Traceback (most recent call last): File "F:\pythonProject2\arima.py", line 12, in <module> model = SARIMAX(data, order=(1, 1, 1), seasonal_order=(1, 1, 1, 12)) File "F:\Users\anaconda3\lib\site-packages\statsmodels\tsa\statespace\sarimax.py", line 328, in __init__ self._spec = SARIMAXSpecification( File "F:\Users\anaconda3\lib\site-packages\statsmodels\tsa\arima\specification.py", line 446, in __init__ self._model = TimeSeriesModel(endog, exog=exog, dates=dates, freq=freq, File "F:\Users\anaconda3\lib\site-packages\statsmodels\tsa\base\tsa_model.py", line 411, in __init__ super(TimeSeriesModel, self).__init__(endog, exog, missing=missing, File "F:\Users\anaconda3\lib\site-packages\statsmodels\base\model.py", line 237, in __init__ super(LikelihoodModel, self).__init__(endog, exog, **kwargs) File "F:\Users\anaconda3\lib\site-packages\statsmodels\base\model.py", line 77, in __init__ self.data = self._handle_data(endog, exog, missing, hasconst, File "F:\Users\anaconda3\lib\site-packages\statsmodels\base\model.py", line 101, in _handle_data data = handle_data(endog, exog, missing, hasconst, **kwargs) File "F:\Users\anaconda3\lib\site-packages\statsmodels\base\data.py", line 672, in handle_data return klass(endog, exog=exog, missing=missing, hasconst=hasconst, File "F:\Users\anaconda3\lib\site-packages\statsmodels\base\data.py", line 83, in __init__ self.endog, self.exog = self._convert_endog_exog(endog, exog) File "F:\Users\anaconda3\lib\site-packages\statsmodels\base\data.py", line 508, in _convert_endog_exog raise ValueError("Pandas data cast to numpy dtype of object. " ValueError: Pandas data cast to numpy dtype of object. Check input data with np.asarray(data).
时间: 2023-06-30 18:05:04 浏览: 140
linux 下 pip3 报错“ File “/usr/bin/pip3”, line 9, in from pip import mainImportError: canno”处理
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这个错误通常是因为 Pandas 数据中包含字符串或缺失值等非数值类型,导致数据类型被转换为 object 类型。建议检查输入数据中是否有这类非数值类型的数据,并尝试使用 np.asarray() 将数据转换为数值类型。你可以尝试以下代码:
```python
import numpy as np
import pandas as pd
from statsmodels.tsa.statespace.sarimax import SARIMAX
# 读取数据
data = pd.read_csv('your_data.csv')
# 转换数据类型为 float
data = np.asarray(data['column_name'], dtype=np.float32)
# 拟合 SARIMAX 模型
model = SARIMAX(data, order=(1, 1, 1), seasonal_order=(1, 1, 1, 12))
result = model.fit()
```
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