D:\Program Files\anaconda3\lib\site-packages\statsmodels\tsa\base\tsa_model.py:7: FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead. from pandas import (to_datetime, Int64Index, DatetimeIndex, Period, D:\Program Files\anaconda3\lib\site-packages\statsmodels\tsa\base\tsa_model.py:7: FutureWarning: pandas.Float64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead. from pandas import (to_datetime, Int64Index, DatetimeIndex, Period,
时间: 2023-09-03 09:08:58 浏览: 220
这是一个 FutureWarning 的警告信息,意味着在未来的版本中,pandas 库将移除 pandas.Int64Index 和 pandas.Float64Index。建议使用适当的 dtype,使用 pandas.Index 替代它们。这个警告信息出现在 statsmodels.tsa.base.tsa_model 模块中的 tsa_model.py 文件中的第7行。它在引入一些模块时使用了过时的索引类型。你可以考虑更新你的代码,使用 pandas.Index 来替代这些过时的索引类型,以避免未来版本中的问题。
相关问题
Traceback (most recent call last): File "F:\pythonproject\ARIMA-GRACH\3.py", line 26, in <module> arima_model = ARIMA(train_data, order=(10, 1, 0)) File "E:\anaconda\lib\site-packages\statsmodels\tsa\arima_model.py", line 45, in __init__ super().__init__(*args, **kwargs) File "E:\anaconda\lib\site-packages\statsmodels\tsa\arima_model.py", line 29, in __init__ raise NotImplementedError(ARIMA_DEPRECATION_ERROR) NotImplementedError: statsmodels.tsa.arima_model.ARMA and statsmodels.tsa.arima_model.ARIMA have been removed in favor of statsmodels.tsa.arima.model.ARIMA (note the . between arima and model) and statsmodels.tsa.SARIMAX. statsmodels.tsa.arima.model.ARIMA makes use of the statespace framework and is both well tested and maintained. It also offers alternative specialized parameter estimators.
这个错误是因为你使用了一个已经被弃用的 statsmodels.tsa.arima_model.ARIMA 模型,应该使用新的 statsmodels.tsa.arima.model.ARIMA 模型。你需要更新你的代码来使用新的模型。
具体来说,你需要从 statsmodels.tsa.arima.model 导入 ARIMA,然后创建一个 ARIMA 模型对象,指定 order 参数。示例代码如下:
```python
from statsmodels.tsa.arima.model import ARIMA
arima_model = ARIMA(train_data, order=(10, 1, 0))
```
这应该可以解决你的问题。
E:\anaconda\lib\site-packages\statsmodels\tsa\base\tsa_model.py:471: ValueWarning: A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting. self._init_dates(dates, freq) E:\anaconda\lib\site-packages\statsmodels\tsa\base\tsa_model.py:471: ValueWarning: A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting. self._init_dates(dates, freq) E:\anaconda\lib\site-packages\statsmodels\tsa\base\tsa_model.py:471: ValueWarning: A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting. self._init_dates(dates, freq)
这是一个ValueWarning警告,意味着你提供了一个日期索引,但没有指定与之相关的频率信息。这在预测时会被忽略。你可以通过设置正确的频率信息来解决这个问题,例如:
```python
import pandas as pd
from statsmodels.tsa.arima_model import ARIMA
# 读取数据并设置日期索引
data = pd.read_csv('data.csv', index_col='date', parse_dates=True)
# 设置正确的频率信息
data.index.freq = 'D'
# 拟合ARIMA模型
model = ARIMA(data, order=(1, 1, 1))
results = model.fit()
# 进行预测
forecast = results.forecast(steps=7)
```
这里将日期索引的频率设置为“D”表示每天,你可以根据你的数据集设置不同的频率信息。
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