熊猫数据框匹配行之间的日期

Question

REF         FROM_DATE               EXEMPT_FROM
10001033    2017-07-11 00:00:00     2017-07-11 00:00:00
10001033    2017-07-11 00:00:00     2017-08-10 00:00:00
10001033    2017-07-11 00:00:00     2018-04-01 00:00:00
10001769    2018-05-15 00:00:00     2016-07-15 00:00:00
10001769    2018-05-15 00:00:00     2018-01-03 00:00:00
10001769    2018-05-15 00:00:00     2018-05-15 00:00:00
10001769    2018-05-15 00:00:00     2018-06-14 00:00:00

I have the above data frame and I would like to be able to count the number of Unique REFs whose first row From_DATE does not match its first row Exempt_FROM.

For example the first REF number 10001033 FROM_DATE and EXEMPT_FROM match but the second REF 10001769 do not. What might be the best approach?

Answer 1

IIUC, this is what you want

A = df.groupby('REF').first()
A.FROM_DATE == A.EXEMPT_FROM

Output:

REF
10001033     True
10001769    False

If you want to know how many times you have the desired match, apply sum

sum(A.FROM_DATE == A.EXEMPT_FROM)