How do I separate date and time of a raw date?

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>> a = untitled.startDate(1:10)
a =
10×1 categorical array
2013-07-10 00:01:00.0
2013-07-17 00:01:00.0
2013-06-29 00:01:00.0
2013-07-17 00:01:00.0
2013-05-11 00:01:00.0
2013-05-31 00:01:00.0
2013-06-06 00:01:00.0
2013-08-31 00:01:00.0
2013-05-21 00:01:00.0
2013-08-06 00:01:00.0
>> a.Format = 'dd-MMM-yyyy'
Error using categorical/subsasgn (line 87)
Attempt to assign field of non-structure array.
  3 个评论
aishah
aishah 2018-3-30
What I did was, I imported the data into a 'table'. And I convert the data to 'Categorical Array'.

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采纳的回答

Ahmet Cecen
Ahmet Cecen 2018-3-30
编辑:Ahmet Cecen 2018-3-30
arrayfun(@(x) strsplit(x,' '),string(a),'UniformOutput',false)
string(a) - this makes the data easily process-able, converts to a string array.
@(x) strsplit(x,' ') - this is a function that splits each string into parts whenever a space(' ') is located(which works for your case)
arrayfun - applies the above function to each "row" in the string array.
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aishah
aishah 2018-3-30
b = reshape([k{:}],2,length(a))'
Undefined variable "k" or class "k".
aishah
aishah 2018-3-30
celldisp(b)
b{1} =
"2013-07-10" "00:01:00.0"
b{2} =
"2013-07-17" "00:01:00.0"
b{3} =
"2013-06-29" "00:01:00.0"
b{4} =
"2013-07-17" "00:01:00.0"
b{5} =
"2013-05-11" "00:01:00.0"
b{6} =
"2013-05-31" "00:01:00.0"
b{7} =
"2013-06-06" "00:01:00.0"
b{8} =
"2013-08-31" "00:01:00.0"
b{9} =
"2013-05-21" "00:01:00.0"
b{10} =
"2013-08-06" "00:01:00.0"

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更多回答(1 个)

Peter Perkins
Peter Perkins 2018-4-2
Don't do any of that.
You've read the timestamps in as datetimes. Don't fight that. Assuming you have a table T:
T.StartTime = timeofday(T.StartDate);
T.StartDate = dateshift(T.StartDate,'start','day);
  6 个评论
Steph
Steph 2019-2-24
I missteated my problem I think, I am doing regressions on the data that is collected on each of the specific days. Not on the dates or days themselves
Walter Roberson
Walter Roberson 2019-2-24
Then you do not need to convert the dates + times or datetime objects to numeric. What you need to do is be able to group your data based upon date. You should have a look at splitapply() -- or convert the table to a timetable() object and use retime()

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