I have a DataFrame which contains a lot of intraday data, the DataFrame has several days of data, dates are not continuous.
2012-10-08 07:12:22 0.0 0 0 2315.6 0 0.0 0 2012-10-08 09:14:00 2306.4 20 326586240 2306.4 472 2306.8 4 2012-10-08 09:15:00 2306.8 34 249805440 2306.8 361 2308.0 26 2012-10-08 09:15:01 2308.0 1 53309040 2307.4 77 2308.6 9 2012-10-08 09:15:01.500000 2308.2 1 124630140 2307.0 180 2308.4 1 2012-10-08 09:15:02 2307.0 5 85846260 2308.2 124 2308.0 9 2012-10-08 09:15:02.500000 2307.0 3 128073540 2307.0 185 2307.6 11 ...... 2012-10-10 07:19:30 0.0 0 0 2276.6 0 0.0 0 2012-10-10 09:14:00 2283.2 80 98634240 2283.2 144 2283.4 1 2012-10-10 09:15:00 2285.2 18 126814260 2285.2 185 2285.6 3 2012-10-10 09:15:01 2285.8 6 98719560 2286.8 144 2287.0 25 2012-10-10 09:15:01.500000 2287.0 36 144759420 2288.8 211 2289.0 4 2012-10-10 09:15:02 2287.4 6 109829280 2287.4 160 2288.6 5 ......
How can I extract the unique date in the datetime format from the above DataFrame? To have result like [2012-10-08, 2012-10-10]
Advertisement
Answer
If you have a Series
like:
In [116]: df["Date"] Out[116]: 0 2012-10-08 07:12:22 1 2012-10-08 09:14:00 2 2012-10-08 09:15:00 3 2012-10-08 09:15:01 4 2012-10-08 09:15:01.500000 5 2012-10-08 09:15:02 6 2012-10-08 09:15:02.500000 7 2012-10-10 07:19:30 8 2012-10-10 09:14:00 9 2012-10-10 09:15:00 10 2012-10-10 09:15:01 11 2012-10-10 09:15:01.500000 12 2012-10-10 09:15:02 Name: Date
where each object is a Timestamp
:
In [117]: df["Date"][0] Out[117]: <Timestamp: 2012-10-08 07:12:22>
you can get only the date by calling .date()
:
In [118]: df["Date"][0].date() Out[118]: datetime.date(2012, 10, 8)
and Series have a .unique()
method. So you can use map
and a lambda
:
In [126]: df["Date"].map(lambda t: t.date()).unique() Out[126]: array([2012-10-08, 2012-10-10], dtype=object)
or use the Timestamp.date
method:
In [127]: df["Date"].map(pd.Timestamp.date).unique() Out[127]: array([2012-10-08, 2012-10-10], dtype=object)