Python + PyEcharts——数据可视化

一、第一个PyEcharts图标

1 安装                             pip install pyecharts
2 引用pyecharts from pyecharts import Bar
3 编写实现柱状图

bar = Bar('我的第一个图标','副标题')
bar.add('服装',['衬衫','羊毛衫','雪纺衫','裤子','高跟鞋','袜子'],[5,20,36,10,75,90])

4 输出到.html中进行展示:bar.render(.././html/bar01.html)
5 新建一个html文件

代码:
 #encoding:utf-8
from pyecharts import Bar
bar = Bar('我的第一个图标','副标题')
bar.add('服装',['衬衫','羊毛衫','雪纺衫','裤子','高跟鞋','袜子'],[5,20,36,10,75,90])
bar.render('html/first01.html')

二、柱形图/条形图

Bar.add()方法签名
add(
    name,x_axis,y_axis,
    is_stack = False,
    bar_category_gap = '20%',**kwargs
    )
name -> str         #图例名称
x_axis -> list      # X轴数据
y_axis -> list      # Y轴数据
is_stack -> bool    #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
bar_category_gap -> int/str   #类目轴柱状距离,默认20%
代码: 
 #encoding:utf-8
from pyecharts import Bar
bar = Bar('基本柱状图','副标题')
bar.add(
            '服装',
            ['衬衫','羊毛衫','雪纺衫','裤子','高跟鞋','袜子'],
            [5,20,36,10,75,90],
            is_more_utils = True    #设置最右侧工具栏
        )
bar.show_config()       #调试输出pyecharts的js配置信息
bar.render('./html/first01.html')

三、堆叠(柱状)图

代码:
from pyecharts import Bar

attr = ['衬衫','羊毛衫','雪纺衫','裤子','高跟鞋','袜子']
v1 = [5,20,36,10,75,90]
v2 = [10,25,8,60,20,80]
bar = Bar('柱状信息堆叠图')
bar.add('商家A',attr,v1,is_stack = True)  #is_stack = True才表示堆叠在一起
bar.add('商家B',attr,v2,is_stack = True)
bar.render('./html/first03.html')   


■ 并列(柱形)图
from pyecharts import Bar

attr = ['衬衫','羊毛衫','雪纺衫','裤子','高跟鞋','袜子']
v1 = [5,20,36,10,75,90]
v2 = [10,25,8,60,20,80]
bar = Bar('标记线和标记示例')
bar.add('商家A',attr,v1,mark_point = ['average']) #标记点:商家A的平均值
bar.add('商家B',attr,v2,mark_line = ['min','max'])    #标记线:商家B最小/最大值
bar.render('./html/first04.html')

■ 横向并列(柱形)图 
from pyecharts import Bar

attr = ['衬衫','羊毛衫','雪纺衫','裤子','高跟鞋','袜子']
v1 = [5,20,36,10,75,90]
v2 = [10,25,8,60,20,80]
bar = Bar('X 轴与 Y 轴交换')
bar.add('商家A',attr,v1)  
bar.add('商家B',attr,v2,is_convert = True)    # is_convert = True:X 轴与 Y 轴交换
bar.render('./html/first04.html')   

四、折线/面积图

Line.add()方法签名

add(
    name,x_axis,y_axis,
    is_symbol_show = True,
    is_smooth = False,
    is_stack = False,
    is_step = False,
    is_fill = False,**kwargs    
    )
以下为属性默认值:
    is_symbol_show = True,      #是否显示标记图形
    is_smooth = False,          #是否显示平滑曲线
    is_stack = False,           #是否数据堆叠
    is_step = False,            #是否是阶梯线
    is_fill = False,**kwargs    #是否填充曲线区域面积
▶代码1from pyecharts import Line

attr = ['衬衫','羊毛衫','雪纺衫','裤子','高跟鞋','袜子']
v1 = [5,20,36,10,75,90]
v2 = [10,25,8,60,20,80]
line = Line('折线示例图')
line.add('商家A',attr,v1,mark_point = ['average'])    
line.add('商家B',attr,v2,is_smooth = True, mark_line = ['max','average'])
line.render('./html/first05.html')

▶代码2:(定制折线图)    
from pyecharts import Line

attr = ['衬衫','羊毛衫','雪纺衫','裤子','高跟鞋','袜子']
v1 = [5,20,36,10,75,90]
v2 = [10,25,8,60,20,80]
line = Line('折线示例图')
line.add('商家A',attr,v1,mark_point = ['average','max','min'],
    mark_point_symbol = 'diamond',
    mark_point_textcolor = '#40ff27')   
line.add('商家B',attr,v2,mark_point = ['average','max','min'],
    mark_point_symbol = 'arrow',
    mark_point_symbolsize = 40)
line.render('./html/line01.html')

▶代码3:(面积图)  
from pyecharts import Line

attr = ['衬衫','羊毛衫','雪纺衫','裤子','高跟鞋','袜子']
v1 = [5,20,36,10,75,90]
v2 = [10,25,8,60,20,80]
line = Line('折线面积示例图')
line.add('商家A',attr,v1,is_fill = True,
    line_opacity = 0.2,
    area_opacity = 0.4,
    symbol = None)  
line.add('商家B',attr,v2,is_fill = True,
    line_color = '#000',
    area_opacity = 0.3,
    is_smooth = True)
line.render('./html/area01.html')   

