如何避免收集错误 Python Numpy

Question

我正在尝试训练一个线性回归限定符来继续一个 grap。我的 csv 文件中有几千行数据，我将它们导入到 numpy 数组中。这是我的代码：

import pandas as pd 
import numpy as np 
from matplotlib import pyplot as plt 
import csv
import math
from sklearn import preprocessing, svm
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LinearRegression

def predict():
    sample_data = pd.read_csv("includes\csv.csv")
    x = np.array(sample_data["day"])
    y = np.array(sample_data["balance"])

    for x in x:
        x = x.reshape(1, -1)
        #lol

    for y in y:
        y.reshape(1, -1)
        #lol

    X_train, X_test, y_train, y_test = train_test_split(x, y, test_size=0.2)

    clf = LinearRegression()
    clf.fit(x_train, y_train)
    clf.score(x_test, y_test)

当我运行这个的时候，错误是：

TypeError: Singleton array 6014651 cannot be considered a valid collection.

知道为什么会这样吗？

Answer 1

经过评论讨论：

import pandas as pd 
import numpy as np 
from matplotlib import pyplot as plt 
import csv
import math
from sklearn import preprocessing, svm
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LinearRegression

def predict():
    sample_data = pd.read_csv("includes\csv.csv")
    x = np.array(sample_data["day"])
    y = np.array(sample_data["balance"])

    x = x.reshape(-1,1)

    y = y.reshape(-1,1)

    X_train, X_test, y_train, y_test = train_test_split(x, y, test_size=0.2)

    clf = LinearRegression()
    clf.fit(X_train, y_train)
    clf.score(X_test, y_test)

Answer 2

X_train,X_test要大写,python变量区分大小写

如何避免收集错误 Python Numpy

How to avoid Collection Error Python Numpy

python

pandas

scikit-learn

sklearn-pandas