Merge pull request #12 from jmenglund/develop

Develop

Author: jmenglund

.travis.yml

@@ -10,10 +10,19 @@ branches:
     only:
         - master
 
+install:
+    - pip install .
+    - pip install pycodestyle
+    - pip install pytest
+    - pip install coverage
+    - pip install codecov
+    - pip install dendropy
+    - pip install biopython
+
 script:
-    - py.test pandascharm.py --pep8
-    - coverage run -m py.test
-    - coverage report --include pandascharm.py -m
+    - pycodestyle pandascharm.py test_pandascharm.py setup.py
+    - coverage run -m pytest test_pandascharm.py
+    - coverage report -m pandascharm.py
 
 after_success:
   - codecov

CHANGELOG.rst

@@ -1,6 +1,19 @@
 Changelog
 =========
 
+0.2.0
+-----
+
+* Added functions ``from_dict`` and ``to_dict`` for casting from and to dictionaries.
+* Updated commands for Travis-CI.
+* Updates to ``README.rst``.
+* Updates to ``release-checklist.rst``.
+
+Release date: 2019-02-23
+
+`View commits <https://github.com/jmenglund/pandas-charm/compare/v0.1.3...v0.2.0>`_
+
+
 0.1.3
 -----
 
@@ -11,24 +24,25 @@ Changelog
 * Added Travis-CI testing for Python 3.6.
 * List of included categories are now ignored in matrix conversions involving
   categorical data.
-* ``pytest-cov`` removed from *requirements.txt*.
-* Updates to *setup.py*.
-* Updates to *README.rst*.
-* Updates to *release-checklist.rst*.
+* ``pytest-cov`` removed from ``requirements.txt``.
+* Updates to ``setup.py``.
+* Updates to ``README.rst``.
+* Updates to ``release-checklist.rst``.
 
 Release date: 2017-08-25
 
 `View commits <https://github.com/jmenglund/pandas-charm/compare/v0.1.2...v0.1.3>`_
 
+
 0.1.2
 -----
 
 * Added Python versions for Travis-CI (3.3, 3.5)
-* Added ``pep8`` check to Travis-CI
-* Updates to *README.rst*
+* Added PEP8 check to Travis-CI
+* Updates to ``README.rst``
     - Fixed issue with one example not working (``pc.to_charmatrix()``)
     - Updated text in various places
-* Updates to *release-checklist.rst*
+* Updates to ``release-checklist.rst``
 
 Release date: 2016-08-08
 
@@ -39,8 +53,8 @@ Release date: 2016-08-08
 -----
 
 * Simplified builds with Travis-CI.
-* DOI badge added to the top of *README.rst*.
-* Information on how to cite ``pandas-charm`` added to *README.rst*.
+* DOI badge added to the top of ``README.rst``.
+* Information on how to cite pandas-charm added to ``README.rst``.
 
 Release date: 2016-07-05
 

MANIFEST.in

@@ -1,2 +1,3 @@
 include *.rst
+include CHANGELOG.md
 include LICENSE.txt

README.rst

@@ -3,17 +3,16 @@ pandas-charm
 
 |Build-Status| |Coverage-Status| |PyPI-Status| |License| |DOI-URI|
 
-``pandas-charm`` is a small Python package for getting character 
+pandas-charm is a small Python package for getting character
 matrices (alignments) into and out of `pandas <http://pandas.pydata.org>`_.
-Its purpose is to make pandas interoperable with other scientific 
-packages that can be used for dealing with character matrices, like for example 
-`BioPython <http://biopython.org>`_ and `Dendropy <http://dendropy.org>`_.
+Use this library to make pandas interoperable with
+`BioPython <http://biopython.org>`_ and `DendroPy <http://dendropy.org>`_.
 
-With ``pandas-charm``, it is currently possible to convert between the 
-following objects:
+Convert between the following objects:
 
 * BioPython MultipleSeqAlignment <-> pandas DataFrame
 * DendroPy CharacterMatrix <-> pandas DataFrame
+* Python dictionary <-> pandas DataFrame
 
 The code has been tested with Python 2.7, 3.5 and 3.6.
 
