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Use: {{Octal|x}} where x is the decimal number. Example: {{Octal|4632}} yields 11030 8 . Numbers outside the range of -9007199254740992 to 9007199254740992 may lose precision.
To convert integer decimals to octal, divide the original number by the largest possible power of 8 and divide the remainders by successively smaller powers of 8 until the power is 1. The octal representation is formed by the quotients, written in the order generated by the algorithm. For example, to convert 125 10 to octal: 125 = 8 2 × 1 + 61
Each of these number systems is a positional system, but while decimal weights are powers of 10, the octal weights are powers of 8 and the hexadecimal weights are powers of 16. To convert from hexadecimal or octal to decimal, for each digit one multiplies the value of the digit by the value of its position and then adds the results. For example:
The "decimal" data type of the C# and Python programming languages, and the decimal formats of the IEEE 754-2008 standard, are designed to avoid the problems of binary floating-point representations when applied to human-entered exact decimal values, and make the arithmetic always behave as expected when numbers are printed in decimal.
For example, a packed decimal value encoded with the bytes 12 34 56 7C represents the fixed-point value +1,234.567 when the implied decimal point is located between the fourth and fifth digits: 12 34 56 7C 12 34.56 7+ The decimal point is not actually stored in memory, as the packed BCD storage format does not provide for it.
As an example, "0020" does not represent 20 10 (2×10 1 + 0×10 0), but rather 20 8 = 16 10 (2×8 1 + 0×8 0 = 1×10 1 + 6×10 0). Decimal numbers written with leading zeros will be interpreted as octal by languages that follow this convention and will generate errors if they contain "8" or "9", since these digits do not exist in octal.
When converting from binary to octal every 3 bits relate to one and only one octal digit. Hexadecimal, decimal, octal, and a wide variety of other bases have been used for binary-to-text encoding, implementations of arbitrary-precision arithmetic, and other applications. For a list of bases and their applications, see list of numeral systems.
A decimal floating-point number can be encoded in several ways, the different ways represent different precisions, for example 100.0 is encoded as 1000×10 −1, while 100.00 is encoded as 10000×10 −2. The set of possible encodings of the same numerical value is called a cohort in the standard. If the result of a calculation is inexact the ...
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