用于确定表格数据属于哪种范式的 Python 代码

发布于 2024-08-19 16:26:03 字数 56 浏览 6 评论 0原文

我正在寻找可以获取表格数据并确定其采用的范式（如果有）并显示任何函数依赖关系等的Python代码。

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烟花肆意 2024-08-26 16:26:03

有“标准化”的逻辑测试。然而，它们并不是简单的编程练习；它们是一种简单的编程练习。它们是强加于数据的元数据中的关系。他们需要“思考”。

1NF——无重复组。如何识别“重复组”？它将是强加在表的列上的数组结构。这是怎么做到的？ SQL 不提供机制，因此您必须查看列名来检查“模式”。例如，COL_1、COL_2、COL_3。

1NF——行的一致布局。呃。 SQL 通过表定义的本质强加了这一点。

2NF——一行中的数据取决于键。你必须执行类似这样的程序。

For each non-key column:
   Query distinct pairs (Key and the non-key column)
   Do all non-key values depend in a consistent way on a key value?
   Can you build a simple dict mapping non-key to key?

完整的算法在这里： http://en.wikipedia.org/wiki/Relational_model# Set-theoretic_formulation

3NF——一行中的数据仅取决于键。这更糟糕，因为您必须将非键列的所有组合与非键列的所有组合进行比较，以确保值之间不存在非键依赖性。

4NF 和 5NF 让我感到困惑，所以我就到此为止。

我的观点是——理论上——你可以做到。实际上，需要对数据进行大量复杂的排列才能断言范式关系实际上成立。

对特定违规行为做出假设并通过一些 SQL 查询和一些思考来探究该问题要容易得多。

正式的数学在这里：

http://en.wikipedia.org/wiki/Relational_model

There are logical tests for "normalization". However, they're not trivial exercises in programming; they're relationships in the metadata that are imposed on the data. They require "thinking".

1NF -- no repeating groups. How does one identify a "repeating group"? It would be an array structure imposed on the columns of a table. How is that done? SQL doesn't provide a mechanism, so you'd have to look at the column names to check for a "pattern". COL_1, COL_2, COL_3, for example.

1NF -- consistent layout of rows. Duh. SQL imposes this by the very nature of table definition.

2NF -- data in a row depends on the key. You'd have to do a procedure something like this.

For each non-key column:
   Query distinct pairs (Key and the non-key column)
   Do all non-key values depend in a consistent way on a key value?
   Can you build a simple dict mapping non-key to key?

The full algorithm is here: http://en.wikipedia.org/wiki/Relational_model#Set-theoretic_formulation

3NF -- data in a row depends ONLY on the key. This is worse, because you have to compare all combinations of non-key columns against all combinations of non-key columns to be sure that there were no non-key dependencies among the values.

4NF and 5NF confuse me, so I'll stop here.

My point is that -- theoretically -- you can do it. Practically, it's a lot of complex permutations of data to assert that the normal form relationships actually hold.

It's much, much easier to have a hypothesis about a specific violation and probe just that issue with some SQL queries and some thinking.

The formal math is here:

http://en.wikipedia.org/wiki/Relational_model

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