Traceback (most recent call last): File "D:\pythonProject3.10\lib\site-packages\pandas\core\indexes\base.py", line 3652, in get_loc return self._engine.get_loc(casted_key) File "pandas\_libs\index.pyx", line 147, in pandas._libs.index.IndexEngine.get_loc File "pandas\_libs\index.pyx", line 176, in pandas._libs.index.IndexEngine.get_loc File "pandas\_libs\hashtable_class_helper.pxi", line 7080, in pandas._libs.hashtable.PyObjectHashTable.get_item File "pandas\_libs\hashtable_class_helper.pxi", line 7088, in pandas._libs.hashtable.PyObjectHashTable.get_item KeyError: 0 The above exception was the direct cause of the following exception: Traceback (most recent call last): File "D:\PycharmProjects\数学建模\er.4.py", line 33, in <module> print(liebiao(6002000206)) File "D:\PycharmProjects\数学建模\er.4.py", line 16, in liebiao for i, row in df.loc[df[0] == a].iterrows(): File "D:\pythonProject3.10\lib\site-packages\pandas\core\frame.py", line 3761, in __getitem__ indexer = self.columns.get_loc(key) File "D:\pythonProject3.10\lib\site-packages\pandas\core\indexes\base.py", line 3654, in get_loc raise KeyError(key) from err KeyError: 0

这是一个 Python 的错误信息，看起来是在使用 Pandas 库时出现了问题。具体来说，代码中使用了 DataFrame 的 loc 方法，但是传入的参数出现了问题，导致无法找到对应的行。错误信息提示说 KeyError: 0，即在 DataFrame 中没有名为 0 的列或索引。建议检查代码中对 DataFrame 的操作，确认索引或列名是否正确。

相关问题

Traceback (most recent call last): File "D:\kelly\PycharmProjects\pythonProject8\收益率预测.py", line 119, in <module> n_out = np.sum(datafit['yearmonth'] > 20090101) File "D:\python3.10\lib\site-packages\pandas\core\frame.py", line 3807, in __getitem__ indexer = self.columns.get_loc(key) File "D:\python3.10\lib\site-packages\pandas\core\indexes\base.py", line 3804, in get_loc raise KeyError(key) from err KeyError: 'yearmonth'

这个错误的原因是你尝试在一个 pandas DataFrame 中访问不存在的列 'yearmonth'。'yearmonth' 列可能不存在于该 DataFrame 中，或者你错误地拼写了该列的名称。

你可以先检查 DataFrame 中是否存在 'yearmonth' 列，可以通过打印 DataFrame 的列名列表来检查：

print(datafit.columns)

或者可以通过使用 `in` 操作符来判断该列是否存在于 DataFrame 中：

if 'yearmonth' in datafit.columns:
    n_out = np.sum(datafit['yearmonth'] > 20090101)
else:
    print("Column 'yearmonth' does not exist in DataFrame.")

如果该列确实不存在，你需要检查代码中的数据源是否正确，并确保列名拼写正确。

Traceback (most recent call last): File "E:\anaconda\lib\site-packages\pandas\core\indexes\range.py", line 385, in get_loc return self._range.index(new_key) ValueError: 0 is not in range The above exception was the direct cause of the following exception: Traceback (most recent call last): File "F:\pythonproject\ARIMA-GRACH\6.py", line 34, in <module> arima_pred = arima_result.forecast()[0][0] File "E:\anaconda\lib\site-packages\pandas\core\series.py", line 958, in __getitem__ return self._get_value(key) File "E:\anaconda\lib\site-packages\pandas\core\series.py", line 1069, in _get_value loc = self.index.get_loc(label) File "E:\anaconda\lib\site-packages\pandas\core\indexes\range.py", line 387, in get_loc raise KeyError(key) from err KeyError: 0

这个错误是由于 `test_ts` 的索引从0开始，而 `pd.Series([test_ts[i]], index=[test_ts.index[i]-1])` 中的 `index` 参数是从-1开始的，导致索引对不上。你可以将 `index` 参数修改为从0开始的，如下所示：

arima_result = arima_result.append(pd.Series([test_ts[i]], index=[test_ts.index[i]]))
garch_result = garch_result.append(pd.Series([arima_result.resid[-1]], index=[test_ts.index[i]]))

另外，如果你想要使用 ARIMA-GARCH 模型对时间序列进行预测，你还需要实现 GARCH 模型部分的代码。具体实现方式可以参考下面的代码：

from arch import arch_model

# 训练 GARCH 模型
garch_model = arch_model(train_ts, p=1, q=1)
garch_result = garch_model.fit(update_freq=5).forecast(horizon=len(test_ts), reindex=False)

arima_model = ARIMA(train_ts, order=(1, 1, 1))
arima_result = arima_model.fit()
pred_ts = []
for i in range(len(test_ts)):
    # 预测ARIMA模型的下一个值
    arima_pred = arima_result.forecast()[0][0]
    # 使用GARCH模型计算方差
    var = garch_result.forecast(horizon=1).variance.iloc[-1, 0]
    # 计算标准差
    std = np.sqrt(var)
    # 计算置信区间
    conf_int = (arima_pred - 1.96 * std, arima_pred + 1.96 * std)
    # 将预测结果添加到列表中
    pred_ts.append(arima_pred)
    # 将预测结果添加到模型中
    arima_result = arima_result.append(pd.Series([test_ts[i]], index=[test_ts.index[i]]))
    garch_result = garch_result.append(pd.Series([arima_result.resid[-1]], index=[test_ts.index[i]]))