给定another question的数据集：
user item \
0 b80344d063b5ccb3212f76538f3d9e43d87dca9e The Cove - Jack Johnson
1 b80344d063b5ccb3212f76538f3d9e43d87dca9e Entre Dos Aguas - Paco De Lucia
2 b80344d063b5ccb3212f76538f3d9e43d87dca9e Stronger - Kanye West
3 b80344d063b5ccb3212f76538f3d9e43d87dca9e Constellations - Jack Johnson
4 b80344d063b5ccb3212f76538f3d9e43d87dca9e Learn To Fly - Foo Fighters
rating
0 1
1 2
2 1
3 1
4 1
是否有任何方法可以以预期的格式加载这些数据，而不必手动将所有内容移到同一行？
最佳答案
方法之一是基于\n\n进行拆分，然后创建单独的数据帧，然后将它们连接起来。即
#Bit of code from https://stackoverflow.com/questions/45740537/copying-multiindex-dataframes-with-pd-read-clipboard
def read_clipboard_split(index_names_row=None, **kwargs):
encoding = kwargs.pop('encoding', 'utf-8')
# only utf-8 is valid for passed value because that's what clipboard
# supports
if encoding is not None and encoding.lower().replace('-', '') != 'utf8':
raise NotImplementedError(
'reading from clipboard only supports utf-8 encoding')
from pandas import compat, read_fwf
from pandas.io.clipboard import clipboard_get
from pandas.io.common import StringIO
data = clipboard_get()
items = data.split("\n\n")
k = []
for i in items:
k.append(read_fwf(StringIO(i), **kwargs))
df = pd.concat(k,axis=1)
return df
read_clipboard_split()
样本运行：
用户\
0 b80344d063b5ccb3212f76538f3d9e43d87dca9e号
1号B80344d063b5ccb3212f76538f3d9e43d87dca9e
2号b80344d063b5ccb3212f76538f3d9e43d87dca9e
3号B80344d063b5ccb3212f76538f3d9e43d87dca9e
4号B80344d063b5ccb3212f76538f3d9e43d87dca9e
评级
0 1个
12个
2 1个
3 1个
4 1个
输出：
未命名：0用户\n未命名：0分级
0 0 b80344d063b5ccb3212f76538f3d9e43d87dca9e 0 1
1 1 B80344d063b5ccb3212f76538f3d9e43d87dca9e1 2
2 2 B80344d063b5ccb3212f76538f3d9e43d87dca9e2 1
3 3 b80344d063b5ccb3212f76538f3d9e43d87dca9e3 1
4 4 B80344d063b5ccb3212f76538f3d9e43d87dca9e4 1