From 272163f718e60026530a2d3120a693cb985e112d Mon Sep 17 00:00:00 2001 From: Arik Mitschang Date: Mon, 7 Oct 2024 16:01:31 -0400 Subject: [PATCH] [DOC] fix link in doc (#2944) I noticed a small error in documentation, looks like markdown style link used mistakenly. --------- Co-authored-by: ccmao1130 --- docs/source/migration_guides/coming_from_dask.rst | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/source/migration_guides/coming_from_dask.rst b/docs/source/migration_guides/coming_from_dask.rst index 99606c3ff9..8eaedb1258 100644 --- a/docs/source/migration_guides/coming_from_dask.rst +++ b/docs/source/migration_guides/coming_from_dask.rst @@ -30,7 +30,7 @@ Daft does not use an index Dask aims for as much feature-parity with pandas as possible, including maintaining the presence of an Index in the DataFrame. But keeping an Index is difficult when moving to a distributed computing environment. Dask doesn’t support row-based positional indexing (with .iloc) because it does not track the length of its partitions. It also does not support pandas MultiIndex. The argument for keeping the Index is that it makes some operations against the sorted index column very fast. In reality, resetting the Index forces a data shuffle and is an expensive operation. -Daft drops the need for an Index to make queries more readable and consistent. How you write a query should not change because of the state of an index or a reset_index call. In our opinion, eliminating the index makes things simpler, more explicit, more readable and therefore less error-prone. Daft achieves this by using the [Expressions API](../user_guide/expressions). +Daft drops the need for an Index to make queries more readable and consistent. How you write a query should not change because of the state of an index or a reset_index call. In our opinion, eliminating the index makes things simpler, more explicit, more readable and therefore less error-prone. Daft achieves this by using the :doc:`Expressions API <../api_docs/expressions>`. In Dask you would index your DataFrame to return row ``b`` as follows: