If I understand your logic correctly, then you should be be able to do this without a loop. From what I can see, it looks like you want to drop rows if the FilePath column does not begin with .. If this is correct, then below is one way to do this:
Create sample data using nested list
d = [
['BytesAccessed','FilePath','DateTime'],
[0, '/lib/x86_64-linux-gnu/libtinfo.so.5 832.0', '[28/Jun/2018:11:53:09]'],
[1, './lib/x86-linux-gnu/yourtext.so.6 932.0', '[28/Jun/2018:11:53:09]'],
[2, '/lib/x86_64-linux-gnu/mytes0', '[28/Jun/2018:11:53:09]'],
]
data = pd.DataFrame(d[1:], columns=d[0])
print(data)
BytesAccessed FilePath DateTime
0 0 /lib/x86_64-linux-gnu/libtinfo.so.5 832.0 [28/Jun/2018:11:53:09]
1 1 ./lib/x86-linux-gnu/yourtext.so.6 932.0 [28/Jun/2018:11:53:09]
2 2 /lib/x86_64-linux-gnu/mytes0 [28/Jun/2018:11:53:09]
Filtered data to drop rows that do not contain . at any location in the FilePath column
data_filtered = (data.set_index('FilePath')
.filter(like='.', axis=0)
.reset_index())[data.columns]
print(data_filtered)
BytesAccessed FilePath DateTime
0 0 /lib/x86_64-linux-gnu/libtinfo.so.5 832.0 [28/Jun/2018:11:53:09]
1 1 ./lib/x86-linux-gnu/yourtext.so.6 932.0 [28/Jun/2018:11:53:09]