The csv file "house$\_$price.csv$"$ contains the basic information about houses.

Read the data from the csv file "house$\_$price.csv$",$ and create a dataframe object.

Plot the histogram chart and the density chart of the distribution of bedrooms $($i$.$e$.$ the column "bedrooms"$).$

Plot the scatter chart of the relationship between the column $"$sqft$\_$living" and the column "price".

Plot the bar chart of the average selling price $($i$.$e$.$ the column "price"$)$ of houses in different cities $($i$.$e$.$ the column "city"$)$ and also compute the standard deviation.

Plot the box chart of the selling price $($i$.$e$.$ the column "price"$)$ of houses in different cities $($i$.$e$.$ the column "city"$).$

In $[2]$:

import pandas as pd

import matplotlib. pyplot as plt

import seaborn as sns

In $[9]$:

#$1$ Read the data

#file ruth

path$=\text{'}$ house$\_$price. csv$\text{'}$

In $[14]$

df $=$ pd$.$ read$\_$csv $($path$)$

df

Out $[14]$ :

$\backslash$table$[[,$date,price,bedrooms,bathrooms,sqft$\_$living,sqft$\_$lot,floors,waterfront,view,condition,sqft$\_$above,sqft$\_$basement,yr$\_$built,yr$\_$renovated$],[0,\backslash$table$[[2014-$