I have a Dataframe (data) for which the head looks like the following:
status datetime country amount city
601766 received 1.453916e+09 France 4.5 Paris
669244 received 1.454109e+09 Italy 6.9 Naples
I would like to predict the status given datetime, country, amount and city
Since status, country, city are string, I one-hot-encoded them:
one_hot = pd.get_dummies(data['country'])
data = data.drop(item, axis=1) # Drop the column as it is now one_hot_encoded
data = data.join(one_hot)
I then create a simple LinearRegression model and fit my data:
y_data = data['status']
classifier = LinearRegression(n_jobs = -1)
X_train, X_test, y_train, y_test = train_test_split(data, y_data, test_size=0.2)
columns = X_train.columns.tolist()
classifier.fit(X_train[columns], y_train)
But I got the following error:
could not convert string to float: 'received'
I have the feeling I miss something here and I would like to have some inputs on how to proceed. Thank you for having read so far!