ibis-project · cpcloud · Sep 15, 2024 · Sep 15, 2024 · Sep 15, 2024 · Sep 15, 2024
diff --git a/README.md b/README.md
@@ -166,7 +166,7 @@ Ibis broadly supports two types of backend:
 1. SQL-generating backends
 2. DataFrame-generating backends
 
-![Ibis backend types](https://raw.githubusercontent.com/ibis-project/ibis/main/docs/images/backends.png)
+![Ibis backend types](./docs/images/backends.png)
 
 ## Portability
 

diff --git a/docs/_freeze/posts/ffill-and-bfill-using-ibis/index/execute-results/html.json b/docs/_freeze/posts/ffill-and-bfill-using-ibis/index/execute-results/html.json
diff --git a/docs/concepts/internals.qmd b/docs/concepts/internals.qmd
@@ -18,9 +18,9 @@ The internals are designed to map the Ibis API to the backend.
 1. Backend specific rewrites
 1. Expressions are compiled
 1. The SQL string that generated by the compiler is sent to the database and
-   executed (this step is skipped for the pandas backend)
-1. The database returns some data that is then turned into a pandas DataFrame
-   by Ibis
+   executed (this step is skipped for the polars backend)
+1. The database returns some data that is then turned into an in-memory format
+   such as a pandas DataFrame
 
 ## Expressions
 

diff --git a/docs/images/backends.png b/docs/images/backends.png
diff --git a/docs/posts/ffill-and-bfill-using-ibis/index.qmd b/docs/posts/ffill-and-bfill-using-ibis/index.qmd
@@ -30,7 +30,7 @@ This was heavily inspired by Gil Forsyth's writeup on ffill and bfill on the
 ### Setup
 
 First, we want to make some mock data.
-To demonstrate this technique in a non-pandas backend, we will use the DuckDB backend.
+To demonstrate this technique we will use the DuckDB backend.
 
 Our data will have measurements by date, and these measurements will be grouped by an event id.
 We will then save this data to `data.parquet` so we can register that parquet file as a table in our DuckDB connector.

diff --git a/ibis/backends/tests/test_temporal.py b/ibis/backends/tests/test_temporal.py
@@ -1323,7 +1323,6 @@ def test_day_of_week_column_group_by(
         .rename(columns={"timestamp_col": "day_of_week_result"})
     )
 
-    # FIXME(#1536): Pandas backend should use query.schema().apply_to
     backend.assert_frame_equal(result, expected, check_dtype=False)
 
 

diff --git a/ibis/formats/pandas.py b/ibis/formats/pandas.py
@@ -91,7 +91,7 @@ def infer_table(cls, df):
         for column_name in df.dtypes.keys():
             if not isinstance(column_name, str):
                 raise TypeError(
-                    "Column names must be strings to use the pandas backend"
+                    "Column names must be strings to ingest a pandas DataFrame"
                 )
 
             pandas_column = df[column_name]

diff --git a/poetry.lock b/poetry.lock
diff --git a/pyproject.toml b/pyproject.toml
@@ -194,15 +194,6 @@ oracle = [
   "pandas",
   "rich",
 ]
-pandas = [
-  "regex",
-  "packaging",
-  "pyarrow",
-  "pyarrow-hotfix",
-  "numpy",
-  "pandas",
-  "rich",
-]
 polars = [
   "polars",
   "packaging",
@@ -313,18 +304,14 @@ filterwarnings = [
   # pandas 1.5.x
   "ignore:iteritems is deprecated and will be removed in a future version:FutureWarning",
   'ignore:Passing unit-less datetime64 dtype to \.astype is deprecated:FutureWarning',
-  'ignore:The default value of numeric_only in DataFrameGroupBy\.sum is deprecated:FutureWarning',
   # numpy
   "ignore:Creating an ndarray from ragged nested sequences:",
   'ignore:`np\.bool` is a deprecated alias for the builtin `bool`:DeprecationWarning',
   # numpy, coming from a pandas call
   'ignore:In the future `np\.bool` will be defined as the corresponding NumPy scalar:FutureWarning',
   # pandas by way of polars when comparing arrays
   'ignore:The truth value of an empty array is ambiguous\.:DeprecationWarning',
-  # druid
-  'ignore:Dialect druid.rest will not make use of SQL compilation caching:',
   # ibis
-  'ignore:`(Base)?Backend.database` is deprecated:FutureWarning',
   'ignore:`StructValue\.destructure` is deprecated as of v10\.0; use lift or unpack instead:FutureWarning',
   # spark
   "ignore:distutils Version classes are deprecated:DeprecationWarning",
@@ -347,7 +334,7 @@ filterwarnings = [
   "ignore:the imp module is deprecated in favour of importlib:DeprecationWarning",
   # pytest raises a syntax error when encountering this from *any* module, including third party modules
   "ignore:invalid escape sequence:DeprecationWarning",
-  # geopandas raises usr warning on geometry column
+  # geopandas raises user warning on geometry column
   "ignore:Geometry is in a geographic CRS",
   # `is_sparse` deprecation was addressed in pyarrow 13.0.0 (see https://github.com/apache/arrow/pull/35366),
   # but flink requires apache-beam<2.49, which caps its pyarrow dependency (see https://github.com/apache/beam/blob/v2.48.0/sdks/python/setup.py#L144)
@@ -366,8 +353,6 @@ filterwarnings = [
   "ignore:Passing a BlockManager to DataFrame is deprecated:DeprecationWarning",
   # snowpark logging warnings
   "ignore:The 'warn' method is deprecated, use 'warning' instead:DeprecationWarning",
-  # dask and pandas backend deprecation
-  'ignore:The (dask|pandas) backend is slated for removal in 10\.0:DeprecationWarning',
 ]
 empty_parameter_set_mark = "fail_at_collect"
 markers = [
-Original file line number
+Diff line change
@@ Expand Up / @@ -1323,7 +1323,6 @@ def test_day_of_week_column_group_by( @@
             .rename(columns={"timestamp_col": "day_of_week_result"})
         )
-        # FIXME(#1536): Pandas backend should use query.schema().apply_to
         backend.assert_frame_equal(result, expected, check_dtype=False)
@@ Expand Down @@