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DOC: edit SPSS comparison guide to documentation
- Added file to doc/source/getting_started/comparison/index.rst toctree - Fixed formatting and whitespace issues to meet documentation standards
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doc/source/getting_started/comparison/comparison_with_spss.rst

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Comparison with SPSS
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********************
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For potential users coming from `SPSS <https://www.ibm.com/spss>`__, this page is meant to demonstrate
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For potential users coming from `SPSS <https://www.ibm.com/spss>`__, this page is meant to demonstrate
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how various SPSS operations would be performed using pandas.
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.. include:: includes/introduction.rst
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:widths: 20, 20
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``DataFrame``, data file
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column, variable
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column, variable
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row, case
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groupby, split file
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``NaN``, system-missing
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~~~~~~~~~~~~~
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A ``DataFrame`` in pandas is analogous to an SPSS data file - a two-dimensional
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data source with labeled columns that can be of different types. As will be shown in this
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data source with labeled columns that can be of different types. As will be shown in this
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document, almost any operation that can be performed in SPSS can also be accomplished in pandas.
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``Series``
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``Index``
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~~~~~~~~~
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Every ``DataFrame`` and ``Series`` has an ``Index`` -- labels on the *rows* of the data. SPSS does not
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have an exact analogue, as cases are simply numbered sequentially from 1. In pandas, if no index is
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Every ``DataFrame`` and ``Series`` has an ``Index`` -- labels on the *rows* of the data. SPSS does not
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have an exact analogue, as cases are simply numbered sequentially from 1. In pandas, if no index is
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specified, a ``RangeIndex`` is used by default (first row = 0, second row = 1, and so on).
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While using a labeled ``Index`` or ``MultiIndex`` can enable sophisticated analyses and is ultimately an
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important part of pandas to understand, for this comparison we will essentially ignore the ``Index`` and
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just treat the ``DataFrame`` as a collection of columns. Please see the :ref:`indexing documentation<indexing>`
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While using a labeled ``Index`` or ``MultiIndex`` can enable sophisticated analyses and is ultimately an
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important part of pandas to understand, for this comparison we will essentially ignore the ``Index`` and
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just treat the ``DataFrame`` as a collection of columns. Please see the :ref:`indexing documentation<indexing>`
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for much more on how to use an ``Index`` effectively.
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Reading external data
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~~~~~~~~~~~~~~~~~~~~
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Like SPSS, pandas provides utilities for reading in data from many formats. The ``tips`` dataset, found within
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Like SPSS, pandas provides utilities for reading in data from many formats. The ``tips`` dataset, found within
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the pandas tests (`csv <https://raw.githubusercontent.com/pandas-dev/pandas/main/pandas/tests/io/data/csv/tips.csv>`_)
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will be used in many of the following examples.
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# Save multiple results to Excel sheets
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with pd.ExcelWriter('results.xlsx') as writer:
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tips.describe().to_excel(writer, sheet_name='Descriptives')
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tips.groupby('sex').mean().to_excel(writer, sheet_name='Means by Gender')
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tips.groupby('sex').mean().to_excel(writer, sheet_name='Means by Gender')

doc/source/getting_started/comparison/index.rst

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comparison_with_spreadsheets
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comparison_with_sas
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comparison_with_stata
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comparison_with_spss

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