Convert 18-digit LDAP/FILETIME timestamps to human readable date
I know this answer is very late to the party, but for anyone else looking in the future.
The 18-digit Active Directory timestamps (LDAP), also named 'Windows NT time format','Win32 FILETIME or SYSTEMTIME' or NTFS file time. These are used in Microsoft Active Directory for pwdLastSet, accountExpires, LastLogon, LastLogonTimestamp and LastPwdSet. The timestamp is the number of 100-nanoseconds intervals (1 nanosecond = one billionth of a second) since Jan 1, 1601 UTC.
Therefore, 130305048577611542 does indeed relate to December 3, 2013.
When putting this value through the date time function in Python, it is truncating the value to nine digits. Therefore the timestamp becomes 130305048 and goes from 1.1.1970 which does result in a 1974 date!
In order to get the correct Unix timestamp you need to do: 
(130305048577611542 / 10000000) - 11644473600
I have exported a list of AD Users out of AD and need to validate their login times.
The output from the powershell script give lastlogin as LDAP/FILE time
EXAMPLE 130305048577611542 
I am having trouble converting this to readable time in pandas 
Im using the following code:
df['date of login'] = pd.to_datetime(df['FileTime'], unit='ns')
The column FileTime contains time formatted like the EXAMPLE above. 
Im getting the following output in my new column date of login 
EXAMPLE 1974-02-17 03:50:48.577611542
I know this is being parsed incorrectly as when i input this date time on a online converter i get this output
EXAMPLE:
Epoch/Unix time: 1386031258
GMT: Tuesday, December 3, 2013 12:40:58 AM
Your time zone: Monday, December 2, 2013 4:40:58 PM GMT-08:00
Anyone have an idea of what occuring here why are all my dates in the 1970'