Why code fail to bootstrap when points lower than a certain limit?

Hi everyone,

My script stop bootstraping when the observtions are lower than a certain limit. May someoen suggets how can i fix this or what are the other possible wayes to bootstrap and computing 99%, 95% and 68% or 50% of the bootsrap population? (data is also attached)

ss = readmatrix('data.csv');

nBoot=2000;
for i=1:148;
    bb=ss(:,i);
    X = bb(~isnan(bb));
    [bci(:,i),bmeans(:,i)] = bootci(nBoot,{@mean,X},'alpha',.23,'type','per');
    bmu(i,1) = mean(bmeans(:,i)); 
end
R_bound=bci';
R_mean=bmu;
R_upper=R_bound(:,2);
R_lower=R_bound(:,1);

(The dataset consist of numbers and NaN values, after removing NaN the actual values for bootsrap within each colum are varies between 2 to 40. However, the code stop wokring when the total enteries are lower than 2). For example, the above code working when i remove few columns with low data points

ss = readmatrix('data.csv');
ss(:,[15, 17, 18, 35, 36, 45]) = []; % removing columns with few data points. 
nBoot=2000;
for i=1:142;
    bb=ss(:,i);
    X = bb(~isnan(bb));
    [bci(:,i),bmeans(:,i)] = bootci(nBoot,{@mean,X},'alpha',.23,'type','per');
    bmu(i,1) = mean(bmeans(:,i)); 
end
R_bound=bci';
R_mean=bmu;
R_upper=R_bound(:,2);
R_lower=R_bound(:,1);

May someone help me out here.

Thank you!