数据可视化第二版-03部分-09章-时间趋势
总结
本系列博客为基于《数据可视化第二版》一书的教学资源博客。本文主要是第9章，时间趋势可视化的案例相关。
可视化视角-时间趋势
代码实现
安装依赖
pip install scikit-learn -i https://pypi.tuna.tsinghua.edu.cn/simple pip install seaborn -i https://pypi.tuna.tsinghua.edu.cn/simple pip install tushare==1.2.89 -i https://pypi.tuna.tsinghua.edu.cn/simple pip install mplfinance==0.12.9b7 -i https://pypi.tuna.tsinghua.edu.cn/simple
折线图
折线图1
# 折线图实现1 import matplotlib.pyplot as plt # 解决中文乱码问题 plt.rcParams['font.sans-serif'] = ['SimHei'] # X轴，Y轴数据 x = [0, 1, 2, 3, 4, 5, 6] y = [64, 70, 88, 80, 77, 85, 80] plt.figure(figsize=(8, 4)) # 创建绘图对象 # 在当前绘图对象绘图，设置曲线参数（X轴，Y轴，红色实线，线宽度） plt.plot(x, y, color="r", marker="p", linestyle="-", alpha=0.5, mfc="c") plt.xlabel("测验次数") # X轴标签 plt.ylabel("分数") # Y轴标签 plt.title("小明成绩变化图") # 图标题 plt.show() # 显示图
输出为：
折线图案例2
# 折线图实现二 import matplotlib.pyplot as plt plt.rcParams['font.sans-serif'] = ['SimHei'] # 解决中文乱码问题 x = range(1, 11) y1 = [0.840, 0.839, 0.834, 0.832, 0.824, 0.831, 0.823, 0.820, 0.814, 0.815] y2 = [0.838, 0.840, 0.840, 0.834, 0.828, 0.814, 0.812, 0.822, 0.840, 0.835] plt.plot(x, y1, marker='*', mec='r', mfc='b', label='小明') plt.plot(x, y2, marker='*', mec='y', mfc='r', label='小红') plt.legend() # 让图例生效 plt.xticks(x, rotation=1) plt.xlabel('射击次数') # X轴标签 plt.ylabel("得分") # Y轴标签 plt.ylim(0.8, 0.85) plt.title("两名玩家十次射击游戏的得分") # 标题 plt.show()
折线图示例3-seaborn
参考:https://blog.csdn.net/m0_38139250/article/details/129729191
import numpy as np import pandas as pd import matplotlib.pyplot as plt import matplotlib as mpl import seaborn as sns sns.set_theme(style="darkgrid") mpl.rcParams['font.sans-serif']=['SimHei'] mpl.rcParams['axes.unicode_minus']=False flights = sns.load_dataset("flights",cache=True,data_home=r'.\seaborn-data') flights.head() #使用标记而不是破折号来识别组 ax = sns.lineplot(x="year", y="passengers",hue="month", style="month", markers=True, dashes=False, data=flights) plt.show()
面积图
# 堆叠面积图 from matplotlib import pyplot as plt plt.rcParams['font.sans-serif'] = ['SimHei'] # 解决中文乱码问题 x = [i for i in range(30)] y1 = [x ** 2 - 2 * x + 500 for x in range(30)] y2 = [2 * x ** 2 for x in range(30)] plt.plot(x, y1) plt.plot(x, y2) plt.fill_between(x, y1, color='skyblue', alpha=0.4, label='A产品') plt.fill_between(x, y2, color='lightpink', alpha=0.4, label='B产品') plt.xlabel('天数') plt.ylabel('商品的销量') plt.title('两种商品一个月内的销量', fontsize=18) plt.legend() # 让图例生效 plt.show()
面积图2-堆积面积图
# 堆叠面积图 import matplotlib.pyplot as plt plt.rcParams['font.sans-serif'] = ['SimHei'] # 解决中文乱码问题 days = [1, 2, 3, 4, 5] sleeping = [7, 8, 6, 9, 10] eating = [2, 1, 4, 3, 2] working = [9, 10, 8, 4, 5] playing = [6, 5, 6, 8, 7] plt.figure(figsize=(9, 6)) plt.stackplot(days, sleeping, eating, working, playing) plt.xlabel('天数') plt.ylabel('活动时间') plt.xticks([1, 2, 3, 4, 5]) plt.title('日常活动所占时间面积图', fontsize=18) plt.legend(['睡觉', '吃饭', '工作', '玩耍'], fontsize=18) plt.show()
河流图
参考:
河流图1
