【问题标题】:python pandas: I've got an error that occurs in the line I used drop functionpython pandas:我在使用 drop 函数的行中出现错误
【发布时间】:2020-02-10 05:09:18
【问题描述】:

我开始学习机器学习,我正在跟随 youtube 上的某个人学习它。 这是链接:https://www.youtube.com/watch?v=6g4O5UOH304&t=1684s 所以基本上,和他写的代码是一样的。

import pandas as pd
import numpy as np
import sklearn
from sklearn import linear_model
from sklearn.utils import shuffle

data = pd.read_csv("student-mat.csv", sep=";")

#print(data.head())
data = data[["G1", "G2", "G3", "studytime", "failures", "absences"]]
print(data.head())
predict = "G3"

x = np.array(data.drop([predict]), axis=1)
y = np.array(data[predict])

x_train, x_test, y_train, y_test = sklearn.model_selection.train_test_split(x, y, test_size=0.1)
linear = linear_model.LinearRegression()

linear.fit(x_train, y_train)
acc = linear.score(x_test, y_test)
print(acc)

当我运行这个..

Traceback (most recent call last):
  File "C:/Users/asb46/PycharmProjects/tensorEnv/lec1.py", line 14, in <module>
    x = np.array(data.drop([predict]), axis=1)
  File "C:\Users\asb46\Anaconda3\envs\tensor\lib\site-packages\pandas\core\frame.py", line 3697, in drop
    errors=errors)
  File "C:\Users\asb46\Anaconda3\envs\tensor\lib\site-packages\pandas\core\generic.py", line 3111, in drop
    obj = obj._drop_axis(labels, axis, level=level, errors=errors)
  File "C:\Users\asb46\Anaconda3\envs\tensor\lib\site-packages\pandas\core\generic.py", line 3143, in _drop_axis
    new_axis = axis.drop(labels, errors=errors)
  File "C:\Users\asb46\Anaconda3\envs\tensor\lib\site-packages\pandas\core\indexes\base.py", line 4404, in drop
    '{} not found in axis'.format(labels[mask]))
KeyError: "['G3'] not found in axis"

我正在使用熊猫:0.23.4 版本。我尝试降级,但仍然出现错误...我不知道 我的代码的正确版本是什么。

【问题讨论】:

  • x = np.array(data.drop([predict], axis=1))?

标签: python pandas tensorflow


【解决方案1】:

对代码稍作改动即可解决此问题。

代替

x = np.array(data.drop([predict]), axis=1)

x = np.array(data.drop([predict], axis=1))

说明:axis 是 drop 方法的参数,而不是 np.array 的参数

【讨论】:

    猜你喜欢
    • 2017-09-13
    • 1970-01-01
    • 2022-12-11
    • 2013-06-30
    • 2017-01-05
    • 1970-01-01
    • 2021-08-05
    • 1970-01-01
    • 1970-01-01
    相关资源
    最近更新 更多