Putting Timetables Together to Create One Large Table

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CMatlabWold 2020-6-23

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https://ww2.mathworks.cn/matlabcentral/answers/553669-putting-timetables-together-to-create-one-large-table

评论： CMatlabWold 2020-6-25

Hi,

I have a code. And I want to put the columns of timetables sequentially.

For instance, in my code produces these timetables tt5, tt11, tt17, tt23, tt29, tt36, tt41, tt47, tt53, tt59. They represent the years 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, and 2019, respectively.

Following the last row of tt5, I want the first row of tt11 to begin. Then following the last row of tt11, I want the first row of tt17 to begin. In this way, there creates one large table, with the data running straight from 2010 thru 2019.

I would appreciate any help. Thank you.

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CMatlabWold 2020-6-24

在 MATLAB Online 中打开

I know. But I'm getting the tables from this code:

%2010
tt0 = readtable('BackupByZipCode1.xlsx');
tt1=table2timetable(tt0)
tt1.ZIPCODE = categorical(tt1.ZIPCODE);
tt1.Dummy = ones(height(tt1),1);
tt2 = unstack(tt1,'Dummy','ZIPCODE');
tt2 = fillmissing(tt2,'Constant',0);
caldiff(tt1.Date([1 end]),'days')
t = datetime(2010,1,1):caldays(1):datetime(2010,12,31);
tt3 = retime(tt2,t,'FillWithConstant','Constant',0);
tt3.DoY = day(tt3.Date,'dayofyear');
tt4 = timetable2table(tt3,'ConvertRowTimes',false);
tt4 = varfun(@sum,tt4,'GroupingVariable','DoY');
tt3.MoY = month(tt3.Date);
tt3.DoM = day(tt3.Date);
tt3.WoY = week(tt3.Date);
tt4 = timetable2table(tt3,'ConvertRowTimes',false);
tt4 = varfun(@sum,tt4,'GroupingVariables',{'WoY' 'MoY' 'DoM'});
leapDayRows = (tt4.MoY==2) & (tt4.DoM==29);
tt4(leapDayRows,:) = [];
tt5 = varfun(@sum,tt4,'GroupingVariable','WoY') 
%2011
tt6 = readtable('BackupByZipCode1.xlsx');
tt7=table2timetable(tt6)
tt7.ZIPCODE = categorical(tt7.ZIPCODE);
tt7.Dummy = ones(height(tt7),1);
tt8 = unstack(tt7,'Dummy','ZIPCODE');
tt8 = fillmissing(tt8,'Constant',0);
caldiff(tt7.Date([1 end]),'days')
t0 = datetime(2011,1,1):caldays(1):datetime(2011,12,31);
tt9 = retime(tt8,t0,'FillWithConstant','Constant',0);
tt9.DoY = day(tt9.Date,'dayofyear');
tt10 = timetable2table(tt9,'ConvertRowTimes',false);
tt10 = varfun(@sum,tt10,'GroupingVariable','DoY');
tt9.MoY = month(tt9.Date);
tt9.DoM = day(tt9.Date);
tt9.WoY = week(tt9.Date);
tt10 = timetable2table(tt9,'ConvertRowTimes',false);
tt10 = varfun(@sum,tt10,'GroupingVariables',{'WoY' 'MoY' 'DoM'});
leapDayRows = (tt10.MoY==2) & (tt10.DoM==29);
tt10(leapDayRows,:) = [];
tt11 = varfun(@sum,tt10,'GroupingVariable','WoY') 
%2012
tt12 = readtable('BackupByZipCode1.xlsx');
tt13=table2timetable(tt12)
tt13.ZIPCODE = categorical(tt13.ZIPCODE);
tt13.Dummy = ones(height(tt13),1);
tt14 = unstack(tt13,'Dummy','ZIPCODE');
tt14 = fillmissing(tt14,'Constant',0);
caldiff(tt13.Date([1 end]),'days')
t1 = datetime(2012,1,1):caldays(1):datetime(2012,12,31);
tt15 = retime(tt14,t1,'FillWithConstant','Constant',0);
tt15.DoY = day(tt15.Date,'dayofyear');
tt16 = timetable2table(tt15,'ConvertRowTimes',false);
tt16 = varfun(@sum,tt16,'GroupingVariable','DoY');
tt15.MoY = month(tt15.Date);
tt15.DoM = day(tt15.Date);
tt15.WoY = week(tt15.Date);
