Remove outliers in pandas

rem_outlier.py

import pandas as pd
import numpy as np

from pandas.api.types import is_numeric_dtype

np.random.seed(42)
age = np.random.randint(20,100,50)
name = ['name'+str(i) for i in range(50)]
address = ['address'+str(i) for i in range(50)]

df = pd.DataFrame(data={'age':age, 'name':name, 'address':address})

def remove_outlier(df):
    low = .05
    high = .95
    quant_df = df.quantile([low, high])
    for name in list(df.columns):
        if is_numeric_dtype(df[name]):
            df = df[(df[name] > quant_df.loc[low, name]) & (df[name] < quant_df.loc[high, name])]
    return df

remove_outlier(df).head()