MATLAB: One measure greater than another

differenceseasy to answergreater thanlesser than

Hi All,

I have a 697 x 38 which has different column headings such as 'startf, maxf, etc'.

I'm wanting to check if my measurements are true (an answer of 1 indiciting not true?) such that;

startf>fmax

startf<fmax etc..

Currently, I've sectioned off the columns of interests:

T = PWALLVOCSPARTSOFBIPHON
Wanted = T(:,'SFStartFreqHzoffundamental')
Wanted1 = T(:,'MaxFHzfundamental'

I now want to check if wanted is greater than wanted1

I tried:

Wanted > Wanted1 ans =

but thats just producing an error.

In addition, if the answers were shown to be untrue. Such as I have data of a start frequency that is lower than minimum frequency, how do i find which rows these will be located in?

Best Answer

Note than an even simpler way to extract data from a table is with dot indexing:

Wanted = T.SFStartFreqHzoffundamental;  %equivalent to T{:,'SFStartFreqHzoffundamental'}
Wanted1 = T.MaxFHzfundamental;          %equivalent to T{:,'MaxFHzfundamental'}
mask = Wanted > Wanted1;

To keep only the portion of the table for whick mask is true:

Tinvalid = T(mask, :)  %Not that this returns a table since we're using () indexing

which can be done in only one line:

Tinvalid = T(T.SFStartFreqHzoffundamental > T.MaxFHzfundamental, :)

If you want to know the row indices, use find:

invalidrows = find(T.SFStartFreqHzoffundamental > T.MaxFHzfundamental)

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MATLAB: Finding the percentage of NaN cells in columns

This does everything for all the tables in ‘C’:

D = load('C.mat');
C = D.C;
for k = 1:numel(C)
    C{k}(:,1:4) = fillmissing(C{k}(:,1:4),'nearest');                           % Fills Missing Data
    filename = C{k}{1,2};                                                       % Input Table Name
    fn{k,:} = sprintf('%s.xlsx',filename{:});                                   % Output File Name
    writetable(C{k},sprintf('%s.xlsx',filename{:}))                             % Write Each Table To Separate File
    rowlen{k,:} = size(C{k}(:,9:12),1);                                         % Row Lengtth Of Each Table
    NaN912{k,:} = [varfun(@isnan,C{k}(:,9:12))];                                % Number Of ‘NaN’ Values In Each Table
    PctNaN(k,:) = table2array(varfun(@(x)sum(x)./size(x,1),NaN912{k,:}));       % Percent ‘NaN’ Values In Selected Variables (Columns)
end
VarNms = compose('NAN in %s', string(C{1}.Properties.VariableNames(:,9:12)));   % Variable Names For ‘NaNPercent’ Table
filnam = cell2table(fn,'VariableNames',{'File name'});                          % File Names Table
NaNPercent = array2table(PctNaN, 'VariableNames',VarNms);                       % ‘PctNaN’ Initial Table
NaNPercent = [filnam NaNPercent];                                               % ‘PctNaN’ Final (Output) Table
FirstTen = NaNPercent(1:10,:)                                                   % Display Sample (Delete)

Producing:

FirstTen =
  10×5 table
           File name           NAN in tmax_m    NAN in tmin_m    NAN in rrr24    NAN in tm_m
    _______________________    _____________    _____________    ____________    ___________
    {'Abadan.xlsx'        }      0.088235           0.1299          0.13971         0.1152  
    {'Abadeh.xlsx'        }       0.10539          0.13235           0.1299        0.19118  
    {'Abali.xlsx'         }       0.12162          0.12162          0.15315        0.15766  
    {'Abumusa Island.xlsx'}        0.1464          0.14865          0.11486        0.16892  
    {'Ahar.xlsx'          }       0.21171           0.2027          0.21396        0.24099  
    {'Ahvaz.xlsx'         }      0.051471         0.058824         0.058824       0.056373  
    {'Aligudarz.xlsx'     }        0.1982          0.22523          0.23198        0.23874  
    {'Anar.xlsx'          }       0.22297          0.18919          0.19369        0.23649  
    {'Arak.xlsx'          }      0.068627         0.078431         0.088235       0.093137  
    {'Ardakan (Yazd).xlsx'}       0.21114          0.20882          0.34339         0.2065

The code retains the original data in ‘rowlen’ and ‘NaN912’ as well as the percent NaN results in the ‘NaNPercent’ table.

MATLAB: How to join text in a table cell

Your whole process of adding a new column and detecting your excess threshold is overly complicated. There is certainly never any need to convert to a matrix.

%demo/test data
Table = array2table(randi([0 150], 69, 4), 'VariableNames', {'something', 'W', 'X', 'N'})
colnames = Table.Properties.VariableNames(2:4);  %asumming you only want to test column 2:4
warnings = rowfun(@(val) {strjoin(colnames(val > 100), ',')}, ...
                  Table, ...
                  'InputVariables', 2:4, ...
                  'OutputVariableNames', 'Warning', ...
                  'SeparateInputs', false);
Table = [warnings, Table]

I've separated the rowfun call onto several lines for readability.

In the above, I call rowfun to process each row one at a time. 'InputVariables' tells it which columns to process (2 to 4), 'OutputVariableNames' tells it which name to give to the output column, 'SeparateInputs', false tells it to keep the values of columns 2:4 together as a vector (easier to process).

The processing function I'm giving to rowfun is an anonymous function which one input val. That val will receive columns 2:4 of each row as a vector. I compare the values of this vector to your threshold. This gives me a logical vector that is used to filter the columns names. I then join these filtered column names together into one char array with strjoin and finally wrap that into a cell array so that it can be put into a table column.

P.S: Please give a better name to your table and to columns M, X, N. Something that actually explain what's in there. Yearlysomething would be a better name for the table, whatever that something is.

Best Answer

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MATLAB: Finding the percentage of NaN cells in columns

MATLAB: How to join text in a table cell

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