又一款超酷的 Python 可视化神器:cutecharts

Python学习与数据挖掘

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2022-01-03 03:21

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前言

大家好,今天给大家介绍一个很酷的 Python 手绘风格可视化神包:cutecharts

和 Matplotlib 、pyecharts 等常见的图表不同,使用这个包可以生成看起来像手绘的各种图表,在一些特殊场景下使用效果可能会更好。

GitHub 地址:

https://github.com/chenjiandongx/cutecharts

它的画风是这样的:

  • cutecharts是由pyecharts作者chenjiandongx开源的一个轻量级的项目;

  • 目前支持BarLinePieRadarScatter五种图表;

  • 支持Page组合图表;

安装

  •  pip install cutecharts;

Line——基本示例

支持的参数直接参考源码中的注释就好~


def set_options(        self,        labels: Iterable,        x_label: str = "",        y_label: str = "",        y_tick_count: int = 3,        legend_pos: str = "upLeft",        colors: Optional[Iterable] = None,        font_family: Optional[str] = None,    ):        """        :param labels: X 坐标轴标签数据        :param x_label: X 坐标轴名称        :param y_label: Y 坐标轴名称        :param y_tick_count: Y 轴刻度分割段数        :param legend_pos: 图例位置,有 "upLeft", "upRight", "downLeft", "downRight" 可选        :param colors: label 颜色数组        :param font_family: CSS font-family        """

def add_series(self, name: str, data: Iterable): """ :param name: series 名称 :param data: series 数据列表 """


基本示例


from cutecharts.charts import Line# 虚假数据x_data = ['Apple', 'Huawei', 'Xiaomi', 'Oppo', 'Vivo', 'Meizu', 'OnePlus']y_data_1 = [57, 134, 137, 129, 145, 60, 49]y_data_2 = [114, 55, 27, 101, 125, 27, 105]
chart = Line("Mobile phone sales")chart.set_options( labels=x_data, x_label="Brand", y_label="Sales",)chart.add_series("series-A", y_data_1)chart.add_series("series-B", y_data_2)chart.render_notebook()


修改图例位置


from cutecharts.charts import Line# 虚假数据x_data = ['Apple', 'Huawei', 'Xiaomi', 'Oppo', 'Vivo', 'Meizu', 'OnePlus']y_data_1 = [57, 134, 137, 129, 145, 60, 49]y_data_2 = [114, 55, 27, 101, 125, 27, 105]
chart = Line("Mobile phone sales")chart.set_options( labels=x_data, x_label="Brand", y_label="Sales", legend_pos="upRight")chart.add_series("series-A", y_data_1)chart.add_series("series-B", y_data_2)chart.render_notebook()


Bar——基本示例

不支持多个系列的数据~


def set_options(        self,        labels: Iterable,        x_label: str = "",        y_label: str = "",        y_tick_count: int = 3,        colors: Optional[Iterable] = None,        font_family: Optional[str] = None,    ):        """        :param labels: X 坐标轴标签数据        :param x_label: X 坐标轴名称        :param y_label: Y 坐标轴名称        :param y_tick_count: Y 轴刻度分割段数        :param colors: label 颜色数组        :param font_family: CSS font-family        """
def add_series(self, name: str, data: Iterable): """ :param name: series 名称 :param data: series 数据列表 """


基本示例


# 虚假数据x_data = ['Apple', 'Huawei', 'Xiaomi', 'Oppo', 'Vivo', 'Meizu', 'OnePlus']y_data = [57, 134, 137, 129, 145, 60, 49]
chart = Bar("Mobile phone sales")chart.set_options( labels=x_data, x_label="Brand", y_label="Sales", colors=Faker.colors)chart.add_series("series-A", y_data)
chart.render_notebook()


Pie——基本示例


def set_options(        self,        labels: Iterable,        inner_radius: float = 0.5,        legend_pos: str = "upLeft",        colors: Optional[Iterable] = None,        font_family: Optional[str] = None,    ):        """        :param labels: 数据标签列表        :param inner_radius: Pie 图半径        :param legend_pos: 图例位置,有 "upLeft", "upRight", "downLeft", "downRight" 可选        :param colors: label 颜色数组        :param font_family: CSS font-family        """

def add_series(self, data: Iterable): """ :param data: series 数据列表 """


基本示例


# 虚假数据x_data = ['Apple', 'Huawei', 'Xiaomi', 'Oppo', 'Vivo', 'Meizu', 'OnePlus']y_data = [57, 134, 137, 129, 145, 60, 49]
chart = Pie("Mobile phone sales")chart.set_options( labels=x_data, colors=Faker.colors)chart.add_series(y_data)
chart.render_notebook()


