Linar regression on pandas gives null as regression score

Question

from sklearn.linear_model import LinearRegression my_y = np.array([2, 5, 6, 10]).reshape(1, -1) my_x = np.array([19, 23, 22, 30]).reshape(1,-1) lm = LinearRegression() lm = lm.fit(my_x, my_y) result = lm.score(my_x, my_y) print(result) Why does this give Nan as output

Answer 1

You need to use reshape(-1, 1) for arrays

my_y = np.array([2,5,6,10]).reshape(-1, 1)
my_x = np.array([19,23,22,30]).reshape(-1, 1)

lm = sk.LinearRegression()
lm = lm.fit(my_x, my_y)
result = lm.score(my_x, my_y)
print(result)

0.9302407516147975