analyzing a messy dataset

import numpy as np

import pandas as pd

import matplotlib.pyplot as plt

import seaborn as sns

Reading in the data

Set the variable sales$\_$df to a Pandas DataFrame from the Real$\_$Estate$\_$Sales$\_2001-2020\_$GL$.$csv file and display the first $5$ rows.

Note: This is a fairly large dataset, so when you call the function to read in the file, add the argument low$\_$memory$=$False.

sales$\_$df $=$

sales$\_$df$.$head$()$

Cleaning up the data

For our analysis, we will want to do a breakdown of real estate sales by year of sale, town, assessed value, sale amount, and property type.

Removing all the unnecessary columns from sales$\_$df$.$ Hint: we are interested in year of sale, not the year the property was listed.

Change the dtypes for Assessed Value and Sale Amount to int.

sales$\_$df$.$head$()$

Display how many values in each column are NaN. This does not need to be saved as a variable. Hint: a function that results in a boolean can be chained with the sum$()$ function to get a count.

We need to extract the year the property was sold.

Remove any row with a NaN.

Set the variable year$\_$sold to a list of years $($as integers$)$ extracted from the Date Recorded column.

Add a new column named Year Sold for those data.

sales$\_$df$.$head$()$

Let's get an overview of the Sale Amount data. Use the Seaborn package to create a scatter plot of Sale Amount as a function of Year Sold.

plt$.$show$()$

The data appear squashed because of an outlier. Display the outliers by returning rows from sales$\_$df that have Sale Amount values greater than $1$e$9.$ You do not need to save this as a new variable

Let's remove the outlier and then calculate the average property sale price by year since the housing market crash in $2008.$

Remove the outlier from sales$\_$df$.$

Set a new variable means$\_$df to a DataFrame containing the mean sale and assessment values by year.

Using Matplotlib, create a single figure with two lineplots:

Grey line plot with circle markers of mean assessment value by year from $2008$ to $2021$

Steelblue line plot with square markers of mean sale price by year from $2008$ to $2021$

Title the graph "Comparison of Average Property Values and Sale Prices from $2008$ to $2021"$

Include x$-$ and y$-$axis labels

Include a legend with labels tht correspond to the column headers