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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]
993
You can get unique values in column (multiple columns) from pandas DataFrame using unique() or Series. unique() functions. unique() from Series is used to get unique values from a single column and the other one is used to get from multiple columns.
In order to select rows between two dates in pandas DataFrame, first, create a boolean mask using mask = (df['InsertedDates'] > start_date) & (df['InsertedDates'] <= end_date) to represent the start and end of the date range. Then you select the DataFrame that lies within the range using the DataFrame.
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) If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
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