# 社团招新河流图 import pyecharts.options as opts from pyecharts.charts import ThemeRiver x_data = ["书画协会", "嘻哈社", "厨艺社"] y_data = [ ["2018/09/01", 10, "书画协会"], ["2019/09/01", 1, "书画协会"], ["2020/09/01", 3, "书画协会"], ["2018/09/01", 1, "嘻哈社"], ["2019/09/01", 2, "嘻哈社"], ["2020/09/01", 3, "嘻哈社"], ["2018/09/01", 4, "厨艺社"], ["2019/09/01", 5, "厨艺社"], ["2020/09/01", 6, "厨艺社"], ] ( ThemeRiver(init_opts=opts.InitOpts(width="1000px", height="500px")) .add( series_name=x_data, data=y_data, singleaxis_opts=opts.SingleAxisOpts( pos_top="50", pos_bottom="50", type_="time" ), ) .set_global_opts( tooltip_opts=opts.TooltipOpts(trigger="axis", axis_pointer_type="line") ) .render("社团招新人数河流图.html") )
河流图2
import pyecharts.options as opts from pyecharts.charts import ThemeRiver """ Gallery 使用 pyecharts 1.1.0 参考地址: https://echarts.apache.org/examples/editor.html?c=themeRiver-basic 目前无法实现的功能: 1、暂时无法设置阴影样式 """ x_data = ["DQ", "TY", "SS", "QG", "SY", "DD"] y_data = [ ["2015/11/08", 10, "DQ"], ["2015/11/09", 15, "DQ"], ["2015/11/10", 35, "DQ"], ["2015/11/11", 38, "DQ"], ["2015/11/12", 22, "DQ"], ["2015/11/13", 16, "DQ"], ["2015/11/14", 7, "DQ"], ["2015/11/15", 2, "DQ"], ["2015/11/16", 17, "DQ"], ["2015/11/17", 33, "DQ"], ["2015/11/18", 40, "DQ"], ["2015/11/19", 32, "DQ"], ["2015/11/20", 26, "DQ"], ["2015/11/21", 35, "DQ"], ["2015/11/22", 40, "DQ"], ["2015/11/23", 32, "DQ"], ["2015/11/24", 26, "DQ"], ["2015/11/25", 22, "DQ"], ["2015/11/26", 16, "DQ"], ["2015/11/27", 22, "DQ"], ["2015/11/28", 10, "DQ"], ["2015/11/08", 35, "TY"], ["2015/11/09", 36, "TY"], ["2015/11/10", 37, "TY"], ["2015/11/11", 22, "TY"], ["2015/11/12", 24, "TY"], ["2015/11/13", 26, "TY"], ["2015/11/14", 34, "TY"], ["2015/11/15", 21, "TY"], ["2015/11/16", 18, "TY"], ["2015/11/17", 45, "TY"], ["2015/11/18", 32, "TY"], ["2015/11/19", 35, "TY"], ["2015/11/20", 30, "TY"], ["2015/11/21", 28, "TY"], ["2015/11/22", 27, "TY"], ["2015/11/23", 26, "TY"], ["2015/11/24", 15, "TY"], ["2015/11/25", 30, "TY"], ["2015/11/26", 35, "TY"], ["2015/11/27", 42, "TY"], ["2015/11/28", 42, "TY"], ["2015/11/08", 21, "SS"], ["2015/11/09", 25, "SS"], ["2015/11/10", 27, "SS"], ["2015/11/11", 23, "SS"], ["2015/11/12", 24, "SS"], ["2015/11/13", 21, "SS"], ["2015/11/14", 35, "SS"], ["2015/11/15", 39, "SS"], ["2015/11/16", 40, "SS"], ["2015/11/17", 36, "SS"], ["2015/11/18", 33, "SS"], ["2015/11/19", 43, "SS"], ["2015/11/20", 40, "SS"], ["2015/11/21", 34, "SS"], ["2015/11/22", 28, "SS"], ["2015/11/23", 26, "SS"], ["2015/11/24", 37, "SS"], ["2015/11/25", 41, "SS"], ["2015/11/26", 46, "SS"], ["2015/11/27", 47, "SS"], ["2015/11/28", 41, "SS"], ["2015/11/08", 10, "QG"], ["2015/11/09", 15, "QG"], ["2015/11/10", 35, "QG"], ["2015/11/11", 38, "QG"], ["2015/11/12", 22, "QG"], ["2015/11/13", 16, "QG"], ["2015/11/14", 7, "QG"], ["2015/11/15", 2, "QG"], ["2015/11/16", 17, "QG"], ["2015/11/17", 33, "QG"], ["2015/11/18", 40, "QG"], ["2015/11/19", 32, "QG"], ["2015/11/20", 26, "QG"], ["2015/11/21", 35, "QG"], ["2015/11/22", 