Temperature - humidity + wind

data = pd.read_csv('data6.csv' )
data['date'] = pd.to_datetime(data['date'] + " " + data['time'], format='%m/%d/%Y %H:%M:%S')
data.set_index('date', inplace=True)
data = data.values

scaler = MinMaxScaler(feature_range=(0, 1))
data = scaler.fit_transform(data)

train_size = int(len(data) * 0.67)
test_size = len(data) - train_size
train, test = data[0:train_size,:], data[train_size:len(data),:]

X = 1
n_out = 1

x,y=[],[]
start =0
data = train.reshape(train.shape(train.shape[0] ,1, train.shape[1]))
for _ in range(len(data)):
  in_end = start+X
  out_end= in_end + n_out
  if out_end < len(data):
    x_input = data[start:in_end]
    x.append(x_input)
    y.append(data[in_end:out_end,0])
start +=1

x = np.asanyarray(x)
y = np.asanyarray(y)