如何分析数据并添加到matplotlib中的绘图

Question

I plotted a curve and I need to do 3 things more to it.

(The code shown below):

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
plt.style.use('seaborn-bright')
print(plt.style.available)
print("NumPy version:", np.__version__)
print("Pandas version:", pd.__version__)
S_S = pd.read_excel("SSCurve.xls")
print(S_S.head())
Stress_Al = S_S['STRESS']
Strain_Al = S_S['STRAIN']
plt.scatter(Strain_Al, Stress_Al)
plt.plot(Strain_Al, Stress_Al)
plt.xlabel('Strain')
plt.ylabel('Stress (MPa)')
plt.title('Engineering Stress Vs Engineering Strain')
plt.tight_layout()
plt.show()

1. I need to know how to get a y-value that corresponds to its x-value.

2. I need to draw a line from a certain point in the x axis that intersects the curve at certain point(something looks like this): Pic

3. Also if possible can I find the slope of two lines (notice I am recalling the data from an xls file)

the date are here here:

Thanks, appreciate your help.

Answer 1

To find the slope of a curve you can use numpy.polyfit()

If you want the line to fit the first part of your Stress/Strain graph i suggest you to do something like this:

z = np.polyfit(S_S['Strain'][0:5], S_S['Stress'][0:5], 1)

If you want to plot this line you can do the following

x= Strain_Al plt.plot(z[0]*x+z[1],'--')

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
plt.style.use('seaborn-bright')
print(plt.style.available)
print("NumPy version:", np.__version__)
print("Pandas version:", pd.__version__)
S_S = pd.read_excel("SSCurve.xls")
print(S_S.head())
Stress_Al = S_S['STRESS']
Strain_Al = S_S['STRAIN']
z = np.polyfit(S_S['Strain'][0:5], S_S['Stress'][0:5], 1)
z[1] = -1
plt.scatter(Strain_Al, Stress_Al)
plt.plot(Strain_Al, Stress_Al)
plt.xlabel('Strain')
plt.ylabel('Stress (MPa)')
plt.title('Engineering Stress Vs Engineering Strain')
plt.ylim(0,7)
x= Strain_Al
plt.plot(z[0]*x+z[1],'--')
plt.tight_layout()
plt.show()

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