For year ended march 29, 2019, what is the difference between  Total Consumer Cyber Safety and Total Enterprise Security?
{"Enterprise Security: -- Endpoint and information protection": {"March 29, 2019": 1027, "March 30, 2018": 983, "March 31, 2017": 947}, "Enterprise Security: -- Network and web security": {"March 29, 2019": 748, "March 30, 2018": 782, "March 31, 2017": 451}, "Enterprise Security: -- WSS and PKI": {"March 29, 2019": "-", "March 30, 2018": 238, "March 31, 2017": 422}, "Enterprise Security: -- Other products and services": {"March 29, 2019": 548, "March 30, 2018": 551, "March 31, 2017": 535}, "Enterprise Security: -- Total Enterprise Security": {"March 29, 2019": 2323, "March 30, 2018": 2554, "March 31, 2017": 2355}, "Consumer Cyber Safety: -- Consumer security": {"March 29, 2019": 1471, "March 30, 2018": 1504, "March 31, 2017": 1527}, "Consumer Cyber Safety: -- Identity and information protection": {"March 29, 2019": 937, "March 30, 2018": 776, "March 31, 2017": 137}, "Consumer Cyber Safety: -- Total Consumer Cyber Safety": {"March 29, 2019": 2408, "March 30, 2018": 2280, "March 31, 2017": 1664}, "Consumer Cyber Safety: -- Total net revenues": {"March 29, 2019": 4731, "March 30, 2018": 4834, "March 31, 2017": 4019}}
total_consumer_cyber_safety = df["Consumer Cyber Safety: -- Total Consumer Cyber Safety"]["March 29, 2019"]
total_enterprise_security = df["Enterprise Security: -- Total Enterprise Security"]["March 29, 2019"]
answer = total_consumer_cyber_safety - total_enterprise_security