Merge branch 'main' into update-docs-data-table-representation

Author: gnkl

.github/workflows/code-checks.yml

@@ -33,7 +33,7 @@ jobs:
 
     steps:
     - name: Checkout
-      uses: actions/checkout@v5
+      uses: actions/checkout@v6
       with:
         fetch-depth: 0
 
@@ -114,7 +114,7 @@ jobs:
 
     steps:
     - name: Checkout
-      uses: actions/checkout@v5
+      uses: actions/checkout@v6
       with:
         fetch-depth: 0
 
@@ -142,7 +142,7 @@ jobs:
 
     steps:
       - name: Checkout
-        uses: actions/checkout@v5
+        uses: actions/checkout@v6
         with:
           fetch-depth: 0
 

.github/workflows/codeql.yml

@@ -27,7 +27,7 @@ jobs:
           - python
 
     steps:
-      - uses: actions/checkout@v5
+      - uses: actions/checkout@v6
       - uses: github/codeql-action/init@v4
         with:
           languages: ${{ matrix.language }}

.github/workflows/docbuild-and-upload.yml

@@ -36,7 +36,7 @@ jobs:
 
     steps:
     - name: Checkout
-      uses: actions/checkout@v5
+      uses: actions/checkout@v6
       with:
         fetch-depth: 0
 

.github/workflows/package-checks.yml

@@ -34,7 +34,7 @@ jobs:
 
     steps:
       - name: Checkout
-        uses: actions/checkout@v5
+        uses: actions/checkout@v6
         with:
           fetch-depth: 0
 
@@ -58,7 +58,7 @@ jobs:
       cancel-in-progress: true
     steps:
       - name: Checkout
-        uses: actions/checkout@v5
+        uses: actions/checkout@v6
         with:
           fetch-depth: 0
 

.github/workflows/unit-tests.yml

@@ -139,7 +139,7 @@ jobs:
 
     steps:
     - name: Checkout
-      uses: actions/checkout@v5
+      uses: actions/checkout@v6
       with:
         fetch-depth: 0
 
@@ -198,7 +198,7 @@ jobs:
 
     steps:
       - name: Checkout
-        uses: actions/checkout@v5
+        uses: actions/checkout@v6
         with:
           fetch-depth: 0
 
@@ -216,7 +216,7 @@ jobs:
   Linux-32-bit:
     runs-on: ubuntu-24.04
     container:
-      image: quay.io/pypa/manylinux2014_i686
+      image: quay.io/pypa/manylinux_2_28_i686
       options: --platform linux/386
     steps:
       - name: Checkout pandas Repo
@@ -336,7 +336,7 @@ jobs:
       PYTEST_TARGET: pandas
 
     steps:
-      - uses: actions/checkout@v5
+      - uses: actions/checkout@v6
         with:
           fetch-depth: 0
 
@@ -373,7 +373,7 @@ jobs:
       cancel-in-progress: true
     steps:
       - name: Checkout pandas Repo
-        uses: actions/checkout@v5
+        uses: actions/checkout@v6
         with:
           fetch-depth: 0
 

.github/workflows/wheels.yml

@@ -51,7 +51,7 @@ jobs:
       sdist_file: ${{ steps.save-path.outputs.sdist_name }}
     steps:
       - name: Checkout pandas
-        uses: actions/checkout@v5
+        uses: actions/checkout@v6
         with:
           fetch-depth: 0
 
@@ -122,7 +122,7 @@ jobs:
       IS_SCHEDULE_DISPATCH: ${{ github.event_name == 'schedule' || github.event_name == 'workflow_dispatch' }}
     steps:
       - name: Checkout pandas
-        uses: actions/checkout@v5
+        uses: actions/checkout@v6
         with:
           fetch-depth: 0
 

.gitignore

@@ -21,6 +21,7 @@
 .noseids
 .ipynb_checkpoints
 .tags
+tags
 .cache/
 .vscode/
 

ci/code_checks.sh

@@ -73,12 +73,10 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         -i "pandas.Period.freq GL08" \
         -i "pandas.Period.ordinal GL08" \
         -i "pandas.errors.IncompatibleFrequency SA01,SS06,EX01" \
-        -i "pandas.errors.InvalidVersion GL08" \
         -i "pandas.api.extensions.ExtensionArray.value_counts EX01,RT03,SA01" \
         -i "pandas.api.typing.DataFrameGroupBy.plot PR02" \
         -i "pandas.api.typing.SeriesGroupBy.plot PR02" \
         -i "pandas.api.typing.Resampler.quantile PR01,PR07" \
-        -i "pandas.arrays.NumpyExtensionArray GL08" \
         -i "pandas.tseries.offsets.BDay PR02,SA01" \
         -i "pandas.tseries.offsets.BHalfYearBegin.is_on_offset GL08" \
         -i "pandas.tseries.offsets.BHalfYearBegin.n GL08" \

doc/source/user_guide/io.rst

@@ -3717,6 +3717,7 @@ The look and feel of Excel worksheets created from pandas can be modified using
 
 * ``float_format`` : Format string for floating point numbers (default ``None``).
 * ``freeze_panes`` : A tuple of two integers representing the bottommost row and rightmost column to freeze. Each of these parameters is one-based, so (1, 1) will freeze the first row and first column (default ``None``).
+* ``autofilter`` : A boolean indicating whether to add automatic filters to all columns (default ``False``).
 
 .. note::
 

doc/source/user_guide/timeseries.rst

@@ -241,6 +241,19 @@ inferred frequency upon creation:
 
     pd.DatetimeIndex(["2018-01-01", "2018-01-03", "2018-01-05"], freq="infer")
 
+In most cases, parsing strings to datetimes (with any of :func:`to_datetime`, :class:`DatetimeIndex`, or :class:`Timestamp`) will produce objects with microsecond ("us") unit. The exception to this rule is if your strings have nanosecond precision, in which case the result will have "ns" unit:
+
+.. ipython:: python
+
+   pd.to_datetime(["2016-01-01 02:03:04"]).unit
+   pd.to_datetime(["2016-01-01 02:03:04.123"]).unit
+   pd.to_datetime(["2016-01-01 02:03:04.123456"]).unit
+   pd.to_datetime(["2016-01-01 02:03:04.123456789"]).unit
+
+.. versionchanged:: 3.0.0
+
+        Previously, :func:`to_datetime` and :class:`DatetimeIndex` would always parse strings to "ns" unit. During pandas 2.x, :class:`Timestamp` could give any of "s", "ms", "us", or "ns" depending on the specificity of the input string.
+
 .. _timeseries.converting.format:
 
 Providing a format argument
@@ -379,6 +392,16 @@ We subtract the epoch (midnight at January 1, 1970 UTC) and then floor divide by
 
    (stamps - pd.Timestamp("1970-01-01")) // pd.Timedelta("1s")
 
+Another common way to perform this conversion is to convert directly to an integer dtype. Note that the exact integers this produces will depend on the specific unit
+or resolution of the datetime64 dtype:
+
+.. ipython:: python
+
+   stamps.astype(np.int64)
+   stamps.astype("datetime64[s]").astype(np.int64)
+   stamps.astype("datetime64[ms]").astype(np.int64)
+
+
 .. _timeseries.origin:
 
 Using the ``origin`` parameter