How to find outliers in Python?
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# How to find outliers in Python?

This recipe helps you find outliers in Python

0
In [2]:
```## How to find outliers in Python
def Kickstarter_Example_30():
print()
print(format('How to find outliers in Python', '*^82'))

import warnings
warnings.filterwarnings("ignore")

from sklearn.covariance import EllipticEnvelope
from sklearn.datasets import make_blobs
import matplotlib.pyplot as plt

# Create simulated data
X, _ = make_blobs(n_samples = 100,
n_features = 20,
centers = 7,
cluster_std = 1.1,
shuffle = True,
random_state = 42)

# Detect Outliers
# Create detector
outlier_detector = EllipticEnvelope(contamination=.1)

# Fit detector
outlier_detector.fit(X)

# Predict outliers
print(); print(X)
print(); print(outlier_detector.predict(X))
plt.scatter(X[:,0], X[:,1])

# Show the scatterplot
plt.show()

Kickstarter_Example_30()
```
```**************************How to find outliers in Python**************************

[[ 4.93252797  7.68541287 -3.97876821 ...  4.52684633 -3.24863123
9.41974416]
[-9.3234536   4.59276437 -4.39779468 ... -7.09597087  8.20227193
2.26134033]
[-8.7338198   3.08658417 -3.49905765 ... -6.82385124  8.775862
1.38825176]
...
[-2.83969517 -6.07980264  6.47763993 ... -9.36607752 -2.57352093
-9.39410402]
[-2.1671993  10.63717797  5.58330442 ...  0.50898027 -1.25365592
-5.02572796]
[ 7.21074034  9.28156979 -3.54240715 ...  3.89782083 -3.2259812
11.03335594]]

[-1  1  1  1  1  1  1  1  1  1  1  1  1  1  1  1  1  1  1 -1  1  1  1 -1
1  1  1  1  1  1  1  1  1  1  1  1  1  1  1  1 -1 -1 -1  1  1  1  1  1
1  1  1  1  1  1  1  1  1  1  1  1  1  1 -1  1  1  1  1  1  1  1  1  1
1  1  1  1  1  1  1  1  1  1  1  1  1  1  1 -1  1  1 -1  1  1  1  1  1
1  1  1 -1]
```

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