Allow Users to Transpose Tables


During my usage of the current implementation in Coda, I noticed the absence of certain useful functionalities, specifically the ability to transpose tables. This feature is particularly valuable in situations where users unintentionally create columns that should have been rows, realizing the need for transposition once the table is complete. Therefore, I propose the inclusion of a new button, such as “Transpose table,” to enable users to perform this action seamlessly. However, I anticipate a potential issue related to column types when implementing this functionality.

Steps to Reproduce:

  1. The absence of a dedicated option or button for transposing tables.

Expected Result:

I expected to find a straightforward option within Coda’s interface that allows users to transpose tables effortlessly, thereby converting columns into rows.

Actual Result:

The functionality to transpose tables is missing from the current implementation of Coda. Users are unable to perform the necessary transposition, causing inconvenience and inefficiency when reorganizing tables.


The lack of a transposition feature significantly affects users’ ability to correct table structures by converting columns to rows when needed. This limitation can lead to suboptimal table layouts, decreased productivity, and potential data inconsistencies.

Suggested Solution:

To tackle this issue, my suggestion is the incorporation of a new button, named “Transpose table.”. This addition will empower users to effortlessly toggle between converting columns into rows and vice versa.

It is essential to acknowledge the potential difficulties associated with incorporating the transposition functionality, specifically concerning column types. To maintain a consistent user experience, I propose a simple rule of thumb: prioritize the preservation of identical column types during table transposition. Alternatively, in cases where the number of rows perfectly matches the number of columns, a solution would involve having the existing column types while seamlessly transposing the table. This approach ensures seamless compatibility and minimizes any potential disruption to the user’s workflow.