opts

from? ?pyecharts.charts? ?import? ?Line

x=['星期一','星期二','星期三','星期四','星期五','星期七','星期日']

y1=[100,200,300,400,100,400,300]

y2=[200,300,200,100,200,300,400]

line=(

Line()

.add_xaxis(xaxis_data=x)

.add_yaxis(series_name="y1線",y_axis=y1,?is_smooth=True)

.add_yaxis(series_name="y2線",y_axis=y2,?is_smooth=True)

.set_global_opts(title_opts=opts.TitleOpts(title="Line-多折線重疊"))

)

line.render_notebook()

is_smooth：平滑曲線標(biāo)志

5.階梯圖

import? ?pyecharts.options? ?as? ?opts

from? ? pyecharts.charts? ?import? ?Line

x=['星期一','星期二','星期三','星期四','星期五','星期七','星期日']

y1=[100,200,300,400,100,400,300]

line=(

Line()

.add_xaxis(xaxis_data=x)

.add_yaxis(series_name="y1線",y_axis=y1,?is_step=True)

.set_global_opts(title_opts=opts.TitleOpts(title="Line-階梯圖"))

)

line.render_notebook()

is_step：階梯圖參數(shù)

6.變換折線的樣式

import? ?pyecharts.options? ?as? ?opts

from? ?pyecharts.charts? ?import? ?Line

from? ? pyecharts.faker? ?import? ?Faker

x=['星期一','星期二','星期三','星期四','星期五','星期七','星期日']

y1=[100,200,300,400,100,400,300]

line?=?(

Line()

.add_xaxis(xaxis_data=x)

.add_yaxis(

"y1",

y1,

symbol="triangle",

symbol_size=30,

linestyle_opts=opts.LineStyleOpts(color="red",?width=4,?type_="dashed"),

itemstyle_opts=opts.ItemStyleOpts(

border_width=3,?border_color="yellow",?color="blue"

),

)

.set_global_opts(title_opts=opts.TitleOpts(title="Line-ItemStyle"))

)

line.render_notebook()

linestyle_opts:折線樣式配置color設(shè)置顏色，width設(shè)置寬度type設(shè)置類型，有'solid','dashed','dotted'三種類型 itemstyle_opts：圖元樣式配置，border_width設(shè)置描邊寬度，border_color設(shè)置描邊顏色，color設(shè)置紋理填充顏色

7.折線面積圖

import? ?pyecharts.options? as? ?opts

from? ?pyecharts.charts? ?import? ?Line

x=['星期一','星期二','星期三','星期四','星期五','星期七','星期日']

y1=[100,200,300,400,100,400,300]

y2=[200,300,200,100,200,300,400]

line=(

Line()

.add_xaxis(xaxis_data=x)

.add_yaxis(series_name="y1線",y_axis=y1,areastyle_opts=opts.AreaStyleOpts(opacity=0.5))

.add_yaxis(series_name="y2線",y_axis=y2,areastyle_opts=opts.AreaStyleOpts(opacity=0.5))

.set_global_opts(title_opts=opts.TitleOpts(title="Line-多折線重疊"))

)

line.render_notebook()

8.雙橫坐標(biāo)折線圖

import? ? pyecharts.options? ?as? ?opts

from? ? pyecharts.charts? ?import? ?Line

from? ? pyecharts.commons.utils? ?import? ?JsCode

js_formatter?="""function?(params)?{

console.log(params);

return '降水量??'?+ params.value +?(params.seriesData.length ? '：'?+ params.seriesData[0].data :?'');

}"""

line=(

Line()

.add_xaxis(

xaxis_data=[

"2016-1",

"2016-2",

"2016-3",

"2016-4",

"2016-5",

"2016-6",

"2016-7",

"2016-8",

"2016-9",

"2016-10",

"2016-11",

"2016-12",

]

)

.extend_axis(

xaxis_data=[

"2015-1",

"2015-2",

"2015-3",

"2015-4",

"2015-5",

"2015-6",

"2015-7",

"2015-8",

"2015-9",

"2015-10",

"2015-11",

"2015-12",

],

xaxis=opts.AxisOpts(

type_="category",

axistick_opts=opts.AxisTickOpts(is_align_with_label=True),

axisline_opts=opts.AxisLineOpts(

is_on_zero=False,?linestyle_opts=opts.LineStyleOpts(color="#6e9ef1")

