pandas get delta from corresponding date in a seperate list of dates

I have a dataframe

df a b
   7 2019-05-01 00:00:01
   6 2019-05-02 00:15:01 
   1 2019-05-06 00:10:01
   3 2019-05-09 01:00:01
   8 2019-05-09 04:20:01
   9 2019-05-12 01:10:01
   4 2019-05-16 03:30:01

And

l = [datetime.datetime(2019,05,02), datetime.datetime(2019,05,10), datetime.datetime(2019,05,22) ]

I want to add a column with the following:
for each row, find the last date from l that is before it, and add number of days between them.
If none of the date is smaller – add the delta from the smallest one.
So the new column will be:

df a b.                 delta
   7 2019-05-01 00:00:01 -1
   6 2019-05-02 00:15:01  0
   1 2019-05-06 00:10:01  4
   3 2019-05-09 01:00:01  7
   8 2019-05-09 04:20:01  7
   9 2019-05-12 01:10:01  2
   4 2019-05-16 03:30:01  6

How can I do it?

Thanks

>Solution :

Using merge_asof to align df['b'] and the list (as Series), then computing the difference:

# ensure datetime
df['b'] = pd.to_datetime(df['b'])

# craft Series for merging (could be combined with line below)
s = pd.Series(l, name='l')

# merge and fillna with minimum date
ref = pd.merge_asof(df['b'], s, left_on='b', right_on='l')['l'].fillna(s.min())

# compute the delta as days
df['delta'] =(df['b']-ref).dt.days

output:

   a                   b  delta
0  7 2019-05-01 00:00:01     -1
1  6 2019-05-02 00:15:01      0
2  1 2019-05-06 00:10:01      4
3  3 2019-05-09 01:00:01      7
4  8 2019-05-09 04:20:01      7
5  9 2019-05-12 01:10:01      2
6  4 2019-05-16 03:30:01      6

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