Javascript weird addition [duplicate] - javascript

This question already has answers here:
Is floating point math broken?
(31 answers)
Closed 5 years ago.
Can anyone answer me why javascript adds up 1.123460 + 0.112210 as 1.2356699999999998
while no way I can come up with that result by manual calculation or by any other compilers..
Am I going crazy or javascript, cannot figure out

Its just how JavaScript and many other languages deal with floats. Rounding them to 15 decimal places. Check this How to deal with floating point number precision in JavaScript? How to deal with floating point number precision in JavaScript?

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Reduce or solve calculative errors in Javascript [duplicate]

This question already has answers here:
How to deal with floating point number precision in JavaScript?
(47 answers)
Closed 1 year ago.
Sometimes simple algebra can result in floating accuracy errors.
in this case, I encountered 12 * 1.6 which resulted in 19.20000000003
Is there a way to catch this issue or prevent it from happening?
Accuracy is highly important so simply rounding or truncation would not be enough.
No. Its the nature of floating point arithmetic. You only have so much accuaracy.
https://en.wikipedia.org/wiki/Floating-point_arithmetic

Weird result in decimal math operation in Javascript [duplicate]

This question already has answers here:
Is floating point math broken?
(31 answers)
Closed 4 years ago.
Hi I am doing following operation in Javascript and I am getting weird results, can someone tell me what is going on.
5.62-6.18+0.56 = 4.440892098500626e-16
Because of floating point inaccuracies, the result isn't exactly zero. JavaScript uses scientific notation to display numbers as small as this one. You might be interested in the toPrecision() method.

Incorrect Calc in JavaScript [duplicate]

This question already has answers here:
How to deal with floating point number precision in JavaScript?
(47 answers)
Is floating point math broken?
(31 answers)
Closed 5 years ago.
I'm trying to run the following calculation in JavaScript, 78.98 * 10 and the result returned is always 789.8000000000001 My question is where did that 0.0000000000001 come from?
I tried on several calculators, and that 0.0000000000001 should not be there. I did inclusive tests in other programming languages.
My question is, is there a logical explanation for this? If it is an error in the JavaScript engine where I notify?
Thank you.

Javascript eval returning wrong value [duplicate]

This question already has answers here:
How to deal with floating point number precision in JavaScript?
(47 answers)
Closed 6 years ago.
I am trying to use eval() for calculator i am making, but if when i try this
console.log(eval("5.2-5"));
It returns
0.20000000000000018
Why is this happening.Thank you for your time.
This is due to how Javascript handles floating point precision. Please see How to deal with floating point number precision in JavaScript? for more information
Short answer: Due to the nature of how computers process floats, this means floating point accuracy actually breaks down past a certain point. This is what you're seeing.
Javascript evaluates "5.2-2" to a floating point number, which precision is not guaranteed.
If you need a fixed precision you could use
console.log(eval("5.2-5.0").toFixed(2)):

Problems with the calculation JavaScript [duplicate]

This question already has answers here:
Is floating point math broken?
(31 answers)
Closed 9 years ago.
test there in their consoles browser
1067.11-1000 = 67.1099999999999
but the correct thing 67.11
can even test the calculator windows ..
could someone explain this to me?
Floating point numbers are stored using base2, this creates small differences like the one you demonstrate above when converting to base10. The difference will be even greater if use the following numbers: 1000000067.11 - 1000000000 = 67.1100000143. This is because the level of precision decreases as the numbers calculated increases.
Lack of precision is the main disadvantage of the float type numbers - some real numbers can only be represented approximately.
You can follow this link to learn more about representation of floating point format

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