我用 python 创建了一个程序，在其中使用协同过滤来查找基于 Item 的 CF。 我的代码是，
# Create a placeholder items for closes neighbours to an item
data_neighbours = pd.DataFrame(index=data_ibs.columns,columns=[range(1,13)])
print data_neighbours
# Loop through our similarity dataframe and fill in neighbouring item names
for i in range(0,len(data_ibs.columns)):
##use sort_values(...)
data_neighbours.ix[i,:10] = data_ibs.ix[0:,i].sort_values(ascending=[1, 0])[:10].index
data_neighbours.ix[i,:10] = data_ibs.ix[0:,i].sort_values(ascending=[1, 0])[:10].index
print data_neighbours.ix[i,:10]
Output is in table:
user 1 2 3
0 192. c1s1b1p3 c1s1b1p4 c1s1b1p5
1 192. c1s1b1p3 c1s1b1p4 c1s1b1p5
2 192. c1s1b1p3 c1s1b1p4 c1s1b1p5
3 192. c1s1b1p3 c1s1b1p4 c1s1b1p5
4 192. c1s1b1p7 c1s1b1p8 c1s1b1p10
5 192 c1s1b1p5 c1s1b1p6 c1s1b1p7
6 192. c1s1b1p3 c1s1b1p4 c1s1b1p5
7 192. c1s1b1p8 c1s1b1p9 c1s1b1p4
8 192. c1s1b1p6 c1s1b1p10 c1s1b1p5
9 192. c1s1b1p3 c1s1b1p5 c1s1b1p7
10 192. c1s1b1p6 c1s1b1p8 c1s1b1p9
这是 cmd 提示符上显示的表格，我想将此表格保存在 csv 文件中。如何创建 csv 文件来存储该表。
最佳答案
with open('hi.csv','wb') as ff:
sw=csv.writer(ff,delimiter=',',quoting=csv.QUOTE_MINIMAL)
for rows in data_neighbours:
sw.writerow(rows)
data_neighbours 必须包含按行排列的列表...
关于python - 在Python中创建csv文件，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/39166256/