修改内圈半径


# 虚假数据x_data = ['Apple', 'Huawei', 'Xiaomi', 'Oppo', 'Vivo', 'Meizu', 'OnePlus']y_data = [57, 134, 137, 129, 145, 60, 49]
chart = Pie("Mobile phone sales")chart.set_options( labels=x_data, inner_radius=0, colors=Faker.colors)chart.add_series(y_data)
chart.render_notebook()


Radar——基本示例

参考代码注释:


def set_options(        self,        labels: Iterable,        is_show_label: bool = True,        is_show_legend: bool = True,        tick_count: int = 3,        legend_pos: str = "upLeft",        colors: Optional[Iterable] = None,        font_family: Optional[str] = None,    ):        """        :param labels: 数据标签列表        :param is_show_label: 是否显示标签        :param is_show_legend: 是否显示图例        :param tick_count: 坐标系分割刻度        :param legend_pos: 图例位置,有 "upLeft", "upRight", "downLeft", "downRight" 可选        :param colors: label 颜色数组        :param font_family: CSS font-family        """

def add_series(self, name: str, data: Iterable): """ :param name: series 名称 :param data: series 数据列表 """


基本示例


# 虚假数据x_data = ['Apple', 'Huawei', 'Xiaomi', 'Oppo', 'Vivo', 'Meizu', 'OnePlus']y_data_1 = [57, 134, 137, 129, 145, 60, 49]y_data_2 = [114, 55, 27, 101, 125, 27, 105]
chart = Radar("Mobile phone sales")chart.set_options( labels=x_data, is_show_legend=True, colors=Faker.colors)chart.add_series("series-A", y_data_1)chart.add_series("series-B", y_data_2)chart.render_notebook()


Scatter——基本示例


   def set_options(        self,        x_label: str = "",        y_label: str = "",        x_tick_count: int = 3,        y_tick_count: int = 3,        is_show_line: bool = False,        dot_size: int = 1,        time_format: Optional[str] = None,        legend_pos: str = "upLeft",        colors: Optional[Iterable] = None,        font_family: Optional[str] = None,    ):        """        :param x_label: X 坐标轴名称        :param y_label: Y 坐标轴名称        :param x_tick_count: X 轴刻度分割段数        :param y_tick_count: Y 轴刻度分割段数        :param is_show_line: 是否将散点连成线        :param dot_size: 散点大小        :param time_format: 日期格式        :param legend_pos: 图例位置,有 "upLeft", "upRight", "downLeft", "downRight" 可选        :param colors: label 颜色数组        :param font_family: CSS font-family        """

def add_series(self, name: str, data: Iterable): """ :param name: series 名称 :param data: series 数据列表,[(x1, y1), (x2, y2)] """


基本示例


# 随机生成数据data_1 = [(random.randint(0, 100), random.randint(0, 100)) for _ in range(100)]data_2 = [(random.randint(0, 100), random.randint(0, 100)) for _ in range(100)]
chart = Scatter("random dot")chart.set_options( x_label = "I'm x-label", y_label = "I'm x-yabel", x_tick_count = 3, y_tick_count = 3, is_show_line = False, dot_size = 1, legend_pos = "upLeft", colors=Faker.colors)chart.add_series("series-A", data_1)chart.add_series("series-A", data_2)chart.render_notebook()



点连线


# 随机生成数据data_1 = [(random.randint(0, 100), random.randint(0, 100)) for _ in range(10)]data_2 = [(random.randint(0, 100), random.randint(0, 100)) for _ in range(10)]
chart = Scatter("random dot")chart.set_options( x_label = "I'm x-label", y_label = "I'm x-yabel", x_tick_count = 3, y_tick_count = 3, is_show_line = True, dot_size = 1, legend_pos = "upLeft", colors=Faker.colors)chart.add_series("series-A", data_1)chart.add_series("series-A", data_2)chart.render_notebook()



组合图表——Page


# 虚假数据x_data = ['Apple', 'Huawei', 'Xiaomi', 'Oppo', 'Vivo', 'Meizu', 'OnePlus']y_data = [57, 134, 137, 129, 145, 60, 49]
chart_1 = Pie("Mobile phone sales")chart_1.set_options( labels=x_data, inner_radius=0.6, colors=Faker.colors)chart_1.add_series(y_data)

chart_2 = Bar("Mobile phone sales")chart_2.set_options( labels=x_data, x_label="Brand", y_label="Sales", colors=Faker.colors)chart_2.add_series("series-A", y_data)
page = Page()page.add(chart_1, chart_2)page.render_notebook()

原文链接:https://blog.csdn.net/qq_27484665/article/details/115472329

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