Effacer les filtres
Effacer les filtres

How can I find a corresponding data value to a text value?

1 vue (au cours des 30 derniers jours)
Quinty van der Heijden
Quinty van der Heijden le 9 Fév 2022
Commenté : dpb le 15 Fév 2022
I read an Excel file which contains text and numerical data. It looks like this:
For each trial I have to see whether there is a looking ('yes') and eventually add up the durations of all the yesses for each trial.
I found the correct trial with the following code:
T = readcell(BehDataParticipant2);
T_trial1 = strcmp(T, 'Trial 1');
It resulted in zeros and ones throughout the whole table. But now I don't know how to find a 'yes' and the corresponding duration in those corresponding rows. Can you help me? Thanks!

Réponse acceptée

dpb
dpb le 9 Fév 2022
tToy=readtable(BehDataParticipant2,'ReadVariableNames',1,'VariableNamingRule','preserve');
tToy.LookLeftToy=categorical(tToy.LookLeftToy);
tToySummary=groupsummary(tToy,tToy.LookLeftToy,'sum',tToy.("Duration - msec"))
  6 commentaires
Quinty van der Heijden
Quinty van der Heijden le 15 Fév 2022
I'm sorry, was thinking too difficult. But I get it now, thanks!
dpb
dpb le 15 Fév 2022
Understand...is easy to do when still learning one's way around in MATLAB.
I've observed it is the penchant to also want to create new, external variables from the table containing the data to work with instead of using the table reference to the data in the table directly. As a general practice, try to avoid making unneccessary copies of data you already have; there's an extensive section in the documentation on tables on how to reference table data that is invaluable and mandatory reading to use tables effectively -- and for disparate data types and convenience in higher-level coding abstraction, the table is about the alpha dog in the pack of tools available in MATLAB.

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Plus de réponses (1)

DGM
DGM le 9 Fév 2022
Modifié(e) : DGM le 9 Fév 2022
Create the masks only over the relevant columns. Then use a logical combination of the masks to select the entries from the first column.
T = {1180, 'Trial 1', 'yes';
1150, 'Trial 1', [];
860, 'Trial 1', 'yes';
1350, 'Trial 2', 'yes';
940, 'Trial 2', 'yes'};
maskt1 = strcmpi(T(:,2),'trial 1');
maskt2 = strcmpi(T(:,2),'trial 2');
maskyn = strcmpi(T(:,3),'yes');
maskedvalues1 = cell2mat(T(maskt1 & maskyn,1))
maskedvalues1 = 2×1
1180 860
maskedvalues2 = cell2mat(T(maskt2 & maskyn,1))
maskedvalues2 = 2×1
1350 940

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