WEB: add pandas 3.0 release candidate announcement blog

Author: jorisvandenbossche

web/pandas/community/blog/pandas-3.0-release-candidate.md

@@ -0,0 +1,114 @@
+Title: pandas 3.0.0 release candidate ready for testing
+Date: 2025-12-12
+
+# pandas 3.0.0 release candidate ready for testing!
+
+We're excited to announce the release candidate for pandas 3.0. This major
+release brings significant improvements to pandas, but also features some
+potentially breaking changes.
+
+## Highlights of pandas 3.0
+
+pandas 3.0 introduces several major enhancements:
+
+- **Dedicated string data type by default**: String columns are now inferred as
+  the new `str` dtype instead of `object`, providing better performance and type
+  safety
+- **Consistent copy/view behaviour with Copy-on-Write (CoW)** (a.k.a. getting
+  rid of the SettingWithCopyWarning): More predictable and consistent behavior
+  for all operations, with improved performance through avoiding unnecessary
+  copies
+- **New `pd.col` syntax**: Initial support for `pd.col()` as a simplified syntax
+  for creating callables in `DataFrame.assign`
+- **Enhanced deprecation policy**: A new 3-stage deprecation process to give
+  downstream packages more time to adapt
+
+You can find the complete list of changes in our
+[release notes](https://pandas.pydata.org/docs/dev/whatsnew/v3.0.0.html).
+
+## Important changes requiring code updates
+
+As a major release, pandas 3.0 includes some breaking changes that may require
+updates to your code. The two most significant changes are:
+
+### 1. Dedicated string data type by default
+
+Starting with pandas 3.0, string columns are automatically inferred as `str`
+dtype instead of the numpy `object` (which can store any Python object).
+
+**Example of the change:**
+```python
+# Old behavior (pandas < 3.0)
+>>> ser = pd.Series(["a", "b"])
+>>> ser
+0    a
+1    b
+dtype: object  # <-- numpy object dtype
+
+# New behavior (pandas 3.0)
+>>> ser = pd.Series(["a", "b"])
+>>> ser.dtype
+>>> ser
+0    a
+1    b
+dtype: str  # <-- new string dtype
+```
+
+This change improves performance and type safety, but may require code updates.
+For more details, see the
+[String Data Type Migration Guide](https://pandas.pydata.org/docs/dev/user_guide/migration-3-strings.html).
+
+### 2. Consistent copy/view behaviour with Copy-on-Write (CoW)
+
+Copy-on-Write is now the default and only mode in pandas 3.0. This makes
+behavior more consistent and predictable, but requires updates to certain coding
+patterns:
+
+**What you need to update:**
+- **Chained assignment** will no longer work. You'll need to use `.loc` or
+  `.iloc` directly on the DataFrame instead
+- The `SettingWithCopyWarning` is removed (since chained assignment no longer works)
+- Any indexing operation now always behaves as if it were a copy, so
+  modifications won't affect the original DataFrame
+
+**Example of the change:**
+```python
+# Old behavior (pandas < 3.0) - chained assignment
+df[df['A'] > 0]['B'] = 1  # This might modify df (unpredictable)
+
+# New behavior (pandas 3.0) - must use .loc
+df.loc[df['A'] > 0, 'B'] = 1  # This is the correct way
+```
+
+[Copy-on-Write Migration Guide](https://pandas.pydata.org/pandas-docs/version/3.0.0/user_guide/copy_on_write.html)
+
+## Call to Action: Test the Release Candidate
+
+We need your help to ensure a smooth pandas 3.0 release!
+
+Especially if you have pandas code in production or maintain a library with
+pandas as a dependency, it is strongly recommended to run your test suites with
+the release candidate, and report any issue to our issue tracker before the
+official 3.0.0 release.
+
+1. **Install the release candidate** and test it with your codebase
+2. **Run your existing code** to identify any issues or needed updates
+3. **Report any problems** you encounter on our [GitHub repository](https://github.com/pandas-dev/pandas/issues)
+4. **Share your migration experiences** with the community
+
+The more testing we get now, the smoother the final pandas 3.0 release will be
+for everyone. Your feedback is crucial to making this a successful release!
+
+### Getting the Release Candidate
+
+You can install the pandas 3.0 release candidate from PyPI:
+
+```bash
+python -m pip install --upgrade pandas==3.0.0rc0
+```
+
+Or from conda-forge using conda/mamba:
+
+```bash
+conda install -c conda-forge/label/pandas_rc pandas==3.0.0rc0
+```