04-Linear-Regression-Project-DataSet

Driptanil DattaSoftware Developer

NOTE: BEFORE WE CAN CONTINUE WITH THIS PROJECT WE NEED TO PERFORM FEATURE ENGINEERING. THE NEXT SECTION OF THE COURSE WILL FOCUS ON TEACHING YOU FEATURE ENGINEERING ON THIS DATASET.

JUMP FORWARD TO THE FEATURE ENGINEERING SECTION

The dataset we will be working with later on in the next section:

Ames Iowa Data Set: http://jse.amstat.org/v19n3/decock.pdf (opens in a new tab)

import pandas as pd

df = pd.read_csv("..\DATA\Ames_Housing_Data.csv")

df.head()

HTML

PID
MS SubClass
MS Zoning
Lot Frontage
Lot Area

df.info()

STDOUT

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 2930 entries, 0 to 2929
Data columns (total 81 columns):
 #   Column           Non-Null Count  Dtype  
---  ------           --------------  -----

03 Regularization Ridge Lasso Elasticnet 05 Linear Regression Execise