TypeError: 'numpy.float64' object cannot be interpreted as an integer

Question

I am trying to run the detect_ts function from pyculiarity package but getting this error on passing a two-dimensional dataframe in python.

>>> 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

I'd review the docs for detect_ts. Make sure the inputs are the right type(s). data.values extracts an array from data. The other approach is to work from the end, deducing what head, x, and tail are. [np.nan]*np.float64(2) produces your error. — hpaulj
– hpaulj, Commented Feb 17, 2017 at 6:31
The same error occured to me... When I enabled the folder path for accessing the data. (For eg: G folder/Shared link) The error got rectified because link to access data was activated. — Abhishek
– Abhishek, Commented May 10, 2017 at 7:47

Sayan Sil · Accepted Answer · 2017-09-19 19:49:20Z

1

The problem with your code might be that np.nan is a float64 type value but the np.r_[] expects comma separated integers within its square brackets. Hence you need to convert them to integer type first.

But we have another problem here.

return np.r_[[(int)(np.nan)] * head, x, [(int)(np.nan)] * tail]

This should have solved the problem in ordinary cases.... But it wont work in this case, as NaN cannot be type casted to integer type.

ValueError: cannot convert float NaN to integer

Thus, no proper solution can be suggested unless we know what you are trying to do here. Try providing a bit more details about your code and you are sure to get help from us.

:-)

answered Sep 19, 2017 at 19:49

Sayan Sil

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