pyecharts图

Author: jackzhenguo

README.md

@@ -3301,7 +3301,7 @@ def setup_axes():
 main()
 ```
 
-#### 11 绘制仪表盘
+#### 11 pyecharts绘制仪表盘
 
 使用pip install pyecharts 安装，版本为 v1.6，pyecharts绘制仪表盘，只需要几行代码：
 
@@ -3321,6 +3321,257 @@ print('ok')
 ![image-20191228194635902](./img/image-20191228194635902.png)
 
 
+
+#### 12 pyecharts漏斗图
+
+```python
+from pyecharts import options as opts
+from pyecharts.charts import Funnel, Page
+from random import randint
+
+def funnel_base() -> Funnel:
+  c = (
+    Funnel()
+    .add("豪车", [list(z) for z in zip(['宝马', '法拉利', '奔驰', '奥迪', '大众', '丰田', '特斯拉'],
+                 [randint(1, 20) for _ in range(7)])])
+    .set_global_opts(title_opts=opts.TitleOpts(title="豪车漏斗图"))
+  )
+  return c
+funnel_base().render('./img/car_fnnel.html')
+```
+
+以7种车型及某个属性值绘制的漏斗图，属性值大越靠近漏斗的大端。
+
+![](https://i.loli.net/2019/12/28/aCGfBp6YIvWqU84.png)
+
+
+
+#### 13 pyecharts日历图
+
+```python
+import datetime
+import random
+from pyecharts import options as opts
+from pyecharts.charts import Calendar
+
+def calendar_interval_1() -> Calendar:
+    begin = datetime.date(2019, 1, 1)
+    end = datetime.date(2019, 12, 27)
+    data = [
+        [str(begin + datetime.timedelta(days=i)), random.randint(1000, 25000)]
+        for i in range(0, (end - begin).days + 1, 2)  # 隔天统计
+    ]
+    calendar = (
+      Calendar(init_opts=opts.InitOpts(width="1200px")).add(
+            "", data, calendar_opts=opts.CalendarOpts(range_="2019"))
+        .set_global_opts(
+            title_opts=opts.TitleOpts(title="Calendar-2019年步数统计"),
+            visualmap_opts=opts.VisualMapOpts(
+                max_=25000,
+                min_=1000,
+                orient="horizontal",
+                is_piecewise=True,
+                pos_top="230px",
+                pos_left="100px",
+            ),
+        )
+    )
+    return calendar
+
+calendar_interval_1().render('./img/calendar.html')
+```
+
+绘制2019年1月1日到12月27日的步行数，官方给出的图形宽度`900px`不够，只能显示到9月份，本例使用`opts.InitOpts(width="1200px")`做出微调，并且`visualmap`显示所有步数，每隔一天显示一次：
+
+![](https://i.loli.net/2019/12/28/Zw9mWM1QtUVjCgn.png)
+
+#### 14 pyecharts绘制graph图
+
+```python
+import json
+import os
+from pyecharts import options as opts
+from pyecharts.charts import Graph, Page
+
+def graph_base() -> Graph:
+    nodes = [
+        {"name": "cus1", "symbolSize": 10},
+        {"name": "cus2", "symbolSize": 30},
+        {"name": "cus3", "symbolSize": 20}
+    ]
+    links = []
+    for i in nodes:
+        if i.get('name') == 'cus1':
+            continue
+        for j in nodes:
+            if j.get('name') == 'cus1':
+                continue
+            links.append({"source": i.get("name"), "target": j.get("name")})
+    c = (
+        Graph()
+        .add("", nodes, links, repulsion=8000)
+        .set_global_opts(title_opts=opts.TitleOpts(title="customer-influence"))
+    )
+    return c
+```
+
+构建图，其中客户点1与其他两个客户都没有关系(`link`)，也就是不存在有效边：
+
+![](https://i.loli.net/2019/12/28/ts4WrTQINSaHdM1.png)
+
+#### 15 pyecharts水球图
+
+```python
+from pyecharts import options as opts
+from pyecharts.charts import Liquid, Page
+from pyecharts.globals import SymbolType
+
+def liquid() -> Liquid:
+    c = (
+        Liquid()
+        .add("lq", [0.67, 0.30, 0.15])
+        .set_global_opts(title_opts=opts.TitleOpts(title="Liquid"))
+    )
+    return c
+
+liquid().render('./img/liquid.html')
+```
+
+水球图的取值`[0.67, 0.30, 0.15]`表示下图中的`三个波浪线`，一般代表三个百分比:
