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Merge branch 'main' into bug-DatetimeIndex-is_year_start-breaks-on-freq-BusinessMonthStart
2 parents 6197e69 + 283a2dc commit 7761989

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.github/workflows/wheels.yml

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@@ -140,7 +140,7 @@ jobs:
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run: echo "sdist_name=$(cd ./dist && ls -d */)" >> "$GITHUB_ENV"
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- name: Build wheels
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uses: pypa/cibuildwheel@v2.17.0
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uses: pypa/cibuildwheel@v2.18.0
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with:
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package-dir: ./dist/${{ startsWith(matrix.buildplat[1], 'macosx') && env.sdist_name || needs.build_sdist.outputs.sdist_file }}
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env:

ci/code_checks.sh

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@@ -76,7 +76,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
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-i "pandas.DataFrame.min RT03" \
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-i "pandas.DataFrame.plot PR02,SA01" \
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-i "pandas.Grouper PR02" \
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-i "pandas.IntervalIndex.left GL08" \
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-i "pandas.MultiIndex PR01" \
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-i "pandas.MultiIndex.append PR07,SA01" \
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-i "pandas.MultiIndex.copy PR07,RT03,SA01" \
@@ -139,7 +138,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
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-i "pandas.RangeIndex.start SA01" \
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-i "pandas.RangeIndex.step SA01" \
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-i "pandas.RangeIndex.stop SA01" \
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-i "pandas.Series.case_when RT03" \
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-i "pandas.Series.cat.add_categories PR01,PR02" \
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-i "pandas.Series.cat.as_ordered PR01" \
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-i "pandas.Series.cat.as_unordered PR01" \
@@ -230,7 +228,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
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-i "pandas.Series.str.strip RT03" \
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-i "pandas.Series.str.swapcase RT03" \
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-i "pandas.Series.str.title RT03" \
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-i "pandas.Series.str.translate RT03,SA01" \
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-i "pandas.Series.str.upper RT03" \
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-i "pandas.Series.str.wrap RT03,SA01" \
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-i "pandas.Series.str.zfill RT03" \
@@ -245,7 +242,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
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-i "pandas.Series.truediv PR07" \
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-i "pandas.Series.update PR07,SA01" \
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-i "pandas.Series.var PR01,RT03,SA01" \
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-i "pandas.SparseDtype SA01" \
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-i "pandas.Timedelta PR07,SA01" \
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-i "pandas.Timedelta.as_unit SA01" \
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-i "pandas.Timedelta.asm8 SA01" \
@@ -326,7 +322,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
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-i "pandas.api.extensions.ExtensionArray._reduce RT03,SA01" \
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-i "pandas.api.extensions.ExtensionArray._values_for_factorize SA01" \
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-i "pandas.api.extensions.ExtensionArray.astype SA01" \
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-i "pandas.api.extensions.ExtensionArray.copy RT03,SA01" \
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-i "pandas.api.extensions.ExtensionArray.dropna RT03,SA01" \
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-i "pandas.api.extensions.ExtensionArray.dtype SA01" \
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-i "pandas.api.extensions.ExtensionArray.duplicated RT03,SA01" \
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-i "pandas.api.extensions.ExtensionArray.nbytes SA01" \
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-i "pandas.api.extensions.ExtensionArray.ndim SA01" \
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-i "pandas.api.extensions.ExtensionArray.ravel RT03,SA01" \
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-i "pandas.api.extensions.ExtensionArray.shape SA01" \
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-i "pandas.api.extensions.ExtensionArray.shift SA01" \
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-i "pandas.api.extensions.ExtensionArray.take RT03" \
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-i "pandas.api.extensions.ExtensionArray.tolist RT03,SA01" \
@@ -571,7 +565,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
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-i "pandas.tseries.offsets.BQuarterEnd.normalize GL08" \
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-i "pandas.tseries.offsets.BQuarterEnd.rule_code GL08" \
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-i "pandas.tseries.offsets.BQuarterEnd.startingMonth GL08" \
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-i "pandas.tseries.offsets.BYearBegin PR02" \
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-i "pandas.tseries.offsets.BYearBegin.freqstr SA01" \
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-i "pandas.tseries.offsets.BYearBegin.is_on_offset GL08" \
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-i "pandas.tseries.offsets.BYearBegin.month GL08" \
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-i "pandas.tseries.offsets.WeekOfMonth.rule_code GL08" \
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-i "pandas.tseries.offsets.WeekOfMonth.week GL08" \
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-i "pandas.tseries.offsets.WeekOfMonth.weekday GL08" \
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-i "pandas.tseries.offsets.YearBegin PR02" \
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-i "pandas.tseries.offsets.YearBegin.freqstr SA01" \
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-i "pandas.tseries.offsets.YearBegin.is_on_offset GL08" \
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-i "pandas.tseries.offsets.YearBegin.month GL08" \

doc/source/development/policies.rst

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@@ -46,6 +46,8 @@ deprecation removed in the next major release (2.0.0).
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These policies do not apply to features marked as **experimental** in the documentation.
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pandas may change the behavior of experimental features at any time.
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.. _policies.python_support:
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Python support
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~~~~~~~~~~~~~~
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doc/source/getting_started/install.rst

