Im new to Data Science and Analysis. After going through a lot of kernels on Kaggle, I made a model that predicts the price of a property. Ive tested this model using my training data, but now I want to run it on my test data. Ive got a test.csv file and I want to use it. How do I do that? What i previously did with my training dataset:
#loading my train dataset into python
train = pd.read_csv('/Users/sohaib/Downloads/test.csv')
#factors that will predict the price
train_pr = ['OverallQual','GrLivArea','GarageCars','TotalBsmtSF','FullBath','YearBuilt']
#set my model to DecisionTree
model = DecisionTreeRegressor()
#set prediction data to factors that will predict, and set target to SalePrice
prdata = train[train_pr]
target = train.SalePrice
#fitting model with prediction data and telling it my target
model.fit(prdata, target)
model.predict(prdata.head())
Now what I tried to do is, copy the whole code, and change the "train" with "test", and "predate" with "testprdata", and I thought it will work, but sadly no. I know I'm doing something wrong with this, idk what it is.