import numpy as np
import pandas as pd
from sklearn.model_selection import train_test_split

labelled = pd.read_csv("monthly-data-labelled.csv")
unlabelled = pd.read_csv("monthly-data-unlabelled.csv")

X = labelled.drop('city',1).values
y = labelled['city'].values

X_train, X_test, y_train, y_test = train_test_split(X, y)

42a28c2c2f680f8e43f2856ed8b933a96bf14601
<mask token>

<mask token>
labelled = pd.read_csv('monthly-data-labelled.csv')
unlabelled = pd.read_csv('monthly-data-unlabelled.csv')
X = labelled.drop('city', 1).values
y = labelled['city'].values
X_train, X_test, y_train, y_test = train_test_split(X, y)

import numpy as np
import pandas as pd
from sklearn.model_selection import train_test_split
labelled = pd.read_csv('monthly-data-labelled.csv')
unlabelled = pd.read_csv('monthly-data-unlabelled.csv')
X = labelled.drop('city', 1).values
y = labelled['city'].values
X_train, X_test, y_train, y_test = train_test_split(X, y)

import numpy as np
import pandas as pd
from sklearn.model_selection import train_test_split

labelled = pd.read_csv("monthly-data-labelled.csv")
unlabelled = pd.read_csv("monthly-data-unlabelled.csv")

X = labelled.drop('city',1).values
y = labelled['city'].values

X_train, X_test, y_train, y_test = train_test_split(X, y)