tt16 = timetable2table(tt15,'ConvertRowTimes',false);
tt16 = varfun(@sum,tt16,'GroupingVariables',{'WoY' 'MoY' 'DoM'});
leapDayRows = (tt16.MoY==2) & (tt16.DoM==29);
tt16(leapDayRows,:) = [];
tt17 = varfun(@sum,tt16,'GroupingVariable','WoY') 
%2013
tt18 = readtable('BackupByZipCode1.xlsx');
tt19=table2timetable(tt18)
tt19.ZIPCODE = categorical(tt19.ZIPCODE);
tt19.Dummy = ones(height(tt19),1);
tt20 = unstack(tt19,'Dummy','ZIPCODE');
tt20 = fillmissing(tt20,'Constant',0);
caldiff(tt19.Date([1 end]),'days')
t2 = datetime(2013,1,1):caldays(1):datetime(2013,12,31);
tt21 = retime(tt20,t2,'FillWithConstant','Constant',0);
tt21.DoY = day(tt21.Date,'dayofyear');
tt22 = timetable2table(tt21,'ConvertRowTimes',false);
tt22 = varfun(@sum,tt22,'GroupingVariable','DoY');
tt21.MoY = month(tt21.Date);
tt21.DoM = day(tt21.Date);
tt21.WoY = week(tt21.Date);
tt22 = timetable2table(tt21,'ConvertRowTimes',false);
tt22 = varfun(@sum,tt22,'GroupingVariables',{'WoY' 'MoY' 'DoM'});
leapDayRows = (tt22.MoY==2) & (tt22.DoM==29);
tt22(leapDayRows,:) = [];
tt23 = varfun(@sum,tt22,'GroupingVariable','WoY') 
%2014
tt24 = readtable('BackupByZipCode1.xlsx');
tt25=table2timetable(tt24)
tt25.ZIPCODE = categorical(tt25.ZIPCODE);
tt25.Dummy = ones(height(tt25),1);
tt26 = unstack(tt25,'Dummy','ZIPCODE');
tt26 = fillmissing(tt26,'Constant',0);
caldiff(tt25.Date([1 end]),'days')
t3 = datetime(2014,1,1):caldays(1):datetime(2014,12,31);
tt27 = retime(tt26,t3,'FillWithConstant','Constant',0);
tt27.DoY = day(tt27.Date,'dayofyear');
tt28 = timetable2table(tt27,'ConvertRowTimes',false);
tt28 = varfun(@sum,tt28,'GroupingVariable','DoY');
tt27.MoY = month(tt27.Date);
tt27.DoM = day(tt27.Date);
tt27.WoY = week(tt27.Date);
tt28 = timetable2table(tt27,'ConvertRowTimes',false);
tt28 = varfun(@sum,tt28,'GroupingVariables',{'WoY' 'MoY' 'DoM'});
leapDayRows = (tt28.MoY==2) & (tt28.DoM==29);
tt28(leapDayRows,:) = [];
tt29 = varfun(@sum,tt28,'GroupingVariable','WoY') 
%2015
tt30 = readtable('BackupByZipCode1.xlsx');
tt31=table2timetable(tt30)
tt31.ZIPCODE = categorical(tt31.ZIPCODE);
tt31.Dummy = ones(height(tt31),1);
tt32 = unstack(tt31,'Dummy','ZIPCODE');
tt32 = fillmissing(tt32,'Constant',0);
caldiff(tt31.Date([1 end]),'days')
t4 = datetime(2015,1,1):caldays(1):datetime(2015,12,31);
tt33 = retime(tt32,t4,'FillWithConstant','Constant',0);
tt33.DoY = day(tt33.Date,'dayofyear');
tt34 = timetable2table(tt33,'ConvertRowTimes',false);
tt34 = varfun(@sum,tt34,'GroupingVariable','DoY');
tt33.MoY = month(tt33.Date);
tt33.DoM = day(tt33.Date);
tt33.WoY = week(tt33.Date);
tt34 = timetable2table(tt33,'ConvertRowTimes',false);
tt34 = varfun(@sum,tt34,'GroupingVariables',{'WoY' 'MoY' 'DoM'});
leapDayRows = (tt34.MoY==2) & (tt34.DoM==29);
tt34(leapDayRows,:) = [];
tt35 = varfun(@sum,tt34,'GroupingVariable','WoY') 
%2016
tt36 = readtable('BackupByZipCode1.xlsx');
tt37=table2timetable(tt36)
tt37.ZIPCODE = categorical(tt37.ZIPCODE);
tt37.Dummy = ones(height(tt37),1);
tt38 = unstack(tt37,'Dummy','ZIPCODE');
tt38 = fillmissing(tt38,'Constant',0);
caldiff(tt37.Date([1 end]),'days')
t5 = datetime(2016,1,1):caldays(1):datetime(2016,12,31);
tt39 = retime(tt38,t5,'FillWithConstant','Constant',0);
tt39.DoY = day(tt39.Date,'dayofyear');
tt40 = timetable2table(tt39,'ConvertRowTimes',false);
tt40 = varfun(@sum,tt40,'GroupingVariable','DoY');