@@ -29,14 +28,14 @@ Source repository: `<https://github.com/jmenglund/pandas-charm>`_
 Installation
 ------------
 
-For most users, the easiest way is probably to install the latest version 
-hosted on `PyPI <https://pypi.python.org/>`_:
+For most users, the easiest way is probably to install the latest version
+hosted on `PyPI <https://pypi.org/>`_:
 
 .. code-block::
 
     $ pip install pandas-charm
 
-The project is hosted at https://github.com/jmenglund/pandas-charm and 
+The project is hosted at https://github.com/jmenglund/pandas-charm and
 can also be installed using git:
 
 .. code-block::
@@ -46,33 +45,45 @@ can also be installed using git:
     $ python setup.py install
 
 
-You may consider installing ``pandas-charm`` and its required Python packages 
-within a virtual environment in order to avoid cluttering your system's 
-Python path. See for example the environment management system 
-`conda <http://conda.pydata.org>`_ or the package 
+You may consider installing pandas-charm and its required Python packages
+within a virtual environment in order to avoid cluttering your system's
+Python path. See for example the environment management system
+`conda <http://conda.pydata.org>`_ or the package
 `virtualenv <https://virtualenv.pypa.io/en/latest/>`_.
 
 
-Running tests
--------------
+Running the tests
+-----------------
 
-Testing is carried out with `pytest <http://pytest.org>`_. The following
-example shows how you can run the test suite and generate a coverage report:
+Testing is carried out with `pytest <https://docs.pytest.org/>`_:
 
 .. code-block::
 
-    $ pip install pytest pytest-pep8 dendropy biopython 
-    $ py.test -v --pep8
-    $ coverage run -m py.test
-    $ coverage report --include pandascharm.py
+    $ pytest -v test_pandascharm.py
+
+Test coverage can be calculated with `Coverage.py
+<https://coverage.readthedocs.io/>`_ using the following commands:
+
+.. code-block::
+
+    $ coverage run -m pytest
+    $ coverage report -m pandascharm.py
+
+The code follow style conventions in `PEP8
+<https://www.python.org/dev/peps/pep-0008/>`_, which can be checked
+with `pycodestyle <http://pycodestyle.pycqa.org>`_:
+
+.. code-block::
+
+    $ pycodestyle pandascharm.py test_pandascharm.py setup.py
 
 
 Usage
 -----
 
-Below are a few examples on how to use pandas-charm. The examples are 
-written with Python 3 code, but ``pandas-charm`` should work also with 
-Python 2.7. You need to install BioPython and/or DendroPy manually 
+The following examples show how to use pandas-charm. The examples are
+written with Python 3 code, but pandas-charm should work also with
+Python 2.7+. You need to install BioPython and/or DendroPy manually
 before you start:
 
 .. code-block::
@@ -95,9 +106,9 @@ DendroPy CharacterMatrix to pandas DataFrame
     t1  TCCAA
     t2  TGCAA
     t3  TG-AA
-    
-    >>> matrix = dendropy.DnaCharacterMatrix.get_from_string(
-    ...     dna_string, schema='phylip')
+
+    >>> matrix = dendropy.DnaCharacterMatrix.get(
+    ...     data=dna_string, schema='phylip')
     >>> df = pc.from_charmatrix(matrix)
     >>> df
       t1 t2 t3
@@ -107,8 +118,8 @@ DendroPy CharacterMatrix to pandas DataFrame
     3  A  A  A
     4  A  A  A
 
-By default, characters are stored as rows and sequences as columns 
-in the DataFrame. If you want rows to hold sequences, just transpose 
+By default, characters are stored as rows and sequences as columns
+in the DataFrame. If you want rows to hold sequences, just transpose
 the matrix in pandas:
 
