text_html_output_1.png
import matplotlib.pyplot as plt   #visualisation

import pandas as pd

import seaborn as sns

data = pd.read_csv('/kaggle/input/housesalesprediction/kc_house_data.csv')

data.shape

data.dtypes

data.drop(['id', 'date', 'lat', 'long'], axis=1, inplace=True)

column_names = ['bedrooms', 'bathrooms', 'sqft_living', 'sqft_lot', 'floors', 'waterfront', 'view', 'condition', 'grade', 'sqft_above', 'sqft_basement', 'yr_built', 'yr_renovated', 'sqft_living15', 'sqft_lot15']
for column in column_names:
    plt.figure(figsize=(17, 3))
    sns.boxplot(data=data, x=column)