#On command line mprof run script.py #To generate plot mprof plot 我们可以看到内存消耗与时间的关系图 @profile装饰器没有必要放在函数前面,如果我们不保留它,我们不会看到函数级内存消耗,但我们会看到整个脚本的内存消耗 自学气象人补充: 下面所示得是可选参数。如果不指定interval的话,默认是0.1s记录一次内...
from tkinter import *window1=Tk()window1.title('test2')canvas1=Canvas(window1,width=500,height=500,bg='pink') # 设置画布() # 显示画布# 利用create_line()在画布上绘制直线canvas1.create_line(100,100,400,100,width=5,fill='red')canvas1.create_line(100,200,400,200,width=15,fill='green...
plt.title('Simple Line Plot') plt.xlabel('X Axis') plt.ylabel('Y Axis') # 显示图表 plt.show() 在Python 交互式会话或脚本中运行这段代码,你将看到一个简单的折线图。 结论 通过本文,你应该已经学会了如何在命令提示符中使用 pip 安装 Matplotlib,并了解了如何验证安装和绘制一个简单的图表。现在你可...
plt.plot(x, y, linewidth=2.0) 1. 2. 用Line2D实例的设置器方法。假设plot返回一列Line2D对象,如line1,line2=plot(x1, y1, x2, y2).在下面的代码中我们将假使我们只有一条线,所以列表返回的长度是1,把列表以line拆包,我们取列表的第一个element line, = plt.plot(x, y, '-') line.set_antia...
plt.plot(df['Mes'], df['data science'], label='data science') # The parameter label is to indicate the legend. This doesn't mean that it will be shown, we'll have to use another command that I'll explain later.结果如下:我们可以在同一张图中制作多个变量的图,然后进行比较。 plt....
Don't forget to finish off with a plt.show() command, to actually display the plot. # Print the last item of gdp_cap and life_exp print(gdp_cap[-1]) print(life_exp[-1]) # Make a line plot, gdp_cap on the x-axis, life_exp on the y-axis plt.plot(gdp_cap,life_exp) # ...
plot_wrapAmodule by Mike Miller which wraps the functions inthe GNU plotutilspackage. BLTBLT is anextension to the tk widgets that can produce X/Y plots and barcharts. The BLT package can be used throughthe Pmw package, a framework forthe creation of megawidgets built on top of Tkinter. ...
bokeh.plotting import figure, output_file, show # 创建图表 p = figure(plot_width=300, plot_...
plot_raw_data() # Predict forecast with Prophet. df_train = data[['Date','Close']] df_train = df_train.rename(columns={"Date":"ds","Close":"y"}) m = Prophet() m.fit(df_train) future = m.make_future_dataframe(periods=period) ...
Thedot plotis a type of data representation in which each data-point in the figure is represented as a dot. Dot plot underlies discrete functions unlike a continuous function in a line plot. Each value could be correlated but cannot be connected.Matplotlib.pyplotprovides a feature of dot plot...