[FIXED] sklearn mutiple linear regression --> dtype error

Issue

I'm trying to predict a value using a linear regression model. However, when I use .predict from sklearn I can't find a way to plug in the data for X without getting a data type error.

from sklearn import linear_model

KitchenQual_X = KitchenQual_df[["OverallQual", "YearBuilt", "YearRemodAdd", "GarageCars", "GarageArea"]]
KitchenQual_Y = KitchenQual_df["dummy_KitchenQual"]

regr_KitchenQual = linear_model.LinearRegression()
regr_KitchenQual.fit(KitchenQual_X, KitchenQual_Y)

print("Predicted missing KitchenQual value: " + regr_KitchenQual.predict(df_both[["OverallQual", "YearBuilt", "YearRemodAdd", "GarageCars", "GarageArea"]].loc[[1555]]))

When running the code in my kaggle notebook I receive the following error:

---------------------------------------------------------------------------
UFuncTypeError                            Traceback (most recent call last)
<ipython-input-206-1f022a48e21c> in <module>
----> 1 print("Predicted missing KitchenQual value: " + regr_KitchenQual.predict(df_both[["OverallQual", "YearBuilt", "YearRemodAdd", "GarageCars", "GarageArea"]].loc[[1555]]))

UFuncTypeError: ufunc 'add' did not contain a loop with signature matching types (dtype('<U37'), dtype('<U37')) -> dtype('<U37')

I would appreciate any help :)

Solution

Assuming your dependent variable is continuous, using an example data and repeating your steps:

from sklearn import linear_model
import numpy as np
import pandas as pd

KitchenQual_df = pd.DataFrame(np.random.normal(0,1,(2000,6)))
KitchenQual_df.columns = ["OverallQual", "YearBuilt", "YearRemodAdd", "GarageCars", "GarageArea","dummy_KitchenQual"]

KitchenQual_X = KitchenQual_df[["OverallQual", "YearBuilt", "YearRemodAdd", "GarageCars", "GarageArea"]]
KitchenQual_Y = KitchenQual_df["dummy_KitchenQual"]

regr_KitchenQual = linear_model.LinearRegression()
regr_KitchenQual.fit(KitchenQual_X, KitchenQual_Y)

pred = regr_KitchenQual.predict(KitchenQual_df[["OverallQual", "YearBuilt", "YearRemodAdd", "GarageCars", "GarageArea"]].loc[[1555]])

The prediction is an array and you cannot just concatenate a string and an array using +, these negative example below gives you the same error in the question:

"a" + np.array(['b','c'])
"a" + np.array([1,2])

UFuncTypeError: ufunc 'add' did not contain a loop with signature matching types (dtype('<U1'), dtype('<U1')) -> dtype('<U1')

You can do:

print("Predicted missing KitchenQual value: " + str(pred[0]))

Predicted missing KitchenQual value: -0.11176904834490986

Answered By - StupidWolf