Here's how I'd import your data.
opts = detectImportOptions('see.csv'); %let matlab figure out the format of the file.
opts = opts.setvaropts(1, 'Type', 'datetime', 'InputFormat', 'uuuu/MM/dd', 'DatetimeFormat', 'dd/MM/uuuu HH:mm:ss'); %however matlab doesn't detect the first input as datetime
opts.VariableNames = {'DateTime', 'Time', 'Something'}; %give the variable names some more useful names. If the csv file had a header matlab would automatically use it to name the variables
something = readtable('see.csv', opts); %import as table. Obviously use a different name for the output.
something.DateTime = something.DateTime + something.Time; %merge date and time into one datetime
something.Time = []; %and get rid of the time column now that it is part of the date
something.DateTime = dateshift(something.DateTime, 'start', 'hour', 'nearest'); %shift to the nearest hour
something.Something = fillmissing(something.Something, 'linear');
With regards to the fillmissing, considering your numbers are all near 0, it's no wonder you get negative numbers when using cubic interpolation. If you don't want that, use a different fill method.
However, are you sure that you really want to round the time to the nearest hour without affecting the values in the 3rd column? Instead you may want to convert the table to a timetable (at the step before the dateshift, then retime the timetable to hourly:
%.. same code as before up to:
something.Time = [];
something = table2timetable(something);
something = retime(something, 'hourly', 'spline'); %or some other interpolation method