+
+![](./img/liquid.gif)
+
+#### 16 pyecharts饼图
+
+```python
+from pyecharts import options as opts
+from pyecharts.charts import Pie
+from random import randint
+
+def pie_base() -> Pie:
+    c = (
+        Pie()
+        .add("", [list(z) for z in zip(['宝马', '法拉利', '奔驰', '奥迪', '大众', '丰田', '特斯拉'],
+                                       [randint(1, 20) for _ in range(7)])])
+        .set_global_opts(title_opts=opts.TitleOpts(title="Pie-基本示例"))
+        .set_series_opts(label_opts=opts.LabelOpts(formatter="{b}: {c}"))
+    )
+    return c
+
+pie_base().render('./img/pie_pyecharts.html')
+```
+
+#### 17 pyecharts极坐标图
+
+```python
+import random
+from pyecharts import options as opts
+from pyecharts.charts import Page, Polar
+
+def polar_scatter0() -> Polar:
+    data = [(alpha, random.randint(1, 100)) for alpha in range(101)] # r = random.randint(1, 100)
+    print(data)
+    c = (
+        Polar()
+        .add("", data, type_="bar", label_opts=opts.LabelOpts(is_show=False))
+        .set_global_opts(title_opts=opts.TitleOpts(title="Polar"))
+    )
+    return c
+
+polar_scatter0().render('./img/polar.html')
+```
+
+极坐标表示为`(夹角,半径)`，如(6,94)表示夹角为6，半径94的点：
+![](https://i.loli.net/2019/12/28/QxVOFuDB5y6wgpJ.png)
+
+#### 18 pyecharts词云图
+
+```python
+from pyecharts import options as opts
+from pyecharts.charts import Page, WordCloud
+from pyecharts.globals import SymbolType
+
+words = [
+    ("Python", 100),
+    ("C++", 80),
+    ("Java", 95),
+    ("R", 50),
+    ("JavaScript", 79),
+    ("C", 65)
+]
+
+def wordcloud() -> WordCloud:
+    c = (
+        WordCloud()
+        # word_size_range: 单词字体大小范围
+        .add("", words, word_size_range=[20, 100], shape='cardioid')
+        .set_global_opts(title_opts=opts.TitleOpts(title="WordCloud"))
+    )
+    return c
+
+wordcloud().render('./img/wordcloud.html')
+```
+
+`("C",65)`表示在本次统计中C语言出现65次
+
+![](https://i.loli.net/2019/12/28/nSs8MY9Dc4I1egk.png)
+
+#### 19 pyecharts系列柱状图
+
+```python
+from pyecharts import options as opts
+from pyecharts.charts import Bar
+from random import randint
+
+def bar_series() -> Bar:
+    c = (
+        Bar()
+        .add_xaxis(['宝马', '法拉利', '奔驰', '奥迪', '大众', '丰田', '特斯拉'])
+        .add_yaxis("销量", [randint(1, 20) for _ in range(7)])
+        .add_yaxis("产量", [randint(1, 20) for _ in range(7)])
+        .set_global_opts(title_opts=opts.TitleOpts(title="Bar的主标题", subtitle="Bar的副标题"))
+    )
+    return c
+
+bar_series().render('./img/bar_series.html')
+```
+
+![](https://i.loli.net/2019/12/28/egamLZw2oMHA19T.png)
+
+ 
+
+#### 20 pyecharts热力图
+
+```python
+import random
+from pyecharts import options as opts
+from pyecharts.charts import HeatMap
+
+def heatmap_car() -> HeatMap:
+    x = ['宝马', '法拉利', '奔驰', '奥迪', '大众', '丰田', '特斯拉']
+    y = ['中国','日本','南非','澳大利亚','阿根廷','阿尔及利亚','法国','意大利','加拿大']
+    value = [[i, j, random.randint(0, 100)]
+             for i in range(len(x)) for j in range(len(y))]
+    c = (
+        HeatMap()
+        .add_xaxis(x)
+        .add_yaxis("销量", y, value)
+        .set_global_opts(
+            title_opts=opts.TitleOpts(title="HeatMap"),
+            visualmap_opts=opts.VisualMapOpts(),
+        )
+    )
+    return c
+
+heatmap_car().render('./img/heatmap_pyecharts.html')
+```
+
+热力图描述的实际是三维关系，x轴表示车型，y轴表示国家，每个色块的颜色值代表销量，颜色刻度尺显示在左下角，颜色越红表示销量越大。
+
+![image-20191229101724665](./img/image-20191229101724665.png)
+
+
+
 ### 七、Python实战