用Python pyecharts v1.x 绘制图形（二）:折线图、折线面积图、散点图、雷达图、箱线图、词云图

关于pyecharts

• pyecharts是一个用于生成echart（百度开源的数据可视化javascript库）图表的类库。
• pyecharts 分为 v0.5.x 和 v1.x 两个大版本，版本不兼容，本篇所有的案例基于pyecharts v1.6.2。
• chart.render()成的html文件，会导入echarts脚本https://assets.pyecharts.org/assets/echarts.min.js
• 案例背景假设为校OJ(online judge) V2.0 后台

折线图

# 折线图
import random
import pyecharts.options as opts
from pyecharts.charts import Line
from pyecharts.commons.utils import JsCode
 
line = (
    Line()
    .add_xaxis(['{}月第{}周周赛'.format(y,z) 
                     for y in range(1, 3)  # 1、2月  
                         for z in range(1, 5)])  # 1-4周
    .add_yaxis('A题', [random.randint(10, 20) for _ in range(8)], 
               is_smooth=True, # 平滑
               markpoint_opts=opts.MarkPointOpts(
                           # 使用coord这个属性设置自定义标记点数值，我这儿随便写
                           data=[opts.MarkPointItem(name='自定义标记点',coord=[2,18],value='标注值')]
                       )
               )
    .add_yaxis('B题', [random.randint(5, 20) for _ in range(8)])
    .add_yaxis('C题', [random.randint(5, 20) for _ in range(8)])
    .set_series_opts(label_opts=opts.LabelOpts(
                    formatter=JsCode( # 通过定义JavaScript回调函数自定义标签
                         "function(params){"
                                "return params.value[1].toString() + '%';}"  # 外层单引号内存双引号亲测不行！
                    )
                ))
    .set_global_opts(xaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(rotate=-30)), # 设置x轴标签旋转角度
                     yaxis_opts=opts.AxisOpts(name='AC率', min_=3), 
                     title_opts=opts.TitleOpts(title='折线示例_ACM题目分析'))        
    )

line.render('折线图.html')

折线面积图

# 折线面积图
import random
import pyecharts.options as opts
from pyecharts.charts import Line
from pyecharts.commons.utils import JsCode
 
line = (
    Line()
    .add_xaxis(['{}月第{}周周赛'.format(y,z) 
                     for y in range(1, 3)  # 1、2月  
                         for z in range(1, 5)])  # 1-4周
    .add_yaxis('蔡队', 
               [random.randint(10, 20) for _ in range(8)], 
               is_symbol_show=False,         
               areastyle_opts=opts.AreaStyleOpts(opacity=0.5),
               markpoint_opts=opts.MarkPointOpts(data=[opts.MarkPointItem(type_='average', name='均值'),
                                                   opts.MarkPointItem(type_='max', name='最大值'),
                                                   opts.MarkPointItem(type_='min', name='最小值')], 
                                                   symbol_size=50)           
               )
    .add_yaxis('旺神', 
               [random.randint(6, 20) for _ in range(8)], 
               is_smooth=True, 
               is_symbol_show=False,
               areastyle_opts=opts.AreaStyleOpts(opacity=0.5)
               )
    .set_global_opts(xaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(rotate=-30)), # 设置x轴标签旋转角度
                     yaxis_opts=opts.AxisOpts(name='完成积分', min_=5), 
                     title_opts=opts.TitleOpts(title='折线面积图示例_周赛分析'))        
    )

line.render('折线面积图.html')

散点图

# 散点图
from pyecharts.charts import Scatter
from pyecharts import options as opts
from pyecharts.commons.utils import JsCode
import pandas as pd

def scatter_simple() -> Scatter:
    # 数据源
    df = pd.DataFrame({'AC':[21,22,23,24,28,30,34,35,40,44,45],  # 刷题数
                       'ACB':[140,120,380,120,200,190,160,300,300,400,500],
                       '姓名':['小军','NIL','假冒NOI','小白','弱刚','晓雷','窜天','云云','依图','蔡队','旺神',]})
    # inplace=True：不创建新的对象，直接对原始对象进行修改
    # 升序
    df.sort_values('AC', inplace=True, ascending=True)  
    
    c = (
        Scatter()
        .add_xaxis(df.AC.values.tolist())
        .add_yaxis(
            '刷题_能力_姓名',
            df[['ACB','姓名']].values.tolist(),
            label_opts=opts.LabelOpts(
                formatter=JsCode(
                    'function(params){return params.value[2];}' #通过定义JavaScript回调函数自定义标签
                )
            )
        )
        .set_global_opts(
            title_opts=opts.TitleOpts(title='散点图示例--ACM集训队队员能力'),
            xaxis_opts=opts.AxisOpts(name='AC(刷题数)', type_='value', min_=20),  #x轴从20开始，原点不为0
            yaxis_opts=opts.AxisOpts(name='ACB(能力值)', min_=100),  # y轴起始点的值
            legend_opts=opts.LegendOpts(is_show=True)
        )
    )
    return c
scatter_simple().render('散点图.html')

