The number type has a step value controlling which numbers are valid (along with max and min), which defaults to 1. This value is also used by implementations for the stepper buttons (i.e. pressing up increases by step). Simply change this value to whatever is appropriate. For money, two decimal places are probably expected: <label … Read more
(Math.round(num * 100) / 100).toFixed(2); Live Demo var num1 = “1”; document.getElementById(‘num1’).innerHTML = (Math.round(num1 * 100) / 100).toFixed(2); var num2 = “1.341”; document.getElementById(‘num2’).innerHTML = (Math.round(num2 * 100) / 100).toFixed(2); var num3 = “1.345”; document.getElementById(‘num3’).innerHTML = (Math.round(num3 * 100) / 100).toFixed(2); span { border: 1px solid #000; margin: 5px; padding: 5px; } <span id=”num1″></span> <span id=”num2″></span> … Read more
Because floats and doubles cannot accurately represent the base 10 multiples that we use for money. This issue isn’t just for Java, it’s for any programming language that uses base 2 floating-point types. In base 10, you can write 10.25 as 1025 * 10-2 (an integer times a power of 10). IEEE-754 floating-point numbers are … Read more
Welcome to the world of denormalized floating-point! They can wreak havoc on performance!!! Denormal (or subnormal) numbers are kind of a hack to get some extra values very close to zero out of the floating point representation. Operations on denormalized floating-point can be tens to hundreds of times slower than on normalized floating-point. This is … Read more
For non-negative (unsigned) integers only, use isdigit(): >>> a = “03523” >>> a.isdigit() True >>> b = “963spam” >>> b.isdigit() False Documentation for isdigit(): Python2, Python3 For Python 2 Unicode strings: isnumeric().
You are running into the old problem with floating point numbers that not all numbers can be represented exactly. The command line is just showing you the full floating point form from memory. With floating point representation, your rounded version is the same number. Since computers are binary, they store floating point numbers as an … Read more
Because Floating Point Math is not Associative. The way you group the operands in floating point multiplication has an effect on the numerical accuracy of the answer. As a result, most compilers are very conservative about reordering floating point calculations unless they can be sure that the answer will stay the same, or unless you … Read more
float and double are floating binary point types (float is 32-bit; double is 64-bit). In other words, they represent a number like this: 10001.10010110011 The binary number and the location of the binary point are both encoded within the value. decimal is a floating decimal point type. In other words, they represent a number like … Read more
>>> a = “545.2222” >>> float(a) 545.22220000000004 >>> int(float(a)) 545
Binary floating point math is like this. In most programming languages, it is based on the IEEE 754 standard. The crux of the problem is that numbers are represented in this format as a whole number times a power of two; rational numbers (such as 0.1, which is 1/10) whose denominator is not a power … Read more