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Alexander Hess 2019-10-15 19:36:16 +02:00
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05_numbers.ipynb
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@ -21,7 +21,7 @@
"source": [
"After learning about the basic building blocks of expressing and structuring the business logic in programs, we focus our attention on the **data types** Python offers us, both built-in and available via the [standard library](https://docs.python.org/3/library/index.html) or third-party packages.\n",
"\n",
"We start with the \"simple\" ones: Numeric types in this chapter and textual data in Chapter 6. An important fact that holds for all objects of these types is that they are **immutable**. To re-use the bag analogy from [Chapter 1](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/master/01_elements.ipynb#Objects-vs.-Types-vs.-Values), this means that the $0$s and $1$s making up an object's *value* cannot be changed once the bag is created in memory, implying that any operation with or method on the object creates a *new* object in a *different* memory location.\n",
"We start with the \"simple\" ones: Numeric types in this chapter and textual data in [Chapter 6](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/master/06_text.ipynb). An important fact that holds for all objects of these types is that they are **immutable**. To re-use the bag analogy from [Chapter 1](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/master/01_elements.ipynb#Objects-vs.-Types-vs.-Values), this means that the $0$s and $1$s making up an object's *value* cannot be changed once the bag is created in memory, implying that any operation with or method on the object creates a *new* object in a *different* memory location.\n",
"\n",
"Chapters 7, 8, and 9 then cover the more \"complex\" data types, including, for example, the `list` type. Finally, Chapter 10 completes the picture by introducing language constructs to create custom types.\n",
"\n",
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}
},
"source": [
"To preserve the precision for more advanced mathematical functions, `Decimal` objects come with many methods bound on them. For example, [ln()](https://docs.python.org/3/library/decimal.html#decimal.Decimal.ln) and [log10()](https://docs.python.org/3/library/decimal.html#decimal.Decimal.log10) take the logarithm while [sqrt()](https://docs.python.org/3/library/decimal.html#decimal.Decimal.sqrt) calculates the square root. In general, the functions in the [math](https://docs.python.org/3/library/math.html) module in the [standard library](https://docs.python.org/3/library/index.html) should only be used with `float` objects as they do *not* preserve precision."
"To preserve the precision for more advanced mathematical functions, `Decimal` objects come with many **methods bound** on them. For example, [ln()](https://docs.python.org/3/library/decimal.html#decimal.Decimal.ln) and [log10()](https://docs.python.org/3/library/decimal.html#decimal.Decimal.log10) take the logarithm while [sqrt()](https://docs.python.org/3/library/decimal.html#decimal.Decimal.sqrt) calculates the square root. In general, the functions in the [math](https://docs.python.org/3/library/math.html) module in the [standard library](https://docs.python.org/3/library/index.html) should only be used with `float` objects as they do *not* preserve precision."
]
},
{