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SAS Box PlotSAS Day 33: Box Plot Definition: Box Plot or Whisker plot displays the distribution of 5-number summary of a dataset: minimum, maximum, q1, q3, and Median. Interpreting quartiles: The 5-number summary approximately divides the data into 4 sections that each containing 25% of the data. Explore a little more If we want to look at the Outliers, we define the points below q1- 1.5(q3-q1) and q3+
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SAS Box PlotSAS Day 33: Box Plot Definition: Box Plot or Whisker plot displays the distribution of 5-number summary of a dataset: minimum, maximum, q1, q3, and Median. Interpreting quartiles: The 5-number summary approximately divides the data into 4 sections that each containing 25% of the data. Explore a little more If we want to look at the Outliers, we define the points below q1- 1.5(q3-q1) and q3+
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SAS Loess PlotSAS Day 32: Loess Model Scatter Plot When I was in Middle School, Sin(x) and Cos(x) are my favorite curves, because they are so predictable! Once we know the cycle and amplitude, we can solve everything about it. However, in statistical modeling, oscillating curves are not so welcomed. Today we will introduce the Loess Plot for finding a curve of best fit without assuming the data must fit
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SAS Loess Scatter PlotSAS Day 32: Loess Model Scatter Plot When I was in Middle School, Sin(x) and Cos(x) are my favorite curves, because they are so predictable! Once we know the cycle and amplitude, we can solve everything about it. However, in statistical modeling, oscillating curves are not so welcomed. Today we will introduce the Loess Plot for finding a curve of best fit without assuming the data must
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- 4.1 基本步骤 step1: 主菜单 File -> New -> Project, 选择 Scientificstep2: 在项目设置对话框窗口中,指定项目名称,确保将 Conda 选为新环境,然后单击"Create"。step3: 自动创建了 main.py并且打开, 在其中加下面的代码。(主要功能是用拆线图展示北京与上海两个城市一小时的温度变化曲线。Tips: 使用Conda 解释器,像Numpy , matplotlib 基本的科学计算包都已经自带了,不需要再单独安装。)# 画出温度变化图import randomimport matplotlib.pyplot as plt# 准备x, y坐标的数据x = range(60)y_shanghai = [random.uniform(15, 18) for i in x]# 增加北京的温度数据y_beijing = [random.uniform(1, 3) for i in x]# 创建画布plt.figure(figsize=(20, 8), dpi=80)# 绘制折线图# plt.plot(x, y_shanghai)plt.plot(x, y_shanghai, label="SHANGHAI")# 使用多次plot可以画多个折线plt.plot(x, y_beijing, color='r', linestyle='--', label="BEIJING")# 显示图例plt.legend(loc="best")# 构造x轴刻度标签x_ticks_label = ["11:{}".format(i) for i in x]# 构造y轴刻度y_ticks = range(40)# 修改x,y轴坐标的刻度显示plt.xticks(x[::5], x_ticks_label[::5])plt.yticks(y_ticks[::5])# 添加网格显示plt.grid(True, linestyle='--', alpha=0.5)# 添加x轴、y轴描述信息及标题plt.xlabel("Time")plt.ylabel("Temperature")plt.title("Temperature Change between 11am and 12am")# 显示图像plt.show()step4: PyCharm 内需启用 Scientific Mode 才能正常显示 matplotlib 相关图表。主菜单View -> Scientific Mode。step5: 运行项目⇧F10 (Shift + F10), 代码执行完毕,会有如下三个工具窗口显示:"SciView"工具窗口。它有两个选项卡, "data"选项卡中预览数据帧,在"plot"选项卡中预览 matplotlib 图表;"Documentation"工具窗口,显示编辑器内光标插入位置处对象的内联文档,比如光标停留在matplotlib 包导入的地方,就会显示 matplotlib 的相关信息;Python 控制台。执行完毕后,自动打开,程序中涉及变量详细值也在右侧边栏自动显示出来。
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