Traceback (most recent call last): File "D:\kelly\PycharmProjects\pythonProject8\大作业.py", line 145, in <module> model = smf.ols('ExRet ~ PEL1', data=datafit[['ExRet', 'PEL1']].iloc[:(n_in+i),:]) File "D:\python3.10\lib\site-packages\statsmodels\base\model.py", line 226, in from_formula mod = cls(endog, exog, *args, **kwargs) File "D:\python3.10\lib\site-packages\statsmodels\regression\linear_model.py", line 906, in __init__ super(OLS, self).__init__(endog, exog, missing=missing, File "D:\python3.10\lib\site-packages\statsmodels\regression\linear_model.py", line 733, in __init__ super(WLS, self).__init__(endog, exog, missing=missing, File "D:\python3.10\lib\site-packages\statsmodels\regression\linear_model.py", line 190, in __init__ super(RegressionModel, self).__init__(endog, exog, **kwargs) File "D:\python3.10\lib\site-packages\statsmodels\base\model.py", line 267, in __init__ super().__init__(endog, exog, **kwargs) File "D:\python3.10\lib\site-packages\statsmodels\base\model.py", line 92, in __init__ self.data = self._handle_data(endog, exog, missing, hasconst, File "D:\python3.10\lib\site-packages\statsmodels\base\model.py", line 132, in _handle_data data = handle_data(endog, exog, missing, hasconst, **kwargs) File "D:\python3.10\lib\site-packages\statsmodels\base\data.py", line 700, in handle_data return klass(endog, exog=exog, missing=missing, hasconst=hasconst, File "D:\python3.10\lib\site-packages\statsmodels\base\data.py", line 88, in __init__ self._handle_constant(hasconst) File "D:\python3.10\lib\site-packages\statsmodels\base\data.py", line 132, in _handle_constant exog_max = np.max(self.exog, axis=0) File "<__array_function__ internals>", line 180, in amax File "D:\python3.10\lib\site-packages\numpy\core\fromnumeric.py", line 2793, in amax return _wrapreduction(a, np.maximum, 'max', axis, None, out, File "D:\python3.10\lib\site-packages\numpy\core\fromnumeric.py", line 86, in _wrapreduction return ufunc.reduce(obj, axis, dtype, out, **passkwargs) ValueError: zero-size array to reduction operation maximum which has no identity报错如何四u该
时间: 2023-07-21 12:53:22 浏览: 63
根据报错信息,很可能是因为数据集中的某些列中没有数据,导致使用`np.max()`函数时出现了"zero-size array"的错误。可以在使用`np.max()`函数之前先检查数据集中是否存在空值或缺失值,或者可以使用`np.nanmax()`函数来处理数据,该函数可以忽略缺失值并返回最大值。同时,也可以检查一下数据的维度是否符合要求。如果无法解决问题,可以将报错信息和相关代码提供给更有经验的人士进行调试。
相关问题
Traceback (most recent call last): File "D:\kelly\PycharmProjects\pythonProject8\大作业.py", line 39, in <module> ar = sm.tsa.AR(data[col]) File "D:\python3.10\lib\site-packages\statsmodels\tsa\ar_model.py", line 822, in __init__ raise NotImplementedError( NotImplementedError: AR has been removed from statsmodels and replaced with statsmodels.tsa.ar_model.AutoReg.上述代码出现报错
这个错误提示说明您使用的版本的`statsmodels`库已经不再支持使用`AR`方法,而应该使用`AutoReg`方法。您需要将代码中的`AR`替换为`AutoReg`。
以下是示例代码:
```python
import pandas as pd
from scipy.stats import skew, kurtosis
import statsmodels.api as sm
# 读取数据
data = pd.read_csv('data.csv')
# 将非数值类型的值替换为NaN
data = data.apply(pd.to_numeric, errors='coerce')
# 计算均值、标准差、最大值、最小值等统计信息
stats = data.describe()
# 计算偏度和峰度
stats.loc['skew'] = skew(data)
stats.loc['kurt'] = kurtosis(data)
# 计算AR系数
ar_coeffs = []
for col in data.columns:
ar = sm.tsa.AutoReg(data[col], lags=1, trend='c')
ar_model = ar.fit(ic='aic')
ar_coeffs.append(ar_model.params[1])
# 将AR系数添加到统计信息中
stats.loc['AR'] = ar_coeffs
# 打印统计信息
print(stats)
```
在这个示例代码中,我们将`AR`方法替换为`AutoReg`方法,并且使用`lags`参数指定滞后阶数,使用`trend`参数指定是否包含截距。同时,我们也将`ic`参数移动到了`fit()`方法中。
Traceback (most recent call last): File "D:\kelly\PycharmProjects\pythonProject8\大作业.py", line 37, in <module> stats.set_option('display.max_columns', None) File "D:\python3.10\lib\site-packages\pandas\core\generic.py", line 5902, in __getattr__ return object.__getattribute__(self, name) AttributeError: 'DataFrame' object has no attribute 'set_option'报错怎么修改
这个报错是因为DataFrame没有set_option方法。set_option是pandas的顶层函数。所以你可以将代码修改为:
```python
import pandas as pd
pd.set_option('display.max_columns', None)
```
这样就可以正确设置pandas的显示选项了。