Outliers_Percentile.py

#!/usr/bin/env python
# coding: utf-8

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import numpy as np # linear algebra
import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)
import matplotlib.pyplot as plt


Data=pd.read_csv("/Users/khadeejah/Desktop/AB_NYC_2019.csv")
Data.head()


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Data.shape


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Data.describe()


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#Detect the outliers by using percentile
maxthresold=Data['price'].quantile(0.95)
maxthresold


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#remove the outliers
Data[Data['price']>maxthresold]
Data.head()


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#Detect the outliers 
minthresold=Data['price'].quantile(0.05)
minthresold


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#Remove the outliers
Data[Data['price']<minthresold]
Data.head()


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# Data has no outliers
Data_no_outliers=Data[(Data['price']<maxthresold) & (Data['price']>minthresold)]
Data_no_outliers.shape


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Data_no_outliers.describe()


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