From 5780f2111d47cf06c4e6b5e8bfc30b4649ada2bb Mon Sep 17 00:00:00 2001
From: dangotbanned <125183946+dangotbanned@users.noreply.github.com>
Date: Wed, 19 Jun 2024 09:15:07 +0100
Subject: [PATCH] docs(typing): Remove `NonGeoDataType` and amend error message
 in `_data_to_csv_string`

See https://github.com/vega/altair/pull/3426#issuecomment-2177601705

See https://github.com/vega/altair/issues/3441
---
 altair/utils/data.py | 10 +++++-----
 1 file changed, 5 insertions(+), 5 deletions(-)

diff --git a/altair/utils/data.py b/altair/utils/data.py
index 2b429d760..41b5e71aa 100644
--- a/altair/utils/data.py
+++ b/altair/utils/data.py
@@ -44,7 +44,6 @@ class SupportsGeoInterface(Protocol):
 
 DataType = Union[dict, pd.DataFrame, SupportsGeoInterface, DataFrameLike]
 TDataType = TypeVar("TDataType", bound=DataType)
-NonGeoDataType = Union[dict, pd.DataFrame, DataFrameLike]
 
 VegaLiteDataDict = Dict[str, Union[str, dict, List[dict]]]
 ToValuesReturnType = Dict[str, Union[dict, List[dict]]]
@@ -263,7 +262,7 @@ def to_csv(
 
 @overload
 def to_csv(
-    data: NonGeoDataType,
+    data: Union[dict, pd.DataFrame, DataFrameLike],
     prefix: str = ...,
     extension: str = ...,
     filename: str = ...,
@@ -272,7 +271,7 @@ def to_csv(
 
 
 def to_csv(
-    data: Optional[NonGeoDataType] = None,
+    data: Optional[Union[dict, pd.DataFrame, DataFrameLike]] = None,
     prefix: str = "altair-data",
     extension: str = "csv",
     filename: str = "{prefix}-{hash}.{extension}",
@@ -378,8 +377,9 @@ def _data_to_csv_string(data: Union[dict, pd.DataFrame, DataFrameLike]) -> str:
     check_data_type(data)
     if isinstance(data, SupportsGeoInterface):
         raise NotImplementedError(
-            "to_csv does not work with data that "
-            "contains the __geo_interface__ attribute"
+            f"to_csv does not yet work with data that "
+            f"is of type {type(SupportsGeoInterface).__name__!r}.\n"
+            f"See https://github.com/vega/altair/issues/3441"
         )
     elif isinstance(data, pd.DataFrame):
         data = sanitize_dataframe(data)