Mathematical Formulae

or just round($value,2)

You guys are almost there.

0.213333333333 gives me 0.21

I wanted 0.22 as the result.

Even if the value is 0.01123, I need the result to be 0.02 after applying the function or round.

If you want to round up, use ceil instead of round

I don't think ceil() will work because that result is always an integer.

ceil($value*100)/100
instead of
round($value*100)/100

You can always round up this way using ceil()

$out = ceil(($value*100))/100;

But note that 0.01 is not represented exactly in IEEE Standard 754 Floating-Point
so when you think you are passing it 0.07 you may really be passing it
0.070000000000000006661338147751

ceil(($value*100))/100; works to a certain extend.

Results:
0.0533333333333 gives me 0.06, which is what I wanted.

The problem is with other results generated, 0.72 gives me 0.73 and 0.24 gives me 0.25. These should stay at 0.72 or 0.24.

The other noticeable ones are 0.48 becomes 0.49, 0.56 becomes 0.57. Seem to be happening to results with 2 decimal places.

Some results are correct though, like 0.08 stays at 0.08

In  IEEE Standard 754 single precision Floating-Point the closest representable value to 0.72 is
.7200000286102294921875

If you need exact values, you should not be using floating point.
Can you work in pennies instead of pounds or dollars and use integers?

If you can guarantee, for example, that you will never need to distinguish between
0.72 and 0.720001
then you may be able to manage with something like

round($value*100+0.499999)/100

But that will also fail at some point.
For example, if you use single precision IEEE Standard 754 Floating-Point,
10000.720002 will be indistinguishable from 10000.72
If you know what you can guarantee in terms of how close a number can be without rounding up, and what the range of numbers you need to be able to handle, and the precision of the floating point numbers you are using, we may be able to suggest an appropriate threshold, but remember

“Floating point computation is by nature inexact, and programmers can easily misuse it so that the computed answers consist almost entirely of “noise.” One of the
principal problems of numerical analysis is to determine how accurate the results of
certain numerical methods will be. There is a “credibility-gap”: We don’t know how
much of the computer’s answers to believe. Novice computer users solve this problem
by implicitly trusting in the computer as an infallible authority; they tend to believe
that all digits of a printed answer are signi¿cant. Disillusioned computer users have
just the opposite approach; they are constantly afraid that their answers are almost
meaningless.”

See also
https://www.validlab.com/goldberg/paper.pdf

There are mathematical ways to fix this floating point problem, but ozo is absolutely correct that it is inherent in the use of floating point data.

You would need to decide at which decimal point you want to discard the rest.

If you round up .720034, then should you round up .72000000000000034?  How many zeroes are enough before you decide it is .72 rather than .73?

Notes about using float values in PHP (see the large red warning box):
http://php.net/manual/en/language.types.float.php

If you would like to get a tested and working code sample, please follow the guidance of the SSCCE.  In this case, if you can give us a list of the input values and the desired output values, we can show you the exact code to get from input to output.  Obviously the quality of the test data matters, so please feel free to throw in not only the mainstream, but also the edge cases when you make your list.

Erm. Refer to the list below for sample "live" values that I extracted from the database.

0.186666666667 becomes 0.19 <-- correct
0.08 becomes 0.08 <-- correct
0.106666666667 becomes 0.11 <-- correct
0.24 becomes 0.25 <-- wrong (should stay the same value)
0.48 becomes 0.49 <-- wrong (should stay the same value)
0.32 becomes 0.32 <-- correct

In your database, what is the data type of the values?

float?
double?
decimal?

What precision is specified for it?

Ray, you will forever remain as the hero of ee.

Now it goes back to my original problem (the main question).

As I mentioned in the question, I need to round up.

Data like 1.011 becomes 1.01. I need it to be 1.02

Or data like 0.21333 becomes 0.21 instead of 0.22


P.s. The roundtoNickle function was from an expert here. It suited my needs back then.

"Data like 1.011 becomes 1.01. I need it to be 1.02"
Should  1.0101 become  1.02?
Should  1.01001 become  1.02?
Should  1.010001 become  1.02?
At some point, if your numbers are represented as floats, there may be a problem defining where you draw the line between 1.01 and 1.02
Depending on how precisely you want to draw that line there may be trade offs we can make to do it with floats, or it may be impossible to do using floats.

for the particular values in your list:

0.186666666667 becomes 0.19 <-- correct
0.08 becomes 0.08 <-- correct
0.106666666667 becomes 0.11 <-- correct
0.24 becomes 0.25 <-- wrong (should stay the same value)
0.48 becomes 0.49 <-- wrong (should stay the same value)
0.32 becomes 0.32 <-- correct

Something like
round($value+.0049,2) may suffice, but there will be other values it will fail on, so unless there are values for which failure is acceptable (perhaps because you can guarantee that you will never see those values) we cannot guarantee a function that works in all cases.

Are you sure you can't work with integer penny values instead of float pound/dollar values?

my original problem (the main question).

To help you any further we need to see the SSCCE.  In this case that would be a set of input values and the expected outputs, along with the rules you want to apply to transform the inputs into the outputs.  A two column layout of the inputs and the corresponding expected outputs would suffice.  Please post that here, and I'll try to help you make sense of it.

However, please note that there are laws about handling money values, so if your rules violate the laws, you may expect a knock at the door.

Sorry for late reply. Long holiday over here. Going to accept multiple solutions.