<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
 def _convert_to_df(in_file, freq, raw_file):
 """ convert data frame into table with pandas """

    dat = defaultdict(Counter)
    if isinstance(in_file, (str, unicode)):
        with open(in_file) as in_handle:
            for line in in_handle:
                cols = line.strip().split("\t")
                counts = freq[cols[3]]
                dat = _expand(dat, counts, int(cols[1]), int(cols[2]))
    else:
        if raw_file:
            out_handle = open(raw_file, "w")
        for name in in_file:
            counts = freq[name]
            if raw_file:
                print("%s\t%s\t%s\t%s\t%s\t%s" % ("chr", in_file[name][0], in_file[name][1], name, sum(counts.values()), "+"), file=out_handle, end="")
            dat = _expand(dat, counts, in_file[name][0], in_file[name][1])

    for s in dat:
        for p in dat[s]:
            dat[s][p] = mlog2(dat[s][p] + 1)
    return dat