I have a data frame which contains multivariate time series data. It has columns: fundId (each entity), periodId(time stamp), v1, v2, v3 ...
I want to extract features from those times series for each fund over time. Like: fundId v1.max, v1.min, v1.median, ..., v2.max, v2.min, v2.median, ...
I encountered an AttributeError when use function extract_features from library tsfresh. I'm new to Python but I think it might related to multiprocessing.
The trackback shows:
Traceback (most recent call last): File "mypath\lib\site-packages\IPython\core\interactiveshell.py", line 3325, in run_code exec(code_obj, self.user_global_ns, self.user_ns) File "", line 1, in HFeatures = extract_features(FundCharc, column_id='fundId', column_sort='periodId')
File "mypath\lib\site-packages\tsfresh\feature_extraction\extraction.py", line 178, in extract_features distributor=distributor)
File "mypath\lib\site-packages\tsfresh\feature_extraction\extraction.py", line 313, in _do_extraction progressbar_title="Feature Extraction")
File "mypath\lib\site-packages\tsfresh\utilities\distribution.py", line 349, in init self.pool = Pool(processes=n_workers)
File "C:\ProgramData\Miniconda3\lib\multiprocessing\context.py", line 119, in Pool context=self.get_context())
File "C:\ProgramData\Miniconda3\lib\multiprocessing\pool.py", line 176, in init self._repopulate_pool()
File "C:\ProgramData\Miniconda3\lib\multiprocessing\pool.py", line 241, in _repopulate_pool w.start()
File "C:\ProgramData\Miniconda3\lib\multiprocessing\process.py", line 112, in start self._popen = self._Popen(self)
File "C:\ProgramData\Miniconda3\lib\multiprocessing\context.py", line 322, in _Popen return Popen(process_obj)
File "C:\ProgramData\Miniconda3\lib\multiprocessing\popen_spawn_win32.py", line 33, in init prep_data = spawn.get_preparation_data(process_obj._name)
File "C:\ProgramData\Miniconda3\lib\multiprocessing\spawn.py", line 172, in get_preparation_data main_mod_name = getattr(main_module.spec, "name", None)
AttributeError: module 'main' has no attribute 'spec'
from tsfresh import extract_features
HFeatures = extract_features(FundCharc, column_id='fundId', column_sort='periodId')
