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python的pyecharts绘制各种图表详细(附代码)

人气:0

环境:pyecharts库,echarts-countries-pypkg,echarts-china-provinces-pypkg,echarts-china-cities-pypkg

数据:2018年4月16号的全国各地最高最低和天气类型的数据——2018-4-16.json(爬虫爬的)

代码:天气数据爬虫代码,图表绘制代码 代码地址:https://github.com/goodloving/pyecharts.git(py文件)

一、公共属性

1、标题栏的属性:一般在实例化(初始化)类型时给与,如bar = Bar(“大标题”,“副标题”,···各种属性···)

title_color = “颜色”:标题颜色,可以是‘red'或者‘#0000'

title_pos = ‘位置':标题位置,如‘center',‘left'···

width = 1200:图表的宽

height = 800:图表的高

background_color = "颜色":图表的背景色

·····

2、标签栏的属性:如bar.add(“标签”,x,values,···属性···)

'mark_'类,通个'mark_'显示,如 mark_point['max', 'min', 'average']:标出最大最小和平均值的点,

mark_point_textcolor,mark_line_symbolsize·····

'legend_'类,如legend_pos=‘left':标签的位置

'is_'类,如is_label_show=True:显示每个点的值,is_datazoom_show=True:实现移动控制x轴的数量

is_convert = True:x,y轴是否调换

eg:

bar = pyecharts.Bar("全国各地最高气温", "2018-4-18", title_color='red', title_pos='right', width=1400, height=700, background_color='#404a59')
bar.add("最高气温", cities, highs, mark_point=['max', 'min', 'average'], is_label_show=True, is_datazoom_show=True, legend_pos='left')
bar.render('Bar-High.html')

3、Geo,Map无法显示底图

pyecharts v0.3.2以后,pyecharts 将不再自带地图 js 文件。如用户需要用到地图图表,可自行安装对应的地图文件包。

地图文件被分成了三个 Python 包,分别为:
全球国家地图: echarts-countries-pypkg (1.9MB)
中国省级地图: echarts-china-provinces-pypkg (730KB)

中国市级地图: echarts-china-cities-pypkg (3.8MB)

(1)pycharm直接在设置里面搜索安装这三个库

(2)pip安装

pip install echarts-countries-pypkg

pip install echarts-china-provinces-pypkg

pip install echarts-china-cities-pypkg

二、各种图表

1.柱状图/条形图——Bar

bar = pyecharts.Bar("全国各地最高最低气温", "2018-4-18", title_pos='right', title_color='blue', width=1400, height=700,background_color='white')
bar.add("最高气温", cities, highs, mark_point=['max'], legend_text_color='red', is_datazoom_show=True)
bar.add("最低气温", cities, lows, mark_line=['min'], legend_text_color='blue' )


bar.render('Bar-High-Low.html')


2、散点图——EffectScatter

es = pyecharts.EffectScatter("最低气温动态散点图", "2018-4-16", title_pos='right', title_color='blue', width=1400, height=700, background_color='white')
es.add("最低温度", range(0, len(cities)), lows, legend_pos='center', legend_text_color='blue',symbol_size=10, effect_period=3, effect_scale=3.5, symbol='pin',is_datazoom_show=True,is_label_show=True)


es.render("EffectScatter-low.html")


3、漏斗与——Funnel

fl = pyecharts.Funnel("最高气温漏斗图", "2018-40-16", title_pos='left', width=1400, height=700)
fl.add("最低气温", cities[:15], lows[:15], is_label_show=True, label_pos='inside', label_text_color='white')


fl.render("Funnel-low.html")


4、仪表盘——Guage

gu = pyecharts.Gauge("仪表盘图")
gu.add("指标", "达标", 80)


gu.render("Guage-eg.html")


5、地理坐标图——Geo

geo = pyecharts.Geo("最高气温地理坐标系图", '2018-4-16', title_color='#fff', title_pos='center', width=1200, height=600, background_color='#404a95')
geo.add("最高气温", cities, highs, is_visualmap=True, visual_range=[0, 40], visual_text_color='#fff', symbol_size=5, legend_pos='right',is_geo_effect_show=True)


geo.render("Geo-Low.html")


6、关系图——Graph(略)