),

axispointer_opts=opts.AxisPointerOpts(

is_show=True,?label=opts.LabelOpts(formatter=JsCode(js_formatter))

),

),

)

.add_yaxis(

series_name="2015?降水量",

is_smooth=True,

symbol="emptyCircle",

is_symbol_show=False,

color="#d14a61",

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),

linestyle_opts=opts.LineStyleOpts(width=2),

)

.add_yaxis(

series_name="2016?降水量",

is_smooth=True,

symbol="emptyCircle",

is_symbol_show=False,

color="#6e9ef1",

y_axis=[3.9,5.9,11.1,18.7,48.3,69.2,231.6,46.6,55.4,18.4,10.3,0.7],

label_opts=opts.LabelOpts(is_show=False),

linestyle_opts=opts.LineStyleOpts(width=2),

)

.set_global_opts(

legend_opts=opts.LegendOpts(),

tooltip_opts=opts.TooltipOpts(trigger="none",?axis_pointer_type="cross"),

xaxis_opts=opts.AxisOpts(

type_="category",

axistick_opts=opts.AxisTickOpts(is_align_with_label=True),

axisline_opts=opts.AxisLineOpts(

is_on_zero=False,?linestyle_opts=opts.LineStyleOpts(color="#d14a61")

),

axispointer_opts=opts.AxisPointerOpts(

is_show=True,?label=opts.LabelOpts(formatter=JsCode(js_formatter))

),

),

yaxis_opts=opts.AxisOpts(

type_="value",

splitline_opts=opts.SplitLineOpts(

is_show=True,?linestyle_opts=opts.LineStyleOpts(opacity=1)

),

),

)

)

line.render_notebook()

9.用電量隨時(shí)間變化

import? ?pyecharts.options? ?as? ?opts

from? ?pyecharts.charts? ?import? ?Line

x_data?=?["00:00","01:15","02:30","03:45","05:00","06:15","07:30","08:45","10:00","11:15","12:30","13:45","15:00","16:15","17:30","18:45","20:00","21:15","22:30","23:45",]

y_data?=?[300,280,250,260,270,300,550,500,400,390,380,390,400,500,600,750,800,700,600,400,]

line=(

Line()

.add_xaxis(xaxis_data=x_data)

.add_yaxis(

series_name="用電量",

y_axis=y_data,

is_smooth=True,

label_opts=opts.LabelOpts(is_show=False),

linestyle_opts=opts.LineStyleOpts(width=2),

)

.set_global_opts(

title_opts=opts.TitleOpts(title="一天用電量分布",?subtitle="純屬虛構(gòu)"),

tooltip_opts=opts.TooltipOpts(trigger="axis",?axis_pointer_type="cross"),

xaxis_opts=opts.AxisOpts(boundary_gap=False),

yaxis_opts=opts.AxisOpts(

axislabel_opts=opts.LabelOpts(formatter="{value}?W"),

splitline_opts=opts.SplitLineOpts(is_show=True),

),

visualmap_opts=opts.VisualMapOpts(

is_piecewise=True,

dimension=0,

pieces=[

{"lte":6,"color":"green"},

{"gt":6,"lte":8,"color":"red"},

{"gt":8,"lte":14,"color":"yellow"},

{"gt":14,"lte":17,"color":"red"},

{"gt":17,"color":"green"},

],

pos_right=0,

pos_bottom=100

),

)

.set_series_opts(

markarea_opts=opts.MarkAreaOpts(

data=[

opts.MarkAreaItem(name="早高峰",?x=("07:30","10:00")),

opts.MarkAreaItem(name="晚高峰",?x=("17:30","21:15")),

]

)

)

)

line.render_notebook()

這里給大家介紹幾個(gè)關(guān)鍵參數(shù)：

①visualmap_opts：視覺映射配置項(xiàng)，可以將折線分段并設(shè)置標(biāo)簽（is_piecewise），將不同段設(shè)置顏色（pieces）；

②markarea_opts：標(biāo)記區(qū)域配置項(xiàng)，data參數(shù)可以設(shè)置標(biāo)記區(qū)域名稱和位置。