importmatplotlib.pyplotaspltimportmatplotlib.datesasmdatesimportdatetimeimportnumpyasnp# 创建示例数据dates=[datetime.datetime(2023,1,1)+datetime.timedelta(days=i)foriinrange(365)]values=np.random.randn(365).cumsum(
为了进一步增强虚线水平参考线的视觉效果,我们可以调整线条的宽度和透明度: importmatplotlib.pyplotaspltimportnumpyasnp x=np.linspace(0,10,100)y=np.exp(-x/10)*np.cos(2*np.pi*x)plt.figure(figsize=(10,6))plt.plot(x,y)plt.axhline(y=0.5,color='r',linestyle='--',linewidth=2,alpha=0.7)p...
Method 1: Using set() method: In the set() method, we have to pass the xlabel and ylabel parameter values to determine the labels for the x and y axes. Here is a code snippet showing how to use it. import seaborn as sns import numpy as np import matplotlib.pyplot as plt import pa...
plt.plot(x, y) plt.yscale('logit') plt.title('logit') plt.grid(True) # Format the minor tick labels of the y-axis into empty strings with # `NullFormatter`, to avoid cumbering the axis with too many labels. plt.gca().yaxis.set_minor_formatter(NullFormatter()) # Adjust the subplot...
import numpy as np import matplotlib.pyplot as plt t = np.arange(0.0, 3.0, 0.01) s = np.sin(2.5 * np.pi * t) plt.plot(t, s) plt.xlabel('time (s)') plt.ylabel('voltage (mV)') plt.title('Sine Wave') plt.grid(True) ...
As a teaser, here is the plot we’re gonna try building: Load libraries As always, the first step is to import some libraries. import matplotlib.pyplot as plt import numpy as np import pandas as pd Load and prepare the data Today's chart visualizes the price changes (in USD) of a ...
array([5, 4, 3, 2, 1]) # Plotting all lines with labels plt.plot(x1, y1, label='Line 1') plt.plot(x2, y2, label='Line 2') plt.plot(x3, y3, label='Line 3') # Adding legend, x and y labels, and title for the lines plt.legend() plt.xlabel('X-axis') plt.ylabel(...
importnumpyasnp# Generate some datax = np.linspace(0,10,100) y = np.sin(x)# Create a line plotplt.plot(x, y)# Add labels and titleplt.xlabel('Time (s)') plt.ylabel('Amplitude') plt.title('Sine Wave')# Show the plotplt.show() ...
# Plot the stacked area chart with smoothing and custom colorsplt.figure(figsize=(6,6))# Set the figure sizeplt.stackplot(x_smooth,pivot_smooth.values.T,labels=pivot_smooth.columns,colors=custom_colors)plt.xlabel('Year')plt.ylabel('Total Wealth')plt.title('Stacked Area Chart with Smoothing...
数学建模仓库包括了一些常用的数学模型、绘图方法以及其他工具,仓库中的代码文件由Python语言编写。 - MathModels/Models/mcdm.py at main · GalacticLine/MathModels