Get and interpolate missed daily data

Question

Stefania Avvedimento 2022-3-14

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此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/1671079-get-and-interpolate-missed-daily-data

评论： Peter Perkins 2022-3-14

missed data.xlsx

Hi all,

I am working with daily climate data for future projections on a basin catchment (see file attached). I just noticed that the daily precipitation data are reported considering all months of 30 days. So, I need to add rows for month of 31 days (January, March, May, July, August, October,December) and delete row for the month of February (in this case also considering the 29 days for 2032, 2036, 2040, 2044, 2048, 2052, 2056, 2060). Is there any way to automatize the process?

Also how can I interpolate the missing data?

Thanks

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Answer 1

Peter Perkins 2022-3-14

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https://ww2.mathworks.cn/matlabcentral/answers/1671079-get-and-interpolate-missed-daily-data#answer_917264

编辑：Peter Perkins 2022-3-14

在 MATLAB Online 中打开

Tis is a one-liner with timetables and retime:

>> tt = readtimetable("missed data.xlsx")
Warning: Column headers from the file were modified to make them valid MATLAB identifiers before creating variable names for the table. The original column headers are saved in the VariableDescriptions property.
Set 'VariableNamingRule' to 'preserve' to use the original column headers as table variable names. 
tt =
  11158×3 timetable
       Date         Lat       Lon      Prec_mm_day_
    ___________    ______    ______    ____________
    01-Jan-2030    45.341    8.7889             0  
    02-Jan-2030    45.341    8.7889             0  
    03-Jan-2030    45.341    8.7889        3.0156  
[snip]
    28-Dec-2060    45.341    8.7889             0  
    29-Dec-2060    45.341    8.7889             0  
    30-Dec-2060    45.341    8.7889             0  

((In older releases of MATLAB, use readtable and table2timetable.) There are a bunch of NaT's in the times, where the data is "at" Feb 29 in a non-leap year and Feb 30 in any year. TGhose are easy to delete.

>> tt(415:420,:)
ans =
  11×3 timetable
       Date         Lat       Lon      Prec_mm_day_
    ___________    ______    ______    ____________
    27-Feb-2031    45.341    8.7889       0.30469  
    28-Feb-2031    45.341    8.7889             0  
    NaT            45.341    8.7889     0.0078125  
    NaT            45.341    8.7889             0  
    01-Mar-2031    45.341    8.7889     0.0078125  
    02-Mar-2031    45.341    8.7889             0  
>> tt(ismissing(tt.Date),:) = [];

Now interpolate the missing days.

>> tt2 = retime(tt,"daily","linear")
tt2 =
  11322×3 timetable
       Date         Lat       Lon      Prec_mm_day_
    ___________    ______    ______    ____________
    01-Jan-2030    45.341    8.7889             0  
    02-Jan-2030    45.341    8.7889             0  
    03-Jan-2030    45.341    8.7889        3.0156  
[snip]
    29-Dec-2060    45.341    8.7889             0  
    30-Dec-2060    45.341    8.7889             0  
>> tt(28:33,:)
ans =
  7×3 timetable
       Date         Lat       Lon      Prec_mm_day_
    ___________    ______    ______    ____________
    28-Jan-2030    45.341    8.7889        16.398  
    29-Jan-2030    45.341    8.7889        20.563  
    30-Jan-2030    45.341    8.7889        2.6094  
    01-Feb-2030    45.341    8.7889        4.5938  
    02-Feb-2030    45.341    8.7889       0.14844  
    03-Feb-2030    45.341    8.7889     0.0078125  
>> tt2(28:34,:)
ans =
  7×3 timetable
       Date         Lat       Lon      Prec_mm_day_
    ___________    ______    ______    ____________
    28-Jan-2030    45.341    8.7889        16.398  
    29-Jan-2030    45.341    8.7889        20.563  
    30-Jan-2030    45.341    8.7889        2.6094  
    31-Jan-2030    45.341    8.7889        3.6016  
    01-Feb-2030    45.341    8.7889        4.5938  
    02-Feb-2030    45.341    8.7889       0.14844  
    03-Feb-2030    45.341    8.7889     0.0078125  

The Lat/Lon seem to be constant. I don't know if they should be stored separately, or if this is only art of your data and you have not told us about needing to do this calculation at all your locations.

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Stefania Avvedimento 2022-3-14

The values "0" should be not interpolated since they indicate no rainy days. I only need to interpolate the values of missing day.

Peter Perkins 2022-3-14

My response already shows that the value on the 31st of each long month is interpolated.

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Answer 2

Arif Hoq 2022-3-14

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此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/1671079-get-and-interpolate-missed-daily-data#answer_917049

在 MATLAB Online 中打开

A=(datetime(2030,1,1):datetime(2060,12,31))';  % generating normal date
A1=datenum(A);
C=readtable('missed data.xlsx');
D1=datenum(table2cell(C(:,1)));
E=ismember(A1,D1);   
idx=find(E==0); % index of missing date
F=datetime(A1(idx),'ConvertFrom','datenum')  % missing date