五、饼图

Pie.add()方法签名
add(name,attr,value,radius = None,center = None,rosetype = None,**kwargs)
attr:属性名称
radius:饼图半径,数组第一项是内径,第二项是外径,默认[0,75,],设置成百分比
center:圆心,数组第一项是X轴,第二项是Y轴,默认[50,50]
rosetype: 是否展示成南丁格尔图,用过半径区分数据大小,radius和area两种模式,默认radius
▶代码1:(饼图)
from pyecharts import Pie

attr = ['衬衫','羊毛衫','雪纺衫','裤子','高跟鞋','袜子']
v1 = [5,20,36,10,75,90]
pie = Pie('饼图示例')
pie.add('',attr,v1,is_label_show = True)
pie.render('./html/pie01.html') 

▶代码2:(环形图)
from pyecharts import Pie

attr = ['衬衫','羊毛衫','雪纺衫','裤子','高跟鞋','袜子']
v1 = [5,20,36,10,75,90]
pie = Pie('饼图-环形图示例',title_pos = 'center')
pie.add(
            '',attr,v1,
            radius = [40,75],
            is_label_show = True,
            label_text_color = None,
            legend_orient = 'vertical', #图例垂直
            legend_pos = 'left'
        )
pie.render('./html/pie02.html') 

六、散点图

Scatter.add()方法签名
add(name,x_axis,y_axis,extra_data = None,symbol_size = 10,**kwargs)
extra_data -> int:第三维数据(可在 visualmap 中将视图元素映射到第三维度)
symbol_size -> int: 标记图形大小,默认为10
▶代码1from pyecharts import Scatter
v1 = [5,20,35,50,65,80]
v2 = [10,20,30,40,50,60]
scatter = Scatter('散点示例图')
scatter.add('A',v1,v2)
scatter.add('B',v1[::-1],v2)    #v1[::-1]代表切片倒序
scatter.render('./html/scatter01.html')     

▶代码2:(引入第三维/类似气泡图)
from pyecharts import Scatter
v1 = [5,20,35,50,65,80]
v2 = [10,20,30,40,50,60]
scatter = Scatter('散点-气泡示例图')
scatter.add('A',v1,v2)
scatter.add('B',v1[::-1],v2,is_visualmap = True,vasual_type = 'size',vasual_range_size = [20,80])   #v1[::-1]代表切片倒序
scatter.render('./html/scatter02.html')         

七 地图

Map.add() 方法签名
add(
    name,attr,value,
    maptype = 'china',
    is_roam = True,
    is_map_symobol_show = True 
    **kwargs
    )
maptype -> str: 地图类型,支持China,world,北京,天津,上海,湖南,湖北,……363个二线城市
is_roam -> bool/str 是否开启鼠标缩放,漫游等,默认 True,
                    若只想开启缩放/平移 设置scale/move 设置成 True 开启
is
is_map_symobol_show 是否显示地图标记,默认 True。
▶代码1from pyecharts import Map
value = [155,10,66,78]
attr = ['福建','山东','北京','上海']
map = Map('全国地图示例',width = 1200,height = 600)
map.add('',attr,value,maptype = 'china')
map.render('./html/map01.html')

▶代码2from pyecharts import Map
value = [155,10,66,78]
attr = ['汕头市','汕尾市','揭阳市','肇庆市']
map = Map('广东地图示例',width = 1200,height = 600)
map.add('',attr,value,maptype = 'guangong',
        is_visualmap = True,
        visual_text_color = '#000',
        is_label_show = True
        )
map.render('./html/map02.html') 

八、词云图

WordCloud.add() 方法签名
add(
        name,attr,value,
        shape = 'circle',
        word_gap = 20,
        word_size_range = None
        rotate_step = 45
    )
shape-> list :词云图轮廓(circle,cardioid,diamond,triangle-forward,triangle,pentagon,star)
word_gap -> int 单词间隔 默认 20
word_size_range -> int 单词字体大小范围 默认[12,60]
rotate_step -> int 单词旋转角度,默认45。
from pyecharts import WordCloud
name = [
            'Though','the answer','this question',
            'may at first','seem to border','on the',
            'absurd','reflection','will show','that there',
            'is a','good deal','more in','it than meets','the eye'
        ]
value = [10000,6189,4556,2356,2233,1895,1456,1255,981,875,542,462,361,265,125]
worldcloud = WordCloud(width = 1300,height = 620)
worldcloud.add('',name,value,word_size_range = [20,100])
worldcloud.render('./html/worldcloud01.html')

九、图标叠加 Overlap

自定义结合Line/ Bar/ Kline/ Scatter/ EffectScatter 等图表。
利用第一张图表为基础,将后面的数据画在第一张图上。

Overlap.add() 方法签名
add(chart,
    xaxis_index = 0,
    yaxis_index = 0,
    is_add_xaxis = False,
    is_add_yaxis = False)
属性:
is_add_xaxis / is_add_yaxis 是否新增坐标X/Y 默认 False 
▶代码1:bar + line 叠加

from pyecharts import Bar,line,Overlap
attr = ['A','B','C','D','E','F']
v1 = [10,20,30,40,50,60]
v2 = [38,28,35,58,65,70]
bar = Bar('Line - Bar示例')
bar.add('bar',attr,v1)
line = Line()
line.add('line',attr,v2)

overlop = Overlap()
overlop.add(bar)
overlop.add(line)
overlop.render('./html/line-bar01.html')

▶代码2:EffectScatter + Line 叠加

from pyecharts import line,EffectScatter,Overlap
attr = ['衬衫','羊毛衫','雪纺衫','裤子','高跟鞋','袜子']
v1 = [5,20,36,10,10,90]
line = Line('饼图示例')
line.add('',attr,v1,is_random = True)

es = EffectScatter()
es.add('',attr,v1,effect_scale=8)   #闪烁
overlop = Overlap()
overlop.add(es)
overlop.add(line)
overlop.render('./html/line-es01.html')

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转载自blog.csdn.net/wsp_1138886114/article/details/80509375