雷达图

# 雷达图
import random
from pyecharts import options as opts
from pyecharts.charts import Page, Radar
def radar_simple() -> Radar:
    c = (
        Radar()
        .add_schema(
            # 各项的max_值可以不同
            schema=[
                opts.RadarIndicatorItem(name='计算几何学', max_=100),
                opts.RadarIndicatorItem(name='动态规划', max_=100),
                opts.RadarIndicatorItem(name='图论', max_=100),
                opts.RadarIndicatorItem(name='搜索', max_=100),
                opts.RadarIndicatorItem(name='模拟', max_=100),
                opts.RadarIndicatorItem(name='数论', max_=100),
            ]
        )
        .add('旺神', [[random.randint(10, 101) for _ in range(6)]],           
             color='red',           
             areastyle_opts = opts.AreaStyleOpts(  #设置填充的属性
                 opacity = 0.5,                  
                 color='red'                     
         ),)
        .add('蔡队', [[random.randint(10, 101) for _ in range(6)]],
             color='blue',
             areastyle_opts = opts.AreaStyleOpts(
                 opacity = 0.5,#透明度
                 color='blue'
         ),)
        .set_series_opts(label_opts=opts.LabelOpts(is_show=True))
        .set_global_opts(title_opts=opts.TitleOpts(title='雷达图示例-ACM集训队队员能力'))
    )
    return c
radar_simple().render('雷达图.html')

箱线图

# 箱线图--描述离散程度
from pyecharts import options as opts
from pyecharts.charts import Boxplot
def boxpolt_base() -> Boxplot:
    v_sophomore = [
        [1.1, 2.2, 2.6, 3.2, 3.7, 4.2, 4.7, 4.7, 5.5, 6.3, 8.0],
        [2.5, 2.5, 2.8, 3.2, 3.7, 4.2, 4.7, 4.7, 5.5, 6.3, 7.0]
    ]
    v_junior = [
        [3.6, 3.7, 4.7, 4.9, 5.1, 5.2, 5.3, 5.4, 5.7, 5.8, 5.8],
        [3.6, 3.7, 4.7, 4.9, 5.1, 5.2, 5.3, 5.4, 5.7, 5.8, 5.8]
    ]
    # 最小值，下四分位数，中位数、上四分位数、最大值
    # [min, Q1, median (or Q2), Q3, max]
    c = (
        Boxplot()
        .add_xaxis(['寒假作业','暑假作业'])
        .add_yaxis('大二队员', Boxplot.prepare_data(v_sophomore))
        .add_yaxis('大三队员', Boxplot.prepare_data(v_junior))
        .set_series_opts(label_opts=opts.LabelOpts(is_show=True))
        .set_global_opts(title_opts=opts.TitleOpts(title='ACM集训队祖传练习完成时长离散度'),
                         xaxis_opts=opts.AxisOpts(name='单位：小时'), 
                         legend_opts=opts.LegendOpts(is_show=True))
        .reversal_axis() #翻转XY轴
    )
    return c

boxpolt_base().render('箱线图.html')

词云图

# 词云图
from pyecharts import options as opts
from pyecharts.charts import WordCloud
from pyecharts.globals import SymbolType

words = [
    ('背包问题', 10000),
    ('大整数', 6181),
    ('Karatsuba乘法算法', 4386),
    ('穷举搜索', 4055),
    ('傅里叶变换', 2467),
    ('状态树遍历', 2244),
    ('剪枝', 1868),
    ('Gale-shapley', 1484),
    ('最大匹配与匈牙利算法', 1112),
    ('线索模型', 865),
    ('关键路径算法', 847),
    ('最小二乘法曲线拟合', 582),
    ('二分逼近法', 555),
    ('牛顿迭代法', 550),
    ('Bresenham算法', 462),
    ('粒子群优化', 366),
    ('Dijkstra', 360),
    ('A*算法', 282),
    ('负极大极搜索算法', 273),
    ('估值函数', 265)
]
def wordcloud_base() -> WordCloud:
    c = (
        WordCloud()
        .add("", words, word_size_range=[20, 100], shape=SymbolType.ROUND_RECT)
        .set_global_opts(title_opts=opts.TitleOpts(title='WordCloud示例-OJ搜索关键字'))
    )
    return c
wordcloud_base().render('词云图.html')

其他

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