首页ValueError: Input X contains NaN.

ValueError: Input X contains NaN.

时间: 2024-05-27 20:13:47 浏览: 161

python3.7解决最小二乘遇到ValueError:Expected 2D array, got 1D array instead: array=[5.].关于reshape和predict

在用python的LinearRegression做最小二乘时遇到如下错误： ValueError: Expected 2D array, got 1D array instead: array=[5.]. 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. 翻译过来是： ValueError：预期为2D数组，改为获取1D数组：数组= [5.]。如果数据具有单个

This error occurs when the input data contains missing values or NaN (Not a Number) values. These missing values can occur due to a variety of reasons such as data collection errors, data processing errors, or simply missing data. To resolve this error, you can try the following steps: 1. Check your dataset for missing values or NaN values using functions such as isna(), isnull(), or any(). 2. If you find missing values, try imputing them using techniques such as mean imputation, median imputation, or mode imputation. 3. You can also try removing the rows or columns that contain missing values, depending on the amount of missing data and the importance of those rows or columns in your analysis. 4. Another option is to use machine learning algorithms that can handle missing values, such as tree-based models or deep learning models. Overall, it is important to carefully check and handle missing values in your dataset to avoid errors such as this ValueError.

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