震惊！python中pyecharts模块的竟然还能这样用

安装模块 pyecharts
如果需要安装 0.5.11 版本的开发者，可以使用
pip install pyecharts==0.5.11

1. 柱状图

普通柱状图：

from pyecharts import Bar
bar = Bar("我的第一个图表", "这里是副标题")
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)

效果：

堆叠数据的柱状图：

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("柱状图数据堆叠示例")
bar.add("商家A", attr, v1, is_stack=True,is_more_utils=True)
bar.add("商家B", attr, v2, is_stack=True,is_more_utils=True)

效果：

标记线和标记点：

bar = Bar("标记线和标记点示例")
bar.add("商家A", attr, v1, mark_point=["average"])
bar.add("商家B", attr, v2, mark_line=["min", "max"])

效果：

可控制显示时间段的柱状图：

import random
attr = ["{}天".format(i) for i in range(30)]
v1 = [random.randint(1, 30) for _ in range(30)]
bar = Bar("Bar - datazoom - slider 示例")
bar.add("", attr, v1, is_label_show=True, is_datazoom_show=True)

效果：

3D柱状图：

from pyecharts import Bar3D
bar3d = Bar3D("3D 柱状图示例", width=1200, height=600)
x_axis = [
    "12a", "1a", "2a", "3a", "4a", "5a", "6a", "7a", "8a", "9a", "10a", "11a",
    "12p", "1p", "2p", "3p", "4p", "5p", "6p", "7p", "8p", "9p", "10p", "11p"
    ]
y_axis = [
    "Saturday", "Friday", "Thursday", "Wednesday", "Tuesday", "Monday", "Sunday"
    ]
data = [
    [0, 0, 5], [0, 1, 1], [0, 2, 0], [0, 3, 0], [0, 4, 0], [0, 5, 0],
    [0, 6, 0], [0, 7, 0], [0, 8, 0], [0, 9, 0], [0, 10, 0], [0, 11, 2],
    [0, 12, 4], [0, 13, 1], [0, 14, 1], [0, 15, 3], [0, 16, 4], [0, 17, 6],
    [0, 18, 4], [0, 19, 4], [0, 20, 3], [0, 21, 3], [0, 22, 2], [0, 23, 5],
    [1, 0, 7], [1, 1, 0], [1, 2, 0], [1, 3, 0], [1, 4, 0], [1, 5, 0],
    [1, 6, 0], [1, 7, 0], [1, 8, 0], [1, 9, 0], [1, 10, 5], [1, 11, 2],
    [1, 12, 2], [1, 13, 6], [1, 14, 9], [1, 15, 11], [1, 16, 6], [1, 17, 7],
    [1, 18, 8], [1, 19, 12], [1, 20, 5], [1, 21, 5], [1, 22, 7], [1, 23, 2],
    [2, 0, 1], [2, 1, 1], [2, 2, 0], [2, 3, 0], [2, 4, 0], [2, 5, 0],
    [2, 6, 0], [2, 7, 0], [2, 8, 0], [2, 9, 0], [2, 10, 3], [2, 11, 2],
    [2, 12, 1], [2, 13, 9], [2, 14, 8], [2, 15, 10], [2, 16, 6], [2, 17, 5],
    [2, 18, 5], [2, 19, 5], [2, 20, 7], [2, 21, 4], [2, 22, 2], [2, 23, 4],
    [3, 0, 7], [3, 1, 3], [3, 2, 0], [3, 3, 0], [3, 4, 0], [3, 5, 0],
    [3, 6, 0], [3, 7, 0], [3, 8, 1], [3, 9, 0], [3, 10, 5], [3, 11, 4],
    [3, 12, 7], [3, 13, 14], [3, 14, 13], [3, 15, 12], [3, 16, 9], [3, 17, 5],
    [3, 18, 5], [3, 19, 10], [3, 20, 6], [3, 21, 4], [3, 22, 4], [3, 23, 1],
    [4, 0, 1], [4, 1, 3], [4, 2, 0], [4, 3, 0], [4, 4, 0], [4, 5, 1],
    [4, 6, 0], [4, 7, 0], [4, 8, 0], [4, 9, 2], [4, 10, 4], [4, 11, 4],
    [4, 12, 2], [4, 13, 4], [4, 14, 4], [4, 15, 14], [4, 16, 12], [4, 17, 1],
    [4, 18, 8], [4, 19, 5], [4, 20, 3], [4, 21, 7], [4, 22, 3], [4, 23, 0],
    [5, 0, 2], [5, 1, 1], [5, 2, 0], [5, 3, 3], [5, 4, 0], [5, 5, 0],
    [5, 6, 0], [5, 7, 0], [5, 8, 2], [5, 9, 0], [5, 10, 4], [5, 11, 1],
    [5, 12, 5], [5, 13, 10], [5, 14, 5], [5, 15, 7], [5, 16, 11], [5, 17, 6],
    [5, 18, 0], [5, 19, 5], [5, 20, 3], [5, 21, 4], [5, 22, 2], [5, 23, 0],
    [6, 0, 1], [6, 1, 0], [6, 2, 0], [6, 3, 0], [6, 4, 0], [6, 5, 0],
    [6, 6, 0], [6, 7, 0], [6, 8, 0], [6, 9, 0], [6, 10, 1], [6, 11, 0],
    [6, 12, 2], [6, 13, 1], [6, 14, 3], [6, 15, 4], [6, 16, 0], [6, 17, 0],
    [6, 18, 0], [6, 19, 0], [6, 20, 1], [6, 21, 2], [6, 22, 2], [6, 23, 6]
    ]
range_color = ['#313695', '#4575b4', '#74add1', '#abd9e9', '#e0f3f8', '#ffffbf',
               '#fee090', '#fdae61', '#f46d43', '#d73027', '#a50026']
bar3d.add(
    "",
    x_axis,
    y_axis,
    [[d[1], d[0], d[2]] for d in data],
    is_visualmap=True,
    visual_range=[0, 20],
    visual_range_color=range_color,
    grid3d_width=200,
    grid3d_depth=80,
)

