ValueError: Type names and field names must be valid identifiers: 'Subject ID'

[Sejin Kim]

`

ValueError Traceback (most recent call last)
in
----> 1 namedtuple("Output", df.columns.astype("str").tolist())

~.conda\envs\lirc-ldri\lib\collections_init_.py in namedtuple(typename, field_names, verbose, rename, module)
399 if not name.isidentifier():
400 raise ValueError('Type names and field names must be valid '
--> 401 'identifiers: %r' % name)
402 if _iskeyword(name):
403 raise ValueError('Type names and field names cannot be a '

ValueError: Type names and field names must be valid identifiers: 'Subject ID'
`

Could we use an alternative datatype to prevent error if the metadata sheet has column names with spaces (Subject ID) or invalid characters (File Size (Bytes))? Or we could rename all columns, but this might be an issue when trying to debug.