小编Ali*_*ice的帖子

我有这种格式的csv文件:

userId  movieId rating  timestamp
1     31      2.5   1260759144
2     10      4     835355493
3     1197    5     1298932770
4     10      4     949810645

我想构造一个稀疏矩阵,其行为userId,列为movieID.我已将所有数据存储为名为"column"的字典,其中column ['user']包含用户ID,column ['movie']包含电影ID,列['rating']的评级如下:

f = open('ratings.csv','rb')
reader = csv.reader(f)
headers = ['user','movie','rating','timestamp']
column = {}
for h in headers:
    column[h] = []
for row in reader:
    for h, v in zip(headers, row):
        column[h].append(float(v))

当我将稀疏矩阵函数称为:

mat = scipy.sparse.csr_matrix((column['rating'],(column['user'],column['movie'])))

我得到"TypeError:无效的形状"

请帮忙