A Function to check if a field has any outliers using IQR

IQR_OutliersFunc.py

import pandas as pd
import numpy as np


def is_outlier(value, p25, p75):
    """Check if value is an outlier
    """
    lower = p25 - 1.5 * (p75 - p25)
    upper = p75 + 1.5 * (p75 - p25)
    return value <= lower or value >= upper

def get_indices_of_outliers(values):
    """Get outlier indices (if any)
    """
    p25 = values.quantile(.25)
    p75 = values.quantile(.75)
    lower = p25 - 1.5 * (p75 - p25)
    upper = p75 + 1.5 * (p75 - p25)

    indices_of_outliers = []
    for ind, value in enumerate(values):
        if is_outlier(value, p25, p75):
            indices_of_outliers.append(ind)
    return indices_of_outliers

def IQR_outliers(dataframe, field):
    indices_of_outliers = get_indices_of_outliers(df[field])
    outlier = dataframe[field][indices_of_outliers]
    dataframe.loc[dataframe[field].index.isin(outlier.index) == True, 
                  field + '_outlier'] = 'Outlier'
    dataframe.loc[dataframe[field].index.isin(outlier.index) == False, 
                  field + '_outlier'] = 'Not Outlier'
    return dataframe

if __name__ == "__main__":
    df = pd.DataFrame(np.random.uniform(0, 100, size=(100, 3)))
    df.columns = ['A', 'B', 'C']
    print(IQR_outliers(df, 'C'))