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  2. Numeric precision in Microsoft Excel - Wikipedia

    en.wikipedia.org/wiki/Numeric_precision_in...

    With some exceptions regarding erroneous values, infinities, and denormalized numbers, Excel calculates in double-precision floating-point format from the IEEE 754 specification [1] (besides numbers, Excel uses a few other data types [2]). Although Excel allows display of up to 30 decimal places, its precision for any specific number is no more ...

  3. Globalize (JavaScript library) - Wikipedia

    en.wikipedia.org/wiki/Globalize_(JavaScript_library)

    Globalize provides number formatting and parsing, date and time formatting and parsing, currency formatting, unit formatting, message formatting (ICU message format pattern), and plural support. Design Goals: Leverages the Unicode CLDR data and follows its UTS#35 specification. Keeps code separate from i18n content.

  4. Single-precision floating-point format - Wikipedia

    en.wikipedia.org/wiki/Single-precision_floating...

    All integers with seven or fewer decimal digits, and any 2 n for a whole number −149 ≤ n ≤ 127, can be converted exactly into an IEEE 754 single-precision floating-point value. In the IEEE 754 standard, the 32-bit base-2 format is officially referred to as binary32; it was called single in IEEE 754-1985.

  5. Decimal floating point - Wikipedia

    en.wikipedia.org/wiki/Decimal_floating_point

    For example, while a fixed-point representation that allocates 8 decimal digits and 2 decimal places can represent the numbers 123456.78, 8765.43, 123.00, and so on, a floating-point representation with 8 decimal digits could also represent 1.2345678, 1234567.8, 0.000012345678, 12345678000000000, and so on.

  6. Decimal data type - Wikipedia

    en.wikipedia.org/wiki/Decimal_data_type

    In the floating-point case, a variable exponent would represent the power of ten to which the mantissa of the number is multiplied. Languages that support a rational data type usually allow the construction of such a value from two integers, instead of a base-2 floating-point number, due to the loss of exactness the latter would cause.

  7. Double-precision floating-point format - Wikipedia

    en.wikipedia.org/wiki/Double-precision_floating...

    Double-precision floating-point format (sometimes called FP64 or float64) is a floating-point number format, usually occupying 64 bits in computer memory; it represents a wide range of numeric values by using a floating radix point. Double precision may be chosen when the range or precision of single precision would be insufficient.

  8. Floating-point arithmetic - Wikipedia

    en.wikipedia.org/wiki/Floating-point_arithmetic

    Since 2 10 = 1024, the complete range of the positive normal floating-point numbers in this format is from 2 −1022 ≈ 2 × 10 −308 to approximately 2 1024 ≈ 2 × 10 308. The number of normal floating-point numbers in a system (B, P, L, U) where B is the base of the system, P is the precision of the significand (in base B),

  9. JavaScript syntax - Wikipedia

    en.wikipedia.org/wiki/JavaScript_syntax

    Numbers are represented in binary as IEEE 754 floating point doubles. Although this format provides an accuracy of nearly 16 significant digits, it cannot always exactly represent real numbers, including fractions. This becomes an issue when comparing or formatting numbers. For example: