Masking sensitive PII
You have been given a dataset containing Social Security numbers (SSN) of American citizens along with their city locations and age. If this was unreleased data only consented to be shared with us, when exposing it, a privacy breach would occur since you are disclosing data the subjects didn't expect us to share.
Your job will be to anonymize the data by applying partial masking to the Sensitive PII ssn
. Remember, data masking is about hiding/obfuscating data to avoid data privacy breaches, while preserving the overall format and semantics.
The dataset has been loaded as insurance_df
, but save the resulting data in masked_df
to keep the original insurance_df
intact.
This exercise is part of the course
Data Privacy and Anonymization in Python
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Uniformly mask the SSN numbers with *
____
# See resulting DataFrame
print(____)