Day wise diurnal plot not the average diurnal plot

I need help! I need to plot day wise diurnal for each days not the average diurnal for around 30 days of dataset. I have 36 columns and 550 rows in my data matrix. I was thinking to extract day wise data into separate wave and also the corresponding time series from the raw time series wave. But I am the beginner in Igor, I have no idea how to write it.

I have attached an example for the plot. I have also attached my Igor experiment.

Please help me!

test.pxp

I'm not entirely sure what you want to do, but be aware that you can use wave subranges for plotting. If you wanted to plot Al for Jan 14th (if I understand your data correctly) you could execute:

display data[1,24][0] vs t_series[1,24]

A neat little thing to know is the feature dimension labels, i.e.

DisplayHelpTopic "Dimension Labels"

If employed, you could make the code more readable:

display data[1,24][%Al] vs t_series[1,24]

 If you want to split the dataset use e.g.

Duplicate/O/R=[1,24][] data, Jan14

 

 

In reply to by ChrLie

Thanks ChrLie! I want to plot everyday diurnal  i.e. 0 to 24 hr from Jan 14 until Feb 9, for Al in a plot and do the same for other elements. I do not want to execute the codes (you have mentioned above ) several times for each day by AppendToGraph but to write a procedure code to execute it and produce these graphs. I hope this is clear now.

The difficult part is to organize your data day-wise because your input wave is not regularly spaced.

However, if your data is split into individual days you can use something like:

function ShowData(ListOfDays, col)
    string ListOfDays
    variable col
       
    variable nSubsets = ItemsInList(ListOfDays)
    variable i
    string wName =""
   
    Display
    for(i=0; i<nSubsets; i+=1)
        wName = StringFromList(i, ListOfDays)
        wave w = $wName
        AppendToGraph   w[][col]
    endfor
end

 Then call it from the command line, e.g.

ShowData("Day_0;Day_1;Day_2", 3) // 3 for sulfur

 

In reply to by ChrLie

Thank again! I will do it for some elements suggested by you but still it seems a bit of manual work. Indeed, I do not have systematic time series. Let's see if I get some more comments.