Sort Matlab table, monthly and seasonally. plot mean and trend seasonal map

I am processing ocean and climate data (1982-2022). Here, I have table which having heatwaves events details. Now, I want to sort the data month wise and also seasonal wise (summer:October- February, and winter:March-September), and then i wanted to plot mean seasonal and trend.

Sample file is attached. length of original file may vary in size.

Thanks in addvance.

Answer 1

[Cris LaPierre]

Use sortrows to sort your table.

Create a column of month names using month. Convert them to categorical values and use mergecats to combine these into 2 categories - Summer and Winter.

Share what you have tried so we can help more.

[Gurumoorthi K]

Thanks for you fast response Sir. Actually my quary is not stright forward. Actually, I want to extract the season from the table (40 year data grid by grid event) and save in seperate tables. Then I wanted to calculate mean and trend for each variable presents in the table.

Can you please share the code for exctract the seasonal data (As such copy the data from table: October- February, and March-September and create separate table as summer and winter).

[Cris LaPierre]

I haven't written any code to do that, but I have pointed you to the functions you can use to do that.

You can use logical indexing to identify the dates of interest.

D = (datetime(2020,1,1):calmonths(1):datetime(2022,12,31))';
T = table(D)

T = 36×1 table
         D     
    ___________

    01-Jan-2020
    01-Feb-2020
    01-Mar-2020
    01-Apr-2020
    01-May-2020
    01-Jun-2020
    01-Jul-2020
    01-Aug-2020
    01-Sep-2020
    01-Oct-2020
    01-Nov-2020
    01-Dec-2020
    01-Jan-2021
    01-Feb-2021
    01-Mar-2021
    01-Apr-2021

S = month(T.D)<3 | month(T.D)>9;
W = ~S;

Summer = T(S,:)

Summer = 15×1 table
         D     
    ___________

    01-Jan-2020
    01-Feb-2020
    01-Oct-2020
    01-Nov-2020
    01-Dec-2020
    01-Jan-2021
    01-Feb-2021
    01-Oct-2021
    01-Nov-2021
    01-Dec-2021
    01-Jan-2022
    01-Feb-2022
    01-Oct-2022
    01-Nov-2022
    01-Dec-2022

Winter = T(W,:)

Winter = 21×1 table
         D     
    ___________

    01-Mar-2020
    01-Apr-2020
    01-May-2020
    01-Jun-2020
    01-Jul-2020
    01-Aug-2020
    01-Sep-2020
    01-Mar-2021
    01-Apr-2021
    01-May-2021
    01-Jun-2021
    01-Jul-2021
    01-Aug-2021
    01-Sep-2021
    01-Mar-2022
    01-Apr-2022

You can then use either varfun or groupsummary to compute the mean.

Share the code you have written so we can be more helpful.

[Gurumoorthi K]

Dear Cris LaPierre,

Your code works well. But need some changes for my case. My data MHW is not in regular date, its a heatwaves event (e.g. 2-4 events per year). So ''D'' may not be required. Now, we must use "T or table_in" while using the conditional statement "S". Can you please give me some details?

Note: The dimension of table_in is 197080x9 table.

table_in=MHW;

D = (datetime(1982,1,1):datetime(2020,12,31))';

T = table({table_in});

S = month(T.D)<3 | month(T.D)>9;

W = ~S;

Summer = T(S,:)

Winter = T(W,:)

[Cris LaPierre]

I created a simple example to show you how to use the functions I mentioned in my original post. You already have the date info in your data, so you don't need to create D. However, you do need to convert your data into datetime variables. Try this:

load table_1.mat
MHW3.mhw_onset = datetime(MHW3.mhw_onset,"ConvertFrom","yyyymmdd");
MHW3.mhw_end = datetime(MHW3.mhw_end,"ConvertFrom","yyyymmdd")

MHW3 = 24×9 table
     mhw_onset       mhw_end      mhw_dur    int_max     int_mean     int_var      int_cum    xloc    yloc
    ___________    ___________    _______    ________    ________    __________    _______    ____    ____

    01-Jan-1982    07-Jan-1982       7         1.0344     0.73135       0.20371     5.1194     1       11 
    30-Jan-1982    05-Feb-1982       7         1.3971      1.1062       0.18736     7.7435     1       11 
    12-Jul-1982    25-Jul-1982      14       0.068631     0.05372       0.01268    0.75207     1       11 
    29-Jul-1982    11-Aug-1982      14       0.062454    0.046373      0.010259    0.64922     1       11 
    05-Sep-1982    21-Oct-1982      47       0.069312    0.047799     0.0096679     2.2466     1       11 
    31-Jan-1983    06-Feb-1983       7         1.1801      0.8704       0.16281     6.0928     1       11 
    25-Feb-1983    06-Mar-1983      10        0.63149     0.53797        0.0501     5.3797     1       11 
    24-Jun-1983    28-Jun-1983       5        0.04795    0.045557     0.0047146    0.22778     1       11 
    28-Jul-1983    02-Aug-1983       6       0.045389    0.041644      0.005188    0.24986     1       11 
    25-Aug-1983    01-Sep-1983       8        0.05064    0.043116     0.0070944    0.34493     1       11 
    18-Sep-1983    26-Sep-1983       9         0.0478     0.04056     0.0040666    0.36504     1       11 
    27-Apr-1984    10-May-1984      14        0.13791     0.10205      0.022857     1.4286     1       11 
    23-May-1984    07-Jun-1984      16       0.093507    0.067273      0.012935     1.0764     1       11 
    28-Jun-1984    07-Jul-1984      10       0.058696    0.046507     0.0080467    0.46507     1       11 
    27-Jul-1984    02-Aug-1984       7       0.035929    0.035113    0.00058924    0.24579     1       11 
    09-Oct-1984    17-Oct-1984       9       0.069806    0.055207       0.01051    0.49687     1       11