14. csv 9 10
import numpy as np
import csv
data = []
target = []
filename = "input_data.csv"
with open(filename) as f:
for row in csv.reader(f):
data.append([float(x) for x in row[:9]])
target.append(float(row[9]))
data = np.array(data)
target = np.array(target)
16. MovieLens
from scipy import sparse
items = []
users = []
ratings = []
for line in open("ml-100k/u.data"):
a = line.split("t")
users.append(int(a[0]))
items.append(int(a[1]))
ratings.append(int(a[2]))
n_users = max(users)
n_items = max(items)
mat = sparse.lil_matrix((n_users, n_items))
for u, i, r in zip(users, items, ratings):
mat[u - 1, i - 1] = r
mat = mat.tocsr()