Modeling
Model 1: Economic Impact of COVID (Unemployment and Card Spending)
January 6th - March 15th
array([1, 1, 1, 0, 2, 1, 1, 2, 2, 0, 0, 1, 2, 0, 0, 0, 2, 1, 2, 1, 0, 0,
2, 1, 2, 1, 1, 2, 1, 0, 0, 1, 0, 0, 0, 1, 0, 1, 2, 1, 0, 0, 0, 0,
2, 0, 1, 2, 0, 0], dtype=int32)
array([[ 0.33596088, -0.81139236],
[ 0.54910234, 0.68508159],
[-1.36582652, 0.44940439]])
KMeans(init='random', n_clusters=3, n_init=1, random_state=0)
array([2, 2, 1, 1, 2, 2, 1, 2, 2, 2, 2, 2, 2, 1, 2, 2, 2, 0, 2, 0, 1, 2,
2, 2, 2, 0, 2, 1, 1, 0, 1, 2, 0, 0, 0, 0, 0, 2, 2, 2, 0, 0, 0, 0,
0, 1, 2, 0, 1, 0], dtype=int32)
array([[-0.72686635, 1.05071854],
[ 1.43919283, 0.15041724],
[-0.11508611, -0.76315287]])
KMeans(init='random', n_clusters=3, n_init=1, random_state=0)
array([1, 2, 1, 0, 1, 2, 0, 2, 2, 2, 2, 2, 2, 2, 1, 2, 0, 2, 2, 1, 0, 2,
1, 1, 2, 0, 1, 1, 2, 1, 0, 1, 1, 1, 0, 0, 2, 2, 0, 2, 0, 0, 1, 0,
0, 0, 1, 0, 0, 0], dtype=int32)
array([[-0.54498581, 1.04478874],
[ 1.01452513, -0.14665297],
[-0.33072879, -0.86453411]])
Model 2: Mobility Data
January 13th - March 15th
Model 3: Pre-COVID Conditions (Income and Education Level)
KMeans(init='random', n_clusters=3, n_init=1, random_state=0)
array([2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 2, 1, 2, 2, 0, 2, 2, 2, 2, 2,
2, 1, 2, 2, 0, 0, 0, 2, 2, 2, 2, 0, 2, 2, 0, 2, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0], dtype=int32)
array([[-0.88000843, -0.89497828],
[ 0.63158111, -1.75553432],
[ 0.48087615, 0.73711076]])
January 22nd - March 15th
KMeans(init='random', n_clusters=2, n_init=1, random_state=0)
array([1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0,
1, 1, 1, 1, 1, 1, 1], dtype=int32)
array([[700987. ],
[ 97001.10638298]])
KMeans(init='random', n_clusters=3, n_init=1, random_state=0)
array([2, 2, 1, 2, 0, 2, 1, 2, 2, 0, 1, 2, 2, 0, 1, 2, 2, 2, 1, 2, 1, 1,
1, 2, 2, 2, 2, 2, 2, 2, 0, 2, 0, 1, 2, 1, 2, 2, 1, 2, 2, 2, 1, 0,
2, 2, 1, 2, 2, 2, 2], dtype=int32)
array([[208875.83333333],
[ 66821.53846154],
[ 15603.15625 ]])
KMeans(init='random', n_clusters=3, n_init=1, random_state=0)
array([1, 2, 1, 2, 0, 2, 2, 2, 2, 0, 1, 2, 2, 1, 2, 2, 2, 2, 1, 2, 2, 2,
2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 2, 1, 2, 1, 2, 2, 2, 2, 1, 2, 1, 0,
2, 2, 1, 2, 2, 1, 2], dtype=int32)
array([[576201.33333333],
[127319.41666667],
[ 34630.75 ]])
Model 5: Predicting September Economic Impact of COVID Using Mobility, Pre-COVID Conditions, and COVID Cases from January to August
KMeans(init='random', n_clusters=3, n_init=1, random_state=0)
array([1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 0, 0, 1, 2, 0, 2, 2, 2,
2, 1, 2, 2, 0, 0, 0, 2, 2, 2, 2, 0, 2, 2, 0, 2, 2, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0], dtype=int32)
array([[ 0.06690464, 0.63063881],
[ 1.05626039, -1.30653883],
[-1.06969338, 0.47599657]])
