预期的二维数组，在 pandas 回归中得到标量数组而不是错误

Question

我尝试计算 pandas 中的回归时出现错误。这是代码：

import pandas as pd
import matplotlib.pyplot as plt

df=pd.DataFrame({"haftalar":[1,2,3,4,5,6,7],
                 "degerler":[6.11,5.66,5.30,5.32,5.25,5.37,5.28]})
haftalar=df[['haftalar']]
degerler=df[['degerler']]

from sklearn.model_selection import train_test_split
x_train, x_test, y_train, y_test = train_test_split(
    haftalar, degerler, test_size=0.57, random_state=0) 

from sklearn.linear_model import LinearRegression

lr=LinearRegression()

lr.fit(x_train,y_train)
tahmin=lr.predict(8)
print(tahmin)

当我尝试运行代码时，出现以下错误：

"if it contains a single sample.".format(array))

ValueError: Expected 2D array, got scalar array instead:
array=8.
Reshape your data either using array.reshape(-1, 1) 
if your data has a single feature or array.reshape(1, -1)
if it contains a single sample.

我将在 3 小时后参加该科目的考试。你能帮帮我吗？

Answer 1

尝试：

tahmin=lr.predict([[8]])

更常见的是，您可能在 numpy 数组中有数据，如下所示：

import numpy as np
x_test = np.array([8])

现在错误消息会告诉您该怎么做：

tahmin=lr.predict(x_test.reshape(-1, 1))

预期的二维数组，在 pandas 回归中得到标量数组而不是错误

Expected 2D array, got scalar array instead error in pandas regression

python

python-3.x

pandas

scikit-learn

sklearn-pandas