面积(km?) 人口(人) GDP(亿美元) 人均GDP(美元) 2,586 502,100 598 110424 385,054 5,144,600 5112.5 100318 11,000 1,696,563 2025.6 100260 2 35,000 31.5 90000 41,284 7,866,500 6508 81324 7,692,024 23,540,517 15053 64863 43,094 5,564,219 3309.5 59191 449,964 9,440,588 5579 57909 704 5,076,700 2957 54776 9,629,091 317,408,015 167997 53101 9,984,670 34,591,000 18251 51990 83,858 8,404,252 4153.6 48957 17,818 2,737,000 1853 47639 41,528 16,697,800 8000 47634 338,145 5,449,950 2569 47129使用上述数据绘制四维数据散点图,面积作为X轴,人口作为Y轴,GDP控制散点大小,人均GDP控制散点颜色,使用pyecharts,写出代码
时间: 2023-09-11 15:12:22 浏览: 135
好的,以下是使用Python的pyecharts库绘制四维数据散点图的代码:
```python
from pyecharts import options as opts
from pyecharts.charts import Scatter
# 定义数据
data = [
[2586, 502100, 598, 110424],
[385054, 5144600, 5112.5, 100318],
[11000, 1696563, 2025.6, 100260],
[2, 35000, 31.5, 90000],
[41284, 7866500, 6508, 81324],
[7692024, 23540517, 15053, 64863],
[43094, 5564219, 3309.5, 59191],
[449964, 9440588, 5579, 57909],
[704, 5076700, 2957, 54776],
[9629091, 317408015, 167997, 53101],
[9984670, 34591000, 18251, 51990],
[83858, 8404252, 4153.6, 48957],
[17818, 2737000, 1853, 47639],
[41528, 16697800, 8000, 47634],
[338145, 5449950, 2569, 47129]
]
# 绘制散点图
scatter = (
Scatter()
.add_xaxis([d[0] for d in data])
.add_yaxis("", [d[1] for d in data], symbol_size=[d[2]/10 for d in data], label_opts=opts.LabelOpts(is_show=False), itemstyle_opts=opts.ItemStyleOpts(color=opts.Color('#5470C6')))
.set_global_opts(
title_opts=opts.TitleOpts(title="四维数据散点图"),
xaxis_opts=opts.AxisOpts(
name="面积(km²)",
splitline_opts=opts.SplitLineOpts(is_show=True),
min_=0
),
yaxis_opts=opts.AxisOpts(
name="人口(人)",
splitline_opts=opts.SplitLineOpts(is_show=True),
min_=0
),
visualmap_opts=opts.VisualMapOpts(
type_="color",
is_calculable=True,
dimension=3,
pos_left="10",
max_=20000,
min_=2000,
range_text=["High", "Low"],
range_color=["lightskyblue", "yellow", "orangered"],
)
)
)
scatter.render_notebook()
```
运行代码后,会在Jupyter Notebook中生成一个交互式的散点图,可以通过鼠标滚轮缩放图表,通过鼠标拖动移动图表。其中,点的大小表示GDP,点的颜色表示人均GDP。
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