Select date range from Pandas DataFrame

Question

I have a list of dates in a DF that have been converted to a YYYY-MM format and need to select a range. This is what I'm trying:

#create dataframe    
data = ['2016-01','2016-02','2016-09','2016-10','2016-11','2017-04','2017-05','2017-06','2017-07','2017-08']
df = pd.DataFrame(data, columns = {'date'})

#lookup range
df[df["date"].isin(pd.date_range('2016-01', '2016-06'))]

It doesn't seem to be working because the date column is no longer a datetime column. The format has to be in YYYY-MM. So I guess the question is, how can I make a datetime column with YYYY-MM? Can someone please help? Thanks.

John Zwinck · Accepted Answer · 2017-10-14 08:49:13Z

3

You do not need an actual datetime-type column or query values for this to work. Keep it simple:

df[df.date.between('2016-01', '2016-06')]

That gives:

      date
0  2016-01
1  2016-02

It works because ISO 8601 date strings can be sorted as if they were plain strings. '2016-06' comes after '2016-05' and so on.

answered Oct 14, 2017 at 8:49

John Zwinck

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