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Python version support
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----------------------
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Officially Python 3.9, 3.10, 3.11 and 3.12.
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See :ref:`Python support policy <policies.python_support>`.
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Installing pandas
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-----------------

doc/source/getting_started/intro_tutorials/01_table_oriented.rst

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@@ -192,8 +192,8 @@ Check more options on ``describe`` in the user guide section about :ref:`aggrega
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.. note::
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This is just a starting point. Similar to spreadsheet
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software, pandas represents data as a table with columns and rows. Apart
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from the representation, also the data manipulations and calculations
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you would do in spreadsheet software are supported by pandas. Continue
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from the representation, the data manipulations and calculations
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you would do in spreadsheet software are also supported by pandas. Continue
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reading the next tutorials to get started!
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.. raw:: html
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- Import the package, aka ``import pandas as pd``
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- A table of data is stored as a pandas ``DataFrame``
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- Each column in a ``DataFrame`` is a ``Series``
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- You can do things by applying a method to a ``DataFrame`` or ``Series``
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- You can do things by applying a method on a ``DataFrame`` or ``Series``
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.. raw:: html
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<div class="d-flex flex-row gs-torefguide">
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<span class="badge badge-info">To user guide</span>
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A more extended explanation to ``DataFrame`` and ``Series`` is provided in the :ref:`introduction to data structures <dsintro>`.
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A more extended explanation of ``DataFrame`` and ``Series`` is provided in the :ref:`introduction to data structures <dsintro>` page.
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.. raw:: html
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doc/source/getting_started/intro_tutorials/02_read_write.rst

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- The table has 12 columns. Most columns have a value for each of the
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rows (all 891 values are ``non-null``). Some columns do have missing
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values and less than 891 ``non-null`` values.
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- The columns ``Name``, ``Sex``, ``Cabin`` and ``Embarked`` consists of
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- The columns ``Name``, ``Sex``, ``Cabin`` and ``Embarked`` consist of
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textual data (strings, aka ``object``). The other columns are
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numerical data with some of them whole numbers (aka ``integer``) and
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others are real numbers (aka ``float``).
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- The kind of data (characters, integers,…) in the different columns
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numerical data, some of them are whole numbers (``integer``) and
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others are real numbers (``float``).
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- The kind of data (characters, integers, …) in the different columns
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- The approximate amount of RAM used to hold the DataFrame is provided
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- Getting data in to pandas from many different file formats or data
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- Exporting data out of pandas is provided by different
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``to_*``\ methods.
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``to_*`` methods.
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- The ``head``/``tail``/``info`` methods and the ``dtypes`` attribute
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are convenient for a first check.
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doc/source/getting_started/intro_tutorials/03_subset_data.rst

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</li>
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When using the column names, row labels or a condition expression, use
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When using column names, row labels or a condition expression, use
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the ``loc`` operator in front of the selection brackets ``[]``. For both
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of labels, a slice of labels, a conditional expression or a colon. Using
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<div class="d-flex flex-row gs-torefguide">
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<span class="badge badge-info">To user guide</span>
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See the user guide section on :ref:`different choices for indexing <indexing.choice>` to get more insight in the usage of ``loc`` and ``iloc``.
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See the user guide section on :ref:`different choices for indexing <indexing.choice>` to get more insight into the usage of ``loc`` and ``iloc``.
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.. raw:: html
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a colon.
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- Select specific rows and/or columns using ``loc`` when using the row
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and column names.
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- Select specific rows and/or columns using ``iloc`` when using the
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positions in the table.
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- Use ``loc`` for label-based selection (using row/column names).
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- Use ``iloc`` for position-based selection (using table positions).
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doc/source/getting_started/intro_tutorials/04_plotting.rst

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To plot a specific column, use the selection method of the
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:ref:`subset data tutorial <10min_tut_03_subset>` in combination with the :meth:`~DataFrame.plot`
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]
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.. note::
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In many development environments such as IPython and
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- The ``.plot.*`` methods are applicable on both Series and DataFrames.
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(line, boxplot, …).
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.. raw:: html

doc/source/getting_started/intro_tutorials/05_add_columns.rst

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Also other mathematical operators (``+``, ``-``, ``*``, ``/``,…) or
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logical operators (``<``, ``>``, ``==``,…) work element-wise. The latter was already
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Other mathematical operators (``+``, ``-``, ``*``, ``/``, …) and logical
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operators (``<``, ``>``, ``==``, …) also work element-wise. The latter was already
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doc/source/getting_started/intro_tutorials/06_calculate_statistics.rst

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The function is a shortcut, as it is actually a groupby operation in combination with counting of the number of records
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The function is a shortcut, it is actually a groupby operation in combination with counting the number of records
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within each group:
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.. ipython:: python

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