Python 3.x 如何找到回归线与OY轴相交的点？

我有一个文件，其中提供了一些数据，x和y值。我的程序画了这些点的回归线，但我现在需要的是找到OY轴上的值，如果我的线被拉长，它将与OY轴相交

我只需要把这条线加长，与OY轴相交，然后找到该点的精确坐标

到目前为止，我的代码是：

import numpy as np

import matplotlib.pyplot as plt  # To visualize

import pandas as pd  # To read data

from sklearn.linear_model import LinearRegression
data = pd.read_csv('data.csv')  # load data set

X = data.iloc[:, 0].values.reshape(-1, 1)  # values converts it into a numpy array

Y = data.iloc[:, 1].values.reshape(-1, 1)  # -1 means that calculate the dimension of rows, but have 1 column

linear_regressor = LinearRegression()  # create object for the class

linear_regressor.fit(X, Y)  # perform linear regression

Y_pred = linear_regressor.predict(X)  # make predictions

plt.scatter(X, Y)

plt.plot(X, Y_pred, color='red')

plt.show()

我的代码需要一个名为“data.csv”的文件，其中包含给定值的坐标。我的示例具有以下价值：

5,0.8
10,0.7
15,0.66
20,0.493
25,0.5
30,0.21

---

您想要这样的东西吗？在这里，您可以使用LinearRegressor对象的

intercept\uu

属性来获得x处的y截距等于零：

import numpy as np
import matplotlib.pyplot as plt  # To visualize
import pandas as pd  # To read data
from io import StringIO
from sklearn.linear_model import LinearRegression
txtfile = StringIO("""5,0.8
10,0.7
15,0.66
20,0.493
25,0.5
30,0.21""")
data = pd.read_csv(txtfile, header=None)  # load data set

X = data.iloc[:, 0].values.reshape(-1, 1)  # values converts it into a numpy array

Y = data.iloc[:, 1].values.reshape(-1, 1)  # -1 means that calculate the dimension of rows, but have 1 column

linear_regressor = LinearRegression()  # create object for the class

linear_regressor.fit(X, Y)  # perform linear regression

Y_pred = linear_regressor.predict(X)  # make predictions

plt.scatter(X, Y)

plt.plot(X, Y_pred, color='red')

plt.plot([0, X[0]], [linear_regressor.intercept_, Y_pred[0]], c="green",  linestyle='--')

ax = plt.gcf().gca()
ax.spines['left'].set_position('zero')
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)

plt.show()

输出：