CODEWITHSUNDEEP
pythonregressionartificial-intelligencetrain-test-split
sonus vareed
sonus vareed

Reputation: 31

Type error:Singleton array while trying to split the dataset in python using train_test_split()

This is the format of the dataset enter image description here

This is my code:

import numpy as np
import matplotlib.pyplot as plt
import pandas as pd

#Importing the dataset
dataset1 = pd.read_csv('DATASETS/movielens movie recommender/ml-25m/ratings.csv')

#Splitting into dependent and independent variables
X1 = dataset1.iloc[:,[0,3]].values
y1 = dataset1.iloc[:, 1:3].values

#Encoding
from sklearn.compose import ColumnTransformer
from sklearn.preprocessing import OneHotEncoder
ct = ColumnTransformer(transformers=[('encoder', OneHotEncoder(), [0,1])], remainder='passthrough')
ct2 = ColumnTransformer(transformers=[('encoder', OneHotEncoder(), [0])], remainder='passthrough')
y1 = np.array(ct.fit_transform(y1))
X1 = np.array(ct2.fit_transform(X1))


#Splitting into training set and test set
from sklearn.model_selection import train_test_split
X1_train, X1_test, y1_train, y1_test = train_test_split(X1, y1, test_size = 0.2, random_state = 1)

I get the following error

TypeError: Singleton array array(<25000095x162542 sparse matrix of type '<class 'numpy.float64'>'
    with 50000190 stored elements in Compressed Sparse Row format>,
      dtype=object) cannot be considered a valid collection.

Could someone tell me what this means and how i could solve this?

Upvotes: 0

Views: 1529

Answers (1)

ALKESH KUMAR
ALKESH KUMAR

Reputation: 21

instead of this

y1 = np.array(ct.fit_transform(y1))

X1 = np.array(ct2.fit_transform(X1))

you can use

y1 = ct.fit_transform(y1).toarray()

x1 = ct.fit_transform(x1).toarray()

it works for me !

Upvotes: 2

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