pandas 如何将训练和测试数据集拆分为 X_Train y_train 和 X_Test y_Test？
声明：本页面是StackOverFlow热门问题的中英对照翻译，遵循CC BY-SA 4.0协议，如果您需要使用它，必须同样遵循CC BY-SA许可，注明原文地址和作者信息，同时你必须将它归于原作者（不是我）：StackOverFlow
原文地址: http://stackoverflow.com/questions/47321709/
Warning: these are provided under cc-by-sa 4.0 license. You are free to use/share it, But you must attribute it to the original authors (not me):
StackOverFlow
How to split train and test dataset to X_Train y_train and X_Test y_Test?
提问by Gaurav Singh
So I successfully split my dataset into Train & Test in a ratio of 70:30 I used this:
所以我成功地将我的数据集以 70:30 的比例拆分为训练和测试，我使用了这个：
df_glass['split'] = np.random.randn(df_glass.shape[0], 1)
msk = np.random.rand(len(df_glass)) <= 0.7
train = df_glass[msk]
test = df_glass[~msk]
print(train)
print(test)
Now how do I split train and test to X_trainand y_trainand X_testand y_testSuch that, Xdenotes the features of the database and y denotes the response?
现在我如何将训练和测试拆分为X_trainandy_train和X_testandy_test这样的，X表示数据库的特征，y 表示响应？
I need to do supervised learning and apply ML modules on X_Trainand y_Train.
我需要进行监督学习并在X_Train和上应用 ML 模块y_Train。
My database looks like this: Database_snippet
我的数据库如下所示： Database_snippet
回答by Vivek Kalyanarangan
Scikit-Learn has a convenience method for splitting pandas dataframes -
Scikit-Learn 有一个方便的方法来拆分 Pandas 数据帧 -
This will do the split -
这将进行拆分 -
from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(df[list_of_X_cols], df['y'], test_size=0.33, random_state=42)
回答by Ariful Shuvo
i guess you may found this useful to understand..
我想你可能会发现这对理解很有用..
import pandas as pd
from sklearn.cross_validation import train_test_split
from sklearn.linear_model import LinearRegression
#importing dataset
dataset = pd.read_csv('Salary_Data.csv')
x = dataset.iloc[:, :-1].values
y = dataset.iloc[:, 1].values
#spliting the dataset into training and test set
x_train, x_test, y_train, y_test = train_test_split(x, y,
test_size=1/3, random_state=0)