7、折线/面积图——Line

line = pyecharts.Line("气温变化折线图", '2018-4-16', width=1200, height=600)
line.add("最高气温", cities, highs, mark_point=['average'], is_datazoom_show=True)
line.add("最低气温", cities, lows, mark_line=['average'], is_smooth=True)


line.render('Line-High-Low.html')


line = pyecharts.Line("气温变化折线图", '2018-4-16', width=1200, height=600)
line.add("最高气温", cities, highs, mark_point=['average'], is_datazoom_show=True, is_fill=True, line_opacity=0.2, area_opacity=0.4)
line.add("最低气温", cities, lows, mark_line=['average'], is_smooth=True, is_fill=True, area_color="#000", area_opacity=0.5)


line.render('Area-High-Low.html')


8、水滴球——Liquid

lq = pyecharts.Liquid("水滴球")
lq.add("Liquid", [0.8, 0.5, 0.2], is_liquid_outline_show=False, is_liquid_animation=True)


lq.render("LiQuid.html")


9、地图——Map

a_city = []
for i in cities:
a_city.append(i + '市')
map = pyecharts.Map("湖北最低气温", width=1200, height=600)
map.add("最低气温", a_city, lows, maptype='湖北', is_visualmap=True, visual_text_color='#000', visual_range= [-15, 20])


map.render("Map-low.html")


value = [95.1, 23.2, 43.3, 66.4, 88.5]

attr= ["China", "Canada", "Brazil", "Russia", "United States"]

map = Map("世界地图示例", width=1200, height=600)

map.add("", attr, value, maptype="world", is_visualmap=True, visual_text_color='#000')

map.render('Map-World.html')


10、平行坐标图——Parallel

parallel = pyecharts.Parallel("高低温度的平行坐标系图", '2018-4-16', width=1200, height=600)
parallel.config(cities[:20])
parallel.add("高低温", [highs[:20], lows[:20]], is_random=True)


parallel.render('Parallel-High-Low.html')


11、饼图——Pie

sun = 0
cloud = 0
lit_rain = 0
mit_rain = 0
sail = 0
shadom = 0
z_rain = 0
th_rain = 0
for i in types:
if i == '晴':
sun += 1
elif i == '多云':
cloud += 1
elif i == '小雨':
lit_rain += 1
elif i == '中雨':
mit_rain += 1
elif i == '阴':
shadom += 1
elif i == '阵雨':
z_rain += 1
elif i == '雷阵雨':
th_rain += 1
elif i == '扬沙':
sail += 1
pie = pyecharts.Pie("全国天气类型比例", '2018-4-16')
pie.add('天气类型', weather, [mit_rain, lit_rain, sail, sun, th_rain, cloud, shadom, z_rain], is_label_show=True)


pie.render('Pie-weather.html')


修改:

pie = pyecharts.Pie("全国天气类型比例", '2018-4-16', title_pos='center')
pie.add('天气类型', weather, [mit_rain, lit_rain, sail, sun, th_rain, cloud, shadom, z_rain], is_label_show=True, legend_pos='left', label_text_color=None, legend_orient='vertical', radius=[30, 75])


pie.render('Pie-weather.html')

pie镶嵌:

center -> list

饼图的中心(圆心)坐标,数组的第一项是横坐标,第二项是纵坐标,默认为 [50, 50]默认设置成百分比,设置成百分比时第一项是相对于容器宽度,第二项是相对于容器高度

rosetype -> str

是否展示成南丁格尔图,通过半径区分数据大小,有'radius'和'area'两种模式。默认为'radius'radius:扇区圆心角展现数据的百分比,半径展现数据的大小area:所有扇区圆心角相同,仅通过半径展现数据大小

pie = pyecharts.Pie("全国天气类型比例", '2018-4-16')
pie.add('', weather, [mit_rain, lit_rain, sail, sun, th_rain, cloud, shadom, z_rain], is_label_show=True, label_text_color=None, legend_orient='vertical', radius=[40, 50], center=[50, 50])
pie.add('', ['中雨', '小雨', '扬沙', '晴'], [lit_rain, mit_rain, sun, sail], radius=[10, 35], center=[50, 50], rosetype='area')


pie.render('Pie-weather.html')


至此,pyecharts的大多数图标的绘制我们都可以实现了,更多知识可以查看下面链接

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