ium_z487183/IUM_project.ipynb at 87d38238cc599d7dd6fea7398a859fa97dddcdcd

!pip3 install -q kaggle
!kaggle datasets download amalab182/property-salesmelbourne-city
!mkdir -p data
!unzip -o property-salesmelbourne-city.zip -d data
!rm property-salesmelbourne-city.zip
!ls data

[1m[[0m[34;49mnotice[0m[1;39;49m][0m[39;49m A new release of pip available: [0m[31;49m22.2.1[0m[39;49m -> [0m[32;49m23.0.1[0m
[1m[[0m[34;49mnotice[0m[1;39;49m][0m[39;49m To update, run: [0m[32;49mpip3 install --upgrade pip[0m
Downloading property-salesmelbourne-city.zip to /Users/mmoryl/Projects/UAM/ium_s487183
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Archive:  property-salesmelbourne-city.zip
  inflating: data/Property Sales of Melbourne City.csv  
Property Sales of Melbourne City.csv

!pip3 install pandas
import pandas as pd
sells = pd.read_csv('data/Property Sales of Melbourne City.csv')
sells
# sells["Car Model"].value_counts()
# len(sells.index)

Requirement already satisfied: pandas in /Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages (1.5.3)
Requirement already satisfied: pytz>=2020.1 in /Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages (from pandas) (2023.2)
Requirement already satisfied: python-dateutil>=2.8.1 in /Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages (from pandas) (2.8.2)
Requirement already satisfied: numpy>=1.21.0 in /Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages (from pandas) (1.24.2)
Requirement already satisfied: six>=1.5 in /Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages (from python-dateutil>=2.8.1->pandas) (1.16.0)

[1m[[0m[34;49mnotice[0m[1;39;49m][0m[39;49m A new release of pip available: [0m[31;49m22.2.1[0m[39;49m -> [0m[32;49m23.0.1[0m
[1m[[0m[34;49mnotice[0m[1;39;49m][0m[39;49m To update, run: [0m[32;49mpip3 install --upgrade pip[0m

	Unnamed: 0	Suburb	Address	Rooms	Type	Price	Method	SellerG	Date	Distance	...	Bathroom	Car	Landsize	BuildingArea	YearBuilt	CouncilArea	Lattitude	Longtitude	Regionname	Propertycount
0	1	Abbotsford	85 Turner St	2	h	1480000	S	Biggin	3/12/2016	2.5	...	1.0	1.0	202.0	NaN	NaN	Yarra	-37.79960	144.99840	Northern Metropolitan	4019.0
1	2	Abbotsford	25 Bloomburg St	2	h	1035000	S	Biggin	4/02/2016	2.5	...	1.0	0.0	156.0	79.0	1900.0	Yarra	-37.80790	144.99340	Northern Metropolitan	4019.0
2	4	Abbotsford	5 Charles St	3	h	1465000	SP	Biggin	4/03/2017	2.5	...	2.0	0.0	134.0	150.0	1900.0	Yarra	-37.80930	144.99440	Northern Metropolitan	4019.0
3	5	Abbotsford	40 Federation La	3	h	850000	PI	Biggin	4/03/2017	2.5	...	2.0	1.0	94.0	NaN	NaN	Yarra	-37.79690	144.99690	Northern Metropolitan	4019.0
4	6	Abbotsford	55a Park St	4	h	1600000	VB	Nelson	4/06/2016	2.5	...	1.0	2.0	120.0	142.0	2014.0	Yarra	-37.80720	144.99410	Northern Metropolitan	4019.0
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
18391	23540	Williamstown	8/2 Thompson St	2	t	622500	SP	Greg	26/08/2017	6.8	...	2.0	1.0	NaN	89.0	2010.0	NaN	-37.86393	144.90484	Western Metropolitan	6380.0
18392	23541	Williamstown	96 Verdon St	4	h	2500000	PI	Sweeney	26/08/2017	6.8	...	1.0	5.0	866.0	157.0	1920.0	NaN	-37.85908	144.89299	Western Metropolitan	6380.0
18393	23544	Yallambie	17 Amaroo Wy	4	h	1100000	S	Buckingham	26/08/2017	12.7	...	3.0	2.0	NaN	NaN	NaN	NaN	-37.72006	145.10547	Northern Metropolitan	1369.0
18394	23545	Yarraville	6 Agnes St	4	h	1285000	SP	Village	26/08/2017	6.3	...	1.0	1.0	362.0	112.0	1920.0	NaN	-37.81188	144.88449	Western Metropolitan	6543.0
18395	23546	Yarraville	33 Freeman St	4	h	1050000	VB	Village	26/08/2017	6.3	...	2.0	2.0	NaN	139.0	1950.0	NaN	-37.81829	144.87404	Western Metropolitan	6543.0

18396 rows × 22 columns

!pip3 install scikit-learn
from sklearn.model_selection import train_test_split

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