我正在尝试从pyculiarity包运行detect_ts函数,但在python中传递二维数据帧时会出现此错误。
>>> import pandas as pd
>>> from pyculiarity import detect_ts
>>> data=pd.read_csv('C:\\Users\\nikhil.chauhan\\Desktop\\Bosch_Frame\\dataset1.csv',usecols=['time','value'])
>>> data.head()
time value
0 0 32.0
1 250 40.5
2 500 40.5
3 750 34.5
4 1000 34.5
>>> results = detect_ts(data,max_anoms=0.05,alpha=0.001,direction = 'both')
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "C:\Windows\System32\pyculiar-0.0.5\pyculiarity\detect_ts.py", line 177, in detect_ts
verbose=verbose)
File "C:\Windows\System32\pyculiar-0.0.5\pyculiarity\detect_anoms.py", line 69, in detect_anoms
decomp = stl(data.value, np=num_obs_per_period)
File "C:\Windows\System32\pyculiar-0.0.5\pyculiarity\stl.py", line 35, in stl
res = sm.tsa.seasonal_decompose(data.values, model='additive', freq=np)
File "C:\Anaconda3\lib\site-packages\statsmodels\tsa\seasonal.py", line 88, in seasonal_decompose
trend = convolution_filter(x, filt)
File "C:\Anaconda3\lib\site-packages\statsmodels\tsa\filters\filtertools.py", line 303, in convolution_filter
result = _pad_nans(result, trim_head, trim_tail)
File "C:\Anaconda3\lib\site-packages\statsmodels\tsa\filters\filtertools.py", line 28, in _pad_nans
return np.r_[[np.nan] * head, x, [np.nan] * tail]
TypeError: 'numpy.float64' object cannot be interpreted as an integer
答案 0 :(得分:0)
您的代码的问题可能是np.nan
是float64
类型值,但np.r_[]
期望以逗号分隔整数在方括号内。
因此,您需要先将它们转换为整数类型。
但我们这里有另一个问题。
return np.r_[[(int)(np.nan)] * head, x, [(int)(np.nan)] * tail]
这应该解决了普通情况下的问题.... 但它在这种情况下不起作用,因为 NaN不能被类型转换为整数类型。
ValueError: cannot convert float NaN to integer
因此,除非我们知道您在这里尝试做什么,否则不能建议适当的解决方案。尝试提供有关您的代码的更多详细信息,您一定会得到我们的帮助。
<强>: - )强>