如何使用 pyecharts 中自带的数据集?我们在学习pyehcarts绘图的过程中,需要一些练习的数据。 pyecharts为我们提供了这样的数据集 -- Faker,存储于 faker.py 文件中。 下面,我们就来详细介绍一下。 1. Faker中包含的数据集这些数据集以列表的方式存储,主要包含类别数据、时间数据、颜色数据、地理数据、世界人口数据。 (1)类别数据clothes = ["衬衫", "毛衣", "领带", "裤子", "风衣", "高跟鞋", "袜子"] drinks = ["可乐", "雪碧", "橙汁", "绿茶", "奶茶", "百威", "青岛"] phones = ["小米", "三星", "华为", "苹果", "魅族", "VIVO", "OPPO"] fruits = ["草莓", "芒果", "葡萄", "雪梨", "西瓜", "柠檬", "车厘子"] animal = ["河马", "蟒蛇", "老虎", "大象", "兔子", "熊猫", "狮子"] cars = ["宝马", "法拉利", "奔驰", "奥迪", "大众", "丰田", "特斯拉"] dogs = ["哈士奇", "萨摩耶", "泰迪", "金毛", "牧羊犬", "吉娃娃", "柯基"]
(2)时间数据week = ["周一", "周二", "周三", "周四", "周五", "周六", "周日"] week_en = "Saturday Friday Thursday Wednesday Tuesday Monday Sunday".split() clock = ( "12a 1a 2a 3a 4a 5a 6a 7a 8a 9a 10a 11a 12p " "1p 2p 3p 4p 5p 6p 7p 8p 9p 10p 11p".split() ) months = ["{}月".format(i) for i in range(1, 13)] days_attrs = ["{}天".format(i) for i in range(30)] days_values = [random.randint(1, 30) for _ in range(30)]
(3)颜色数据visual_color = [ "#313695", "#4575b4", "#74add1", "#abd9e9", "#e0f3f8", "#ffffbf", "#fee090", "#fdae61", "#f46d43", "#d73027", "#a50026", ]
(4)地理数据provinces = ["广东", "北京", "上海", "江西", "湖南", "浙江", "江苏"] guangdong_city = ["汕头市", "汕尾市", "揭阳市", "阳江市", "肇庆市", "广州市", "惠州市"] country = [ "China", "Canada", "Brazil", "Russia", "United States", "Africa", "Germany", ]
(5)世界人口数据2019年世界人口数据集,结构为二层嵌套列表,结构如下,第一列为国家或地区,第二列为人口数量。 POPULATION = [ ["Country (or dependency)", "Population\n(2019)"], ["China", 1420062022], ["India", 1368737513], ["United States", 329093110], ["Indonesia", 269536482], ["Brazil", 212392717], ["Pakistan", 204596442], ["Nigeria", 200962417], ["Bangladesh", 168065920], ["Russia", 143895551], ["Mexico", 132328035], ["Japan", 126854745], ["Ethiopia", 110135635], ... ]
2. Faker中数据集的选取choose :随机选择类别数据集
def choose(self) -> list: return random.choice( [ self.clothes, self.drinks, self.phones, self.fruits, self.animal, self.dogs, self.week, ] )
values :随机生成7个数字(20-150)构成的列表
@staticmethod def values(start: int = 20, end: int = 150) -> list: return [random.randint(start, end) for _ in range(7)]
rand_color :随机从列表中生成1个颜色值
@staticmethod def rand_color() -> str: return random.choice( [ "#c23531", "#2f4554", "#61a0a8", "#d48265", "#749f83", "#ca8622", "#bda29a", "#6e7074", "#546570", "#c4ccd3", "#f05b72", "#444693", "#726930", "#b2d235", "#6d8346", "#ac6767", "#1d953f", "#6950a1", ] )
3. 例子例子1:绘制折线图 from pyecharts.faker import Faker from pyecharts.charts import Line from pyecharts.globals import ThemeType
c = Line({"theme": ThemeType.DARK}) c.add_xaxis(Faker.choose()) c.add_yaxis('商家A', Faker.values()) c.add_yaxis('商家B', Faker.values()) c.set_global_opts(title_opts={"text": "Faker数据集练习"}) c.render('line_base.html')
例2:绘制柱状图 from pyecharts.faker import Faker from pyecharts.charts import Bar from pyecharts.globals import ThemeType
c = Bar({"theme": ThemeType.MACARONS}) c.add_xaxis(Faker.choose()) c.add_yaxis('商家A', Faker.values()) c.add_yaxis('商家B', Faker.values()) c.set_global_opts(title_opts={"text": "Faker数据集练习"}) c.render('bar_base.html')
例子3:涟漪散点图 from pyecharts.faker import Faker from pyecharts.charts import EffectScatter from pyecharts.globals import ThemeType
c = EffectScatter({"theme": ThemeType.VINTAGE}) c.add_xaxis(Faker.choose()) c.add_yaxis('', Faker.values()) c.set_global_opts(title_opts={"text": "Faker数据集练习"}) c.render('effectscatter_base.html')
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