Pandas：更改交叉表结果的顺序
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Pandas: change order of crosstab result
提问by Denis Kulagin
How to change order in the result of pd.crosstab:
如何更改pd.crosstab结果中的顺序：
pd.crosstab(df['col1'], df['col2'])
I would like to be able to sort by:
我希望能够排序：
- unique values of either df['col1']or df['col2'](cols/rows of the crosstab result)
- by marginal values (e.g. showing higher-count values of df['col1']closer to the top)
- df['col1']或df['col2'] 的唯一值（交叉表结果的列/行）
- 通过边际值（例如显示更接近顶部的df['col1'] 的更高计数值）
回答by epattaro
Well, it would be easier to give you a solution if you provided an example of your data, since it can vary a lot accordingly. I will try to build a case scenario and possible solution below.
好吧，如果您提供数据示例，那么为您提供解决方案会更容易，因为它可能会相应地变化很大。我将尝试在下面构建一个案例场景和可能的解决方案。
If we take the example data and crosstab:
如果我们以示例数据和交叉表为例：
a = np.array(['foo', 'foo', 'foo', 'foo', 'bar', 'bar',
'bar', 'bar', 'foo', 'foo', 'foo'], dtype=object)
c = np.array(['dull', 'dull', 'shiny', 'dull', 'dull', 'weird',
'shiny', 'dull', 'shiny', 'shiny', 'shiny'], dtype=object)
CT = pd.crosstab(a, c, rownames=['a'], colnames=['c'])
CT
We have the following output:
我们有以下输出：
Thats a regular dataframe object, its just "crosstabed" or better yet "pivottabled" accordingly.
那是一个常规的数据框对象，它只是相应地“交叉表”或更好的“数据透视表”。
You would like to show:
你想展示：
- unique values of either df['col1'] or df['col2'] (cols/rows of the crosstab result)
- by marginal values (e.g. showing higher-count values of df['col1'] closer to the top)
- df['col1'] 或 df['col2'] 的唯一值（交叉表结果的列/行）
- 通过边际值（例如显示更接近顶部的 df['col1'] 的更高计数值）
So lets start with "1":
所以让我们从“1”开始：
There are different ways you can do that, a simple solution would be to show the same dataframe object with boolean values for singular cases;
有多种方法可以做到这一点，一个简单的解决方案是使用布尔值显示相同的数据帧对象，用于奇异情况；
[CT == 1]
However, that format might not be what you desire in case of large dataframes.
但是，对于大型数据帧，这种格式可能不是您想要的。
You could just print the positive cases, or list/append 'em, a simple example would be:
您可以只打印正面案例，或列出/附加它们，一个简单的例子是：
for col in CT.columns:
for index in CT.index:
if CT.loc[index,col] == 1:
print (index,col,'singular')
Output:
输出：
('bar', 'shiny', 'singular')
('bar', 'weird', 'singular')
The second item/desire is more complicated. You want to order by higher value. But there might be divergences. A higher value in one column, associated to one set of indexes, will most likely diverge in order from the second column (also associated in the same indexes).
第二个项目/愿望更复杂。您想按更高的价值订购。但可能会有分歧。与一组索引相关联的一列中的较高值很可能与第二列（也在相同索引中相关联）的顺序不同。
Hence, you can choose to order by one specific column:
因此，您可以选择按一个特定的列排序：
CT.sort_values('column_name', ascending=False)
Or, you can define a metric by which you want to order (row mean value) and sort accordingly.
或者，您可以定义要用来排序的指标（行平均值）并相应地排序。
Hope that helps!
希望有帮助！