 .. code-block:: pycon
@@ -139,7 +150,7 @@ pandas DataFrame to Dendropy CharacterMatrix
     2  C  C  -
     3  A  A  A
     4  A  A  A
-    
+
     >>> matrix = pc.to_charmatrix(df, data_type='dna')
     >>> print(matrix.as_string('phylip'))
     3 5
@@ -194,35 +205,70 @@ pandas DataFrame to BioPython MultipleSeqAlignment
     2  C  C  -
     3  A  A  A
     4  A  A  A
-    
+
     >>> alignment = pc.to_bioalignment(df, alphabet='generic_dna')
     >>> print(alignment)
     SingleLetterAlphabet() alignment with 3 rows and 5 columns
     TCCAA t1
     TGCAA t2
     TG-AA t3
-    
+
+
+Python dictionary to pandas DataFrame
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+.. code-block:: pycon
+
+    >>> import pandas as pd
+    >>> import pandascharm as pc
+    >>> d = {
+    ...     't1': 'TCCAA',
+    ...     't2': 'TGCAA',
+    ...     't3': 'TG-AA'
+    ... }
+    >>> df = pc.from_dict(d)
+    >>> df
+      t1 t2 t3
+    0  T  T  T
+    1  C  G  G
+    2  C  C  -
+    3  A  A  A
+    4  A  A  A
+
+
+pandas DataFrame to Python dictionary 
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+.. code-block:: pycon
+
+    >>> import pandas as pd
+    >>> import pandascharm as pc
+    >>> df = pd.DataFrame({
+    ...     't1': ['T', 'C', 'C', 'A', 'A'],
+    ...     't2': ['T', 'G', 'C', 'A', 'A'],
+    ...     't3': ['T', 'G', '-', 'A', 'A']})
+    >>> pc.to_dict(df)
+    {'t1': 'TCCAA', 't2': 'TGCAA', 't3': 'TG-AA'}
 
 
 The name
 --------
 
-``pandas-charm`` got its name from the pandas library plus an acronym for
+pandas-charm got its name from the pandas library plus an acronym for
 CHARacter Matrix.
 
 
 License
 -------
 
-``pandas-charm`` is distributed under the 
-`MIT license <https://opensource.org/licenses/MIT>`_.
+pandas-charm is distributed under the `MIT license <https://opensource.org/licenses/MIT>`_.
 
 
 Citing
 ------
 
-If you use results produced with this package in a scientific 
-publication, please just mention the package name in the text and 
+If you use results produced with this package in a scientific
+publication, please just mention the package name in the text and
 cite the Zenodo DOI of this project:
 
 |DOI-URI|
@@ -236,13 +282,19 @@ Author
 
 Markus Englund, `orcid.org/0000-0003-1688-7112 <http://orcid.org/0000-0003-1688-7112>`_
 
+
 .. |Build-Status| image:: https://travis-ci.org/jmenglund/pandas-charm.svg?branch=master
    :target: https://travis-ci.org/jmenglund/pandas-charm
+   :alt: Build status
 .. |Coverage-Status| image:: https://codecov.io/gh/jmenglund/pandas-charm/branch/master/graph/badge.svg
    :target: https://codecov.io/gh/jmenglund/pandas-charm
+   :alt: Coverage status
 .. |PyPI-Status| image:: https://img.shields.io/pypi/v/pandas-charm.svg
    :target: https://pypi.python.org/pypi/pandas-charm
+   :alt: PyPI status
 .. |License| image:: https://img.shields.io/pypi/l/pandas-charm.svg
    :target: https://raw.githubusercontent.com/jmenglund/pandas-charm/master/LICENSE.txt
-.. |DOI-URI| image:: https://zenodo.org/badge/DOI/10.5281/zenodo.848750.svg
-   :target: https://doi.org/10.5281/zenodo.848750
+   :alt: License
+.. |DOI-URI| image:: https://zenodo.org/badge/62513333.svg
+   :target: https://zenodo.org/badge/latestdoi/62513333
+   :alt: DOI

pandascharm.py

@@ -6,7 +6,7 @@
 
 __author__ = 'Markus Englund'
 __license__ = 'MIT'
-__version__ = '0.1.3'
+__version__ = '0.2.0'
 
 
 def frame_as_categorical(frame, include_categories=None):
@@ -83,6 +83,15 @@ def from_charmatrix(charmatrix, categorical=True):
     return new_frame
 
 
+def from_dict(d, categorical=True):
+    d_seq_list = {k: list(v) for (k, v) in d.items()}
+    frame = pandas.DataFrame(d_seq_list)
+    if categorical:
+        return frame_as_categorical(frame)
+    else:
+        return frame
+
+
 def to_bioalignment(frame, alphabet='generic_alphabet'):
     """
     Convert a pandas DataFrame to a BioPython MultipleSeqAlignment.
@@ -150,3 +159,7 @@ def to_charmatrix(frame, data_type):
     taxon_names = list(frame.columns)
     charmatrix.taxon_namespace.sort(key=lambda x: taxon_names.index(x.label))
     return charmatrix
+
+
+def to_dict(frame, into=dict):
+    return frame.apply(lambda x: ''.join(x)).to_dict(into=into)