c-bata / outlier-utils

Utility library for detecting and removing outliers from normally distributed datasets using the Smirnov-Grubbs test.

outlier-utils

Utility library for detecting and removing outliers from normally distributed datasets using the Smirnov-Grubbs test.

Requirements

• Python (version 3.8 or later)
• SciPy
• NumPy

Overview

Both the two-sided and the one-sided version of the test are supported. The former allows extracting outliers from both ends of the dataset, whereas the latter only considers min/max outliers. When running a test, every outlier will be removed until none can be found in the dataset. The output of the test is flexible enough to match several use cases. By default, the outlier-free data will be returned, but the test can also return the outliers themselves or their indices in the original dataset.

Examples

• Two-sided Grubbs test with a Pandas series input

>>> from outliers import smirnov_grubbs as grubbs
>>> import pandas as pd
>>> data = pd.Series([1, 8, 9, 10, 9])
>>> grubbs.test(data, alpha=0.05)
1     8
2     9
3    10
4     9
dtype: int64

• Two-sided Grubbs test with a NumPy array input

>>> import numpy as np
>>> data = np.array([1, 8, 9, 10, 9])
>>> grubbs.test(data, alpha=0.05)
array([ 8,  9, 10,  9])

• One-sided (min) test returning outlier indices

>>> grubbs.min_test_indices([8, 9, 10, 1, 9], alpha=0.05)
[3]

• One-sided (max) tests returning outliers

>>> grubbs.max_test_outliers([8, 9, 10, 1, 9], alpha=0.05)
[]
>>> grubbs.max_test_outliers([8, 9, 10, 50, 9], alpha=0.05)
[50]

License

This software is licensed under the MIT License.

outlier-utils's Issues

build error: is CHANGES.rst missing when installing via pip?

there was no problem when building from the zip

$ 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'

Add other method for removing outliers.

refs https://en.wikipedia.org/wiki/Outlier

G-value miscalculated

In "def test_once(self, data, alpha):" have defined:

$G=value/data.std()$

where "value" is the value to be evaluated minus the mean, given as relative postion of the value in relation of the mean.

$value = abs(data - data.mean()).argmax()$

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:
$data.std()=value/G$
Therefore, NIST use "15.8525" how std, against "14.8287" of outlier-utils.

So, the first equation, it is actually:
$G=value/data.std(ddof=1)$

KeyError: 0 when running example

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