效果：

2. 折线图

普通折线图：

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, 10, 100]
v2 = [55, 60, 16, 20, 15, 80]
line = Line("折线图示例")
line.add("商家A", attr, v1, mark_point=["average"])
line.add("商家B", attr, v2, is_smooth=True, mark_line=["max", "average"])

效果：

折线图属性展示：

line = Line("折线图示例")
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,
)

效果：

折线图-阶梯图：

line = Line("折线图-阶梯图示例")
line.add("商家A", attr, v1, is_step=True, is_label_show=True)

效果：

折线图-面积图：

line = Line("折线图-面积图示例")
line.add(
    "商家A",
    attr,
    v1,
    line_opacity=0.2,
    area_opacity=0.4,
    symbol=None,
)
line.add(
    "商家B",
    attr,
    v2,
    is_fill=True,
    area_color="#000",
    area_opacity=0.3,
    is_smooth=True,
)

效果：

3. 饼状图

正常饼状图：

from pyecharts import Pie

attr = ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]
v1 = [11, 12, 13, 10, 10, 10]
pie = Pie("饼图示例")
pie.add("", attr, v1, is_label_show=True)

效果：

饼图-圆环图：

attr = ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]
v1 = [11, 12, 13, 10, 10, 10]
pie = Pie("饼图-圆环图示例", title_pos='center')
pie.add(
    "",
    attr,
    v1,
    radius=[40, 75],
    label_text_color=None,
    is_label_show=True,
    legend_orient="vertical",
    legend_pos="left",
)

效果：

4. 散点图

散点图：

from pyecharts import Scatter

v1 = [10, 20, 30, 40, 50, 60]
v2 = [10, 20, 30, 40, 50, 60]
scatter = Scatter("散点图示例")
scatter.add("A", v1, v2)
scatter.add("B", v1[::-1], v2)

效果：

5. 词云

词云：

from pyecharts import WordCloud
import pandas as pd
df=pd.read_csv('word.csv',names=['name','number'])
data=df.groupby('name').sum()
wordcloud=WordCloud('黄色',title_top=50,title_pos=50,title_color='purple',width=1200,height=800,background_color='yellow')
wordcloud.add('',data.index,data.values,word_size_range=[20,100])

效果：

6. 地图

地图：

from 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',is_label_show=True)

效果：

地图模块需要下载 一些详细地图信息的模块，详情请查阅官方文档：
https://05x-docs.pyecharts.org/#/