40, "QG"], ["2015/11/23", 32, "QG"], ["2015/11/24", 26, "QG"], ["2015/11/25", 22, "QG"], ["2015/11/26", 16, "QG"], ["2015/11/27", 22, "QG"], ["2015/11/28", 10, "QG"], ["2015/11/08", 10, "SY"], ["2015/11/09", 15, "SY"], ["2015/11/10", 35, "SY"], ["2015/11/11", 38, "SY"], ["2015/11/12", 22, "SY"], ["2015/11/13", 16, "SY"], ["2015/11/14", 7, "SY"], ["2015/11/15", 2, "SY"], ["2015/11/16", 17, "SY"], ["2015/11/17", 33, "SY"], ["2015/11/18", 40, "SY"], ["2015/11/19", 32, "SY"], ["2015/11/20", 26, "SY"], ["2015/11/21", 35, "SY"], ["2015/11/22", 4, "SY"], ["2015/11/23", 32, "SY"], ["2015/11/24", 26, "SY"], ["2015/11/25", 22, "SY"], ["2015/11/26", 16, "SY"], ["2015/11/27", 22, "SY"], ["2015/11/28", 10, "SY"], ["2015/11/08", 10, "DD"], ["2015/11/09", 15, "DD"], ["2015/11/10", 35, "DD"], ["2015/11/11", 38, "DD"], ["2015/11/12", 22, "DD"], ["2015/11/13", 16, "DD"], ["2015/11/14", 7, "DD"], ["2015/11/15", 2, "DD"], ["2015/11/16", 17, "DD"], ["2015/11/17", 33, "DD"], ["2015/11/18", 4, "DD"], ["2015/11/19", 32, "DD"], ["2015/11/20", 26, "DD"], ["2015/11/21", 35, "DD"], ["2015/11/22", 40, "DD"], ["2015/11/23", 32, "DD"], ["2015/11/24", 26, "DD"], ["2015/11/25", 22, "DD"], ["2015/11/26", 16, "DD"], ["2015/11/27", 22, "DD"], ["2015/11/28", 10, "DD"], ] ( ThemeRiver() .add( series_name=x_data, data=y_data, singleaxis_opts=opts.SingleAxisOpts( pos_top="50", pos_bottom="50", type_="time" ), ) .set_global_opts( tooltip_opts=opts.TooltipOpts(trigger="axis", axis_pointer_type="line") ) .render("theme_river.html") )
瀑布图
瀑布图-matplotlib
# 收益瀑布图 import numpy as np import matplotlib.pyplot as plt import random plt.rcParams['font.sans-serif'] = ['SimHei'] # 解决中文乱码问题 plt.rcParams['axes.unicode_minus'] = False # 正常显示负号 profit = [random.randint(-50, 100) for i in range(10)] bottom = 0 bar_width = 0.8 x_tic = np.arange(len(profit), dtype=np.float64) for i in range(10): x = x_tic[i] y = profit[i] if profit[i] > 0: label1 = '盈利' revenue = plt.bar(x, y, bar_width, align='center', bottom=bottom, label=label1, color='red') else: label1 = '亏损' cost = plt.bar(x, y, bar_width, align='center', bottom=bottom, label=label1, color='green') bottom += y x += 0.8 plt.legend(handles=[revenue, cost]) plt.title("瀑布图") plt.xlabel('时间') plt.ylabel('收益') plt.show()
瀑布图-pyecharts
参考:使用 Pyecharts 制作 Bar（柱状图/条形图/瀑布图）
步进图
步进图1-
# 步近图 import matplotlib.pyplot as plt import random plt.rcParams['font.sans-serif'] = ['SimHei'] # 解决中文乱码问题 y = [random.randint(0, 30) for i in range(10)] x = [i for i in range(10)] plt.plot(x, y, drawstyle='steps-mid', c='red') plt.xlabel('天数') plt.ylabel('价格') plt.title('某种商品十天价格变化') plt.show()
烛形图-
# 烛形图 import tushare as ts import mplfinance as mpf import pandas as pd # 获得数据 quotes = ts.get_hist_data('603970', '2020') print(quotes.head()) # 将索引转化为需要的格式 quotes.index = pd.to_datetime(quotes.index) mpf.plot(quotes, type="candle", title="candle charts for stocks", ylabel="price($)")
