# VAR example
from statsmodels.tsa.vector_ar.var_model import VAR
from random import random
# contrived dataset with dependency
data = list()
for i in range(100):
    v1 = i + random()
    v2 = v1 + random()
    row = [v1, v2]
    data.append(row)
# fit model
model = VAR(data)
model_fit = model.fit()
# make prediction
yhat = model_fit.forecast(model_fit.y, steps=1)
print(yhat)

[((12, 8, 12, 17), 'statsmodels.tsa.vector_ar.var_model.VAR', 'VAR', ({(12, 12, 12, 16): 'data'}, {}), '(data)', False, 'from statsmodels.tsa.vector_ar.var_model import VAR\n'), ((7, 13, 7, 21), 'random.random', 'random', ({}, {}), '()', False, 'from random import random\n'), ((8, 14, 8, 22), 'random.random', 'random', ({}, {}), '()', False, 'from random import random\n')]