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这篇文章主要介绍“如何用cutecharts库绘制手绘风格的可视化图形”，在日常操作中，相信很多人在如何用cutecharts库绘制手绘风格的可视化图形问题上存在疑惑，小编查阅了各式资料，整理出简单好用的操作方法，希望对大家解答”如何用cutecharts库绘制手绘风格的可视化图形”的疑惑有所帮助！接下来，请跟着小编一起来学习吧！
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# 导入相关的库
import cutecharts.charts as ctc
import pandas as pd
from cutecharts.components import Page
# 构造数据
df = pd.DataFrame({
"x":["蔬菜", "水果", "水产", "猪肉", "零食", "电商", "物料"],
"y":[100, 130, 169, 220, 286, 372, 484],
"z":[20, 26, 34, 44, 57, 74, 96]})1. 柱形图
chart = ctc.Bar("各品类的销售业绩", width = "500px", height = "400px")
chart.set_options(labels = list(df["x"]),
x_label ="部门",
y_label= "销售额（万元）",
colors = ["#1EAFAE" for i in range(len(df))]
)
chart.add_series("2020年",list(df["y"]))
chart.render_notebook()
1.1 自定义各根柱子的颜色
chart = ctc.Bar("各品类的销售业绩", width = "500px", height = "400px")
chart.set_options(labels=list(df["x"]),
x_label = "2020年",
y_label = "销售额（万元）",
colors = ["yellow","orange","pink","red","purple","green","blue"]
)
chart.add_series("2020年",list(df["y"]))
chart.render_notebook()渲染效果：
2. 折线图
chart = ctc.Line("各品类的销售业绩",width = "500px", height = "400px")
chart.set_options(labels = list(df["x"]), x_label ="2020年环比2019年",
y_label = "销售额（万元）" )
chart.add_series("今年", list(df["y"]))
chart.add_series("去年", list(df["z"]))
chart.render_notebook()
3. 雷达图
chart = ctc.Radar("各品类的销售业绩",width = "700px", height = "600px")
chart.set_options(labels=list(df["x"]),
is_show_legend = True, #by default, it is true. You can turn it off.
legend_pos = "upRight" #location of the legend
)
chart.add_series("2020年",list(df["y"]))
chart.add_series("2019年",list(df["z"]))
chart.render_notebook()
4. 饼图
chart = ctc.Pie("各品类销售业绩占比",width ="500px",height = "400px")
chart.set_options(labels=list(df["x"]),inner_radius=0)
chart.add_series(list(df["y"]))
chart.render_notebook()
5. 环形图
chart = ctc.Pie("各品类销售业绩占比",width ="500px",height = "400px")
chart.set_options(labels=list(df["x"]),inner_radius=0.6)
chart.add_series(list(df["y"]))
chart.render_notebook()
6. 散点图
# 再构造一组数据 amount = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20] sales = [100, 200, 300, 400, 500, 600, 700, 800, 900, 1000, 1100, 1200, 1300, 1400, 1500, 1600, 1700, 1800, 1900, 2000]
chart = ctc.Scatter("某种定价商品的销售额与销售量之间的关系",width= "500px",height = "600px")
chart.set_options(x_label = "销售数量（件）",
y_label = "销售额（元）",
colors=["#1EAFAE"],
is_show_line = False,
dot_size = 1)
chart.add_series("进口香印青提", [(z[0], z[1]) for z in zip(amount, sales)])
chart.render_notebook()
7. 组合图
chart1 = ctc.Line("各品类的销售业绩",width ="500px",height ="400px")
chart1.set_options(labels=list(df["x"]), x_label = "品类",y_label = "销售额（万元）" )
chart1.add_series("2020年", list(df["y"]))
chart1.add_series("2019年", list(df["z"]))
chart2 = ctc.Bar("各品类的销售业绩",width = "500px",height = "400px")
chart2.set_options(labels=list(df["x"]),x_label = "品类",
y_label = "销售额（万元）" ,colors=["#1EAFAE" for i in range(len(df))])
chart2.add_series("2020年", list(df["y"]))
chart2.add_series("2019年", list(df["z"]))
page = Page()
page.add(chart1, chart2)
page.render_notebook()
到此，关于“如何用cutecharts库绘制手绘风格的可视化图形”的学习就结束了，希望能够解决大家的疑惑。理论与实践的搭配能更好的帮助大家学习，快去试试吧！若想继续学习更多相关知识，请继续关注创新互联网站，小编会继续努力为大家带来更多实用的文章！