python - pandas filtering and comparing dates

Question

I have a sql file which consists of the data below which I read into pandas.

df = pandas.read_sql('Database count details', con=engine,
                     index_col='id', parse_dates='newest_available_date')

Output

id       code   newest_date_available
9793708  3514   2015-12-24
9792282  2399   2015-12-25
9797602  7452   2015-12-25
9804367  9736   2016-01-20
9804438  9870   2016-01-20

The next line of code is to get last week's date

date_before = datetime.date.today() - datetime.timedelta(days=7) # Which is 2016-01-20

What I am trying to do is, to compare date_before with df and print out all rows that is less than date_before

if (df['newest_available_date'] < date_before): print(#all rows)

Obviously this returns me an error The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

How should I do this?

Answer 1

I would do a mask like:

a = df[df['newest_date_available'] < date_before]

If date_before = datetime.date(2016, 1, 19), this returns:

        id  code newest_date_available
0  9793708  3514            2015-12-24
1  9792282  2399            2015-12-25
2  9797602  7452            2015-12-25