tt39.MoY = month(tt39.Date);
tt39.DoM = day(tt39.Date);
tt39.WoY = week(tt39.Date);
tt40 = timetable2table(tt39,'ConvertRowTimes',false);
tt40 = varfun(@sum,tt40,'GroupingVariables',{'WoY' 'MoY' 'DoM'});
leapDayRows = (tt40.MoY==2) & (tt40.DoM==29);
tt40(leapDayRows,:) = [];
tt41 = varfun(@sum,tt40,'GroupingVariable','WoY') 
%2017
tt42 = readtable('BackupByZipCode1.xlsx');
tt43=table2timetable(tt42)
tt43.ZIPCODE = categorical(tt43.ZIPCODE);
tt43.Dummy = ones(height(tt43),1);
tt44 = unstack(tt43,'Dummy','ZIPCODE');
tt44 = fillmissing(tt44,'Constant',0);
caldiff(tt43.Date([1 end]),'days')
t6 = datetime(2017,1,1):caldays(1):datetime(2017,12,31);
tt45 = retime(tt44,t6,'FillWithConstant','Constant',0);
tt45.DoY = day(tt45.Date,'dayofyear');
tt46 = timetable2table(tt45,'ConvertRowTimes',false);
tt46 = varfun(@sum,tt46,'GroupingVariable','DoY');
tt45.MoY = month(tt45.Date);
tt45.DoM = day(tt45.Date);
tt45.WoY = week(tt45.Date);
tt46 = timetable2table(tt45,'ConvertRowTimes',false);
tt46 = varfun(@sum,tt46,'GroupingVariables',{'WoY' 'MoY' 'DoM'});
leapDayRows = (tt46.MoY==2) & (tt46.DoM==29);
tt46(leapDayRows,:) = [];
tt47 = varfun(@sum,tt46,'GroupingVariable','WoY') 
%2018
tt48 = readtable('BackupByZipCode1.xlsx');
tt49=table2timetable(tt48)
tt49.ZIPCODE = categorical(tt49.ZIPCODE);
tt49.Dummy = ones(height(tt49),1);
tt50 = unstack(tt49,'Dummy','ZIPCODE');
tt50 = fillmissing(tt50,'Constant',0);
caldiff(tt49.Date([1 end]),'days')
t7 = datetime(2018,1,1):caldays(1):datetime(2018,12,31);
tt51 = retime(tt50,t7,'FillWithConstant','Constant',0);
tt51.DoY = day(tt51.Date,'dayofyear');
tt52 = timetable2table(tt51,'ConvertRowTimes',false);
tt52 = varfun(@sum,tt52,'GroupingVariable','DoY');
tt51.MoY = month(tt51.Date);
tt51.DoM = day(tt51.Date);
tt51.WoY = week(tt51.Date);
tt52 = timetable2table(tt51,'ConvertRowTimes',false);
tt52 = varfun(@sum,tt52,'GroupingVariables',{'WoY' 'MoY' 'DoM'});
leapDayRows = (tt52.MoY==2) & (tt52.DoM==29);
tt52(leapDayRows,:) = [];
tt53 = varfun(@sum,tt52,'GroupingVariable','WoY') 
%2019
tt54 = readtable('BackupByZipCode1.xlsx');
tt55=table2timetable(tt54)
tt55.ZIPCODE = categorical(tt55.ZIPCODE);
tt55.Dummy = ones(height(tt55),1);
tt56 = unstack(tt55,'Dummy','ZIPCODE');
tt56 = fillmissing(tt56,'Constant',0);
caldiff(tt55.Date([1 end]),'days')
t8 = datetime(2019,1,1):caldays(1):datetime(2019,12,31);
tt57 = retime(tt56,t8,'FillWithConstant','Constant',0);
tt57.DoY = day(tt57.Date,'dayofyear');
tt58 = timetable2table(tt57,'ConvertRowTimes',false);
tt58 = varfun(@sum,tt58,'GroupingVariable','DoY');
tt57.MoY = month(tt57.Date);
tt57.DoM = day(tt57.Date);
tt57.WoY = week(tt57.Date);
tt58 = timetable2table(tt57,'ConvertRowTimes',false);
tt58 = varfun(@sum,tt58,'GroupingVariables',{'WoY' 'MoY' 'DoM'});
leapDa
yRows = (tt58.MoY==2) & (tt58.DoM==29);
tt58(leapDayRows,:) = [];
tt59 = varfun(@sum,tt58,'GroupingVariable','WoY')

dpb 2020-6-24

在 MATLAB Online 中打开

t=[];
...
t=[t;tt5];
...
t=[t;tt11];
...
t=[t;tt17];
...

Or, you can just string 'em all out in the end.

Realistically, the whole thing ought to be trashed and rewritten...

CMatlabWold 2020-6-25

Thanks! About the code... Yes, I know

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Putting Timetables Together to Create One Large Table

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