基于Python pyecharts实现多种图例代码解析
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2020-09-16
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基于基于Python pyecharts实现多种图例代码解析实现多种图例代码解析
主要介绍了基于Python pyecharts实现多种图例代码解析,文中通过示例代码介绍的非常详细，对大家的学习或者工作具有一定的参考
学习价值,需要的朋友可以参考下
词云图词云图
from pyecharts.charts import WordCloud
def word1():
words= [
("Sam S Club", 10000),
("Macys", 6181),
("Amy Schumer", 4386),
("Jurassic World", 4055),
("Charter Communications", 2467),
("Chick Fil A", 2244),
("Planet Fitness", 1868),
("Pitch Perfect", 1484),
("Express", 1112),
("Home", 865),
("Johnny Depp", 847),
("Lena Dunham", 582),
("Lewis Hamilton", 555),
("KXAN", 550),
("Mary Ellen Mark", 462),
("Farrah Abraham", 366),
("Rita Ora", 360),
("Serena Williams", 282),
("NCAA baseball tournament", 273),
("Point Break", 265),
]
worldcloud = (
WordCloud()
.add("", words, word_size_range=[20, 100])
.set_global_opts(title_opts=opt.TitleOpts(title="WorldCloud-shape-diamond"))
)
# worldcloud = (
# WordCloud()
# .add("", words, word_size_range=[20, 100], shape=SymbolType.DIAMOND)
# .set_global_opts(title_opts=opt.TitleOpts(title="WorldCloud-shape-diamond"))
# )
worldcloud.render("wordl.html")
os.system("wordl.html")
效果如下:
散点图散点图
from pyecharts.charts import Scatter
import numpy as np
def sca():
x_data = np.linspace(0, 10, 30)
y1_data = np.sin(x_data)
y2_data = np.cos(x_data)
# 绘制散点图
# 设置图表大小
figsise = opt.InitOpts(width="800px", height="600px")
scatter = Scatter(init_opts=figsise)
# 添加数据
scatter.add_xaxis(xaxis_data=x_data)
scatter.add_yaxis(series_name="sin(x)散点图", #名称
y_axis=y1_data, # 数据
label_opts=opt.LabelOpts(is_show=False), # 数据不显示
symbol_size=15, # 设置散点的大小
symbol="triangle" # 设置散点的形状
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