Utility library for detecting and removing outliers from normally distributed datasets using the Smirnov-Grubbs test.
Home Page: https://pypi.python.org/pypi/outlier-utils
License: MIT License
$ sudo -H pip install outlier-utils
Collecting outlier-utils
Using cached outlier_utils-0.0.2.tar.gz
Complete output from command python setup.py egg_info:
Traceback (most recent call last):
File "", line 1, in
File "/private/tmp/pip-build-gmoeex/outlier-utils/setup.py", line 8, in
CHANGES = open(os.path.join(BASE_PATH, 'CHANGES.rst')).read()
IOError: [Errno 2] No such file or directory: '/private/tmp/pip-build-gmoeex/outlier-utils/CHANGES.rst'
In "def test_once(self, data, alpha):" have defined:
where "value" is the value to be evaluated minus the mean, given as relative postion of the value in relation of the mean.
This steps is similar with the we can look here, on NIST site. So, to avaluetion this steps, we go work with [199.31, 199.53, 200.19, 200.82, 201.92, 201.95, 202.18, 245.57].
The G-value on outlier-utils is "2.6392", against "2.4687" of NIST site, so....What the problem?
The problem is with the way to calculate std, because as you want to calculate a std from a sample, you must use data.std(ddof=1).
To calculate the std that NIST uses, just do:
Therefore, NIST use "15.8525" how std, against "14.8287" of outlier-utils.
So, the first equation, it is actually:
data = pd.Series([1, 8, 9, 10, 9])
grubbs.test(data, alpha=0.05)
Gives
KeyError Traceback (most recent call last)
<ipython-input-5-1838b39dbcff> in <module>
1 data = pd.Series([1, 8, 9, 10, 9])
----> 2 grubbs.test(data, alpha=0.05)
~\miniconda3\lib\site-packages\outliers\smirnov_grubbs.py in test(data, alpha)
241
242 def test(data, alpha=DEFAULT_ALPHA):
--> 243 return two_sided_test(data, alpha)
~\miniconda3\lib\site-packages\outliers\smirnov_grubbs.py in two_sided_test(data, alpha)
205
206 def two_sided_test(data, alpha=DEFAULT_ALPHA):
--> 207 return _two_sided_test(data, alpha, OutputType.DATA)
208
209
~\miniconda3\lib\site-packages\outliers\smirnov_grubbs.py in _two_sided_test(data, alpha, output_type)
193
194 def _two_sided_test(data, alpha, output_type):
--> 195 return _test(TwoSidedGrubbsTest, data, alpha, output_type)
196
197
~\miniconda3\lib\site-packages\outliers\smirnov_grubbs.py in _test(test_class, data, alpha, output_type)
189
190 def _test(test_class, data, alpha, output_type):
--> 191 return test_class(data).run(alpha, output_type=output_type)
192
193
~\miniconda3\lib\site-packages\outliers\smirnov_grubbs.py in run(self, alpha, output_type)
120
121 while True:
--> 122 outlier_index = self._test_once(data, alpha)
123 if outlier_index is None:
124 break
~\miniconda3\lib\site-packages\outliers\smirnov_grubbs.py in _test_once(self, data, alpha)
101 :return: the index of the outlier if one if found; None otherwise
102 """
--> 103 target_index, value = self._target(data)
104
105 g = value / data.std()
~\miniconda3\lib\site-packages\outliers\smirnov_grubbs.py in _target(self, data)
152 relative_values = abs(data - data.mean())
153 index = relative_values.argmax()
--> 154 value = relative_values[index]
155 return index, value
156
~\miniconda3\lib\site-packages\pandas\core\series.py in __getitem__(self, key)
869 key = com.apply_if_callable(key, self)
870 try:
--> 871 result = self.index.get_value(self, key)
872
873 if not is_scalar(result):
~\miniconda3\lib\site-packages\pandas\core\indexes\base.py in get_value(self, series, key)
4402 k = self._convert_scalar_indexer(k, kind="getitem")
4403 try:
-> 4404 return self._engine.get_value(s, k, tz=getattr(series.dtype, "tz", None))
4405 except KeyError as e1:
4406 if len(self) > 0 and (self.holds_integer() or self.is_boolean()):
pandas\_libs\index.pyx in pandas._libs.index.IndexEngine.get_value()
pandas\_libs\index.pyx in pandas._libs.index.IndexEngine.get_value()
pandas\_libs\index.pyx in pandas._libs.index.IndexEngine.get_loc()
pandas\_libs\hashtable_class_helper.pxi in pandas._libs.hashtable.Int64HashTable.get_item()
pandas\_libs\hashtable_class_helper.pxi in pandas._libs.hashtable.Int64HashTable.get_item()
KeyError: 0
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