A compact way to reduce, or remove, the fractional part (separated by a decimal point) of numbers in a table

Question

Sim 2023-11-27

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https://ww2.mathworks.cn/matlabcentral/answers/2052447-a-compact-way-to-reduce-or-remove-the-fractional-part-separated-by-a-decimal-point-of-numbers-in

评论： Sim 2023-11-27

Given a table, could you please suggest a compact way to reduce, or remove, the fractional part (separated by a decimal point) of numbers within that table?

Note: Here following, I create a table given some inputs (i.e. Feature 1 and Feature 2) just to show an example, but in my "real" case I would have huge tables directly read from files and I would need a way/method to reduce the decimals just by manipulating the table (indeed, I would have difficulties to extract the inputs from those files, and I would need/prefer to work on the tables):

LastName = {'Paris';'London'};
Feature1 = [71.4589;69.1432];
Feature2 = [176.3458;163.9082];
T = table(Feature1,Feature2);
T.Properties.RowNames = LastName; 

For example, from this:

T
T = 2×2 table
              Feature1    Feature2
              ________    ________

    Paris      71.459      176.35 
    London     69.143      163.91 

to this:

T =
  2×2 table
              Feature1    Feature2
              ________    ________
    Paris        71         176   
    London       69         163   

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Answer 1

Dyuman Joshi 2023-11-27

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https://ww2.mathworks.cn/matlabcentral/answers/2052447-a-compact-way-to-reduce-or-remove-the-fractional-part-separated-by-a-decimal-point-of-numbers-in#answer_1360487

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Take the floor of the data.

LastName = {'Paris';'London'};
Feature1 = [71.4589;69.1432];
Feature2 = [176.3458;163.9082];
T = table(Feature1,Feature2);
T.Properties.RowNames = LastName;
%Applying directly to the whole table
T1 = floor(T)
T1 = 2×2 table
              Feature1    Feature2
              ________    ________

    Paris        71         176   
    London       69         163   

%Applying to certain columns/variables
T2 = floor(T(:,1:2))
T2 = 2×2 table
              Feature1    Feature2
              ________    ________

    Paris        71         176   
    London       69         163   