restructure data table based on date and other categorical variables

I have a data table with 4 variables: d18O (water chemistry measurement), Site, Date and Depth

Site, Date and Depth are all categorical. d18O is the data.

I'm wondering if there is an efficient way to compare d18O collected from the same site, on the same date, at DIFFERENT depths. Some dates do not include d18O collected from multiple depths at the same site, but many do.

I'm completely at a loss of how to code this. I've been doing it manually in excel, but my actual dataset is much larger than what I've attached here and it's extremely inefficient.

Any ideas greatly appreciated.

Answer 1

[Voss]

T = readtable('data_test.csv')

T = 113×4 table
     d18O     Site    Date     Depth
    ______    ____    _____    _____

    -11.57    1004    43773     20  
    -12.63    1004    43773     80  
     -12.8    1004    43802     20  
    -13.01    1004    43802     80  
     -13.9    1004    43838     20  
    -13.11    1004    43838     80  
    -13.99    1004    43865     20  
    -12.97    1004    43865     80  
    -13.98    1004    43899     20  
    -12.94    1004    43899     80  
    -13.29    1004    43927     20  
    -13.11    1004    43927     80  
    -12.87    1004    43959     20  
    -12.99    1004    43959     80  
    -11.84    1004    43984     20  
    -11.59    1004    43984     20  

T_summary = groupsummary(T,{'Site','Date'},@(x){x},{'d18O','Depth'});
T_summary = removevars(T_summary,'GroupCount');
T_summary = renamevars(T_summary,{'fun1_d18O','fun1_Depth'},{'d18O','Depth'})

T_summary = 64×4 table
    Site    Date         d18O           Depth    
    ____    _____    ____________    ____________

    1004    43773    {2×1 double}    {2×1 double}
    1004    43802    {2×1 double}    {2×1 double}
    1004    43838    {2×1 double}    {2×1 double}
    1004    43865    {2×1 double}    {2×1 double}
    1004    43899    {2×1 double}    {2×1 double}
    1004    43927    {2×1 double}    {2×1 double}
    1004    43959    {2×1 double}    {2×1 double}
    1004    43984    {3×1 double}    {3×1 double}
    1004    44018    {2×1 double}    {2×1 double}
    1004    44075    {2×1 double}    {2×1 double}
    1004    44102    {[-11.5600]}    {[      20]}
    1004    44144    {2×1 double}    {2×1 double}
    1004    44166    {2×1 double}    {2×1 double}
    1004    44204    {2×1 double}    {2×1 double}
    1004    44235    {2×1 double}    {2×1 double}
    1004    44263    {2×1 double}    {2×1 double}