From 0cf2f57f8c5096857ca53aa47525633e1051513d Mon Sep 17 00:00:00 2001 From: rasbt Date: Mon, 3 Aug 2020 20:09:28 -0500 Subject: [PATCH 1/6] fix links in readme --- README.md | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/README.md b/README.md index 2611166..032844a 100644 --- a/README.md +++ b/README.md @@ -1,4 +1,4 @@ -![Logo](./docs/sources/img/logos/logo.png) +![Logo](./docs/img/logos/logo.png) **Working with molecular structures in pandas DataFrames** @@ -34,7 +34,7 @@ So, why don't we take pandas to the structural biology world? Working with molec ## Examples -![3eiy](./docs/sources/img/index/3eiy.png) +![3eiy](./docs/img/index/3eiy.png) ```python # Initialize a new PandasPdb object @@ -44,13 +44,13 @@ So, why don't we take pandas to the structural biology world? Working with molec >>> ppdb.df['ATOM'].head() ``` -![3eiy head](./docs/sources/img/index/3eiy_head.png) +![3eiy head](./docs/img/index/3eiy_head.png)



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The CHANGELOG for the current development version is available at -https://github.com/rasbt/biopandas/blob/master/docs/sources/CHANGELOG.md.

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0.2.5 (07-09-2019)

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0.2.4 (02-05-2019)

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0.2.3 (03-29-2018)

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0.2.2 (06-07-2017)

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0.2.1 (2017-05-11)

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  • The amino3to1 method of biopandas.pdb.PandasPDB objects now returns a pandas DataFrame instead of a pandas Series object. The returned data frame has two columns, 'chain_id' and 'residue_name', where the former contains the chain ID of the amino acid and the latter contains the 1-letter amino acid code, respectively.
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  • Significant speed improvements of the distance method of both PandasPdb and PandasMol2 (now about 300 percent faster than previously).
    • -
-
Bug Fixes
-
    -
  • The amino3to1 method of biopandas.pdb.PandasPDB objects now handles multi-chain proteins correctly.
    • -
  • The amino3to1 method of biopandas.pdb.PandasPDB objects now also works as expected if the 'ATOM' entry DataFrame contains disordered DataFrame indices or duplicate DataFrame index values.
    • -
-

0.2.0 (2017-04-02)

-
Downloads
- -
New Features
-
    -
  • Added an amino3to1 method to PandasPdb data frames to convert 3-amino acid letter codes to 1-letter codes.
    • -
  • Added a distance method to PandasPdb data frames to compute the Euclidean distance between atoms and a reference point.
    • -
  • Added the PandasMol2 class for working with Tripos MOL2 files in pandas DataFrames.
    • -
-
Changes
-
    -
  • PandasPDB was renamed to PandasPdb.
    • -
  • Raises a warning if PandasPdb is written to PDB and ATOM and HETAM section contains unexpected columns; these columns will now be skipped.
    • -
-
Bug Fixes
-
    -
  • -
    • -
-

0.1.5 (2016-11-19)

-
Downloads
- -
New Features
-
    -
  • Added an impute_element method to PandasPDB objects to infer the Element Symbol from the Atom Name column.
    • -
  • Added two new selection types for PandasPDB ATOM and HETATM coordinate sections: 'heavy' and 'carbon'.
    • -
-
Changes
-
    -
  • Include test data in the PyPI package; add install_requires for pandas.
    • -
  • The 'hydrogen' atom selection in PandasPDB methods is now based on the element type instead of the atom name.
    • -
  • By default, the RMSD is now computed on all atoms unless a specific selection is defined.
    • -
-
Bug Fixes
-
    -
  • -
    • -
-

0.1.4 (2015-11-24)

-
Downloads
- -
New Features
-

-

-
Changes
-
    -
  • Needed to bump the version number due to a bug in the PyPI setup.py script.
    • -
  • Support for the old pandas sorting syntax (DataFrame.sort vs DataFrame.sort_values) incl. DeprecationWarning.
    • -
-
Bug Fixes
-

-

-

0.1.3 (2015-11-23)

-
New Features
-

-

-
Changes
-

-

-
Bug Fixes
-
    -
  • Exception handling in tests if PDB goes down (which just happened).
    • -
  • Added a separate ANISOU engine to handle those records correctly.
    • -
-

0.1.2 (2015-11-23)

-
    -
  • First Release.
    • -
-
- - - - - - - - - - - - diff --git a/site/CONTRIBUTING/index.html b/site/CONTRIBUTING/index.html deleted file mode 100644 index 687124f..0000000 --- a/site/CONTRIBUTING/index.html +++ /dev/null @@ -1,481 +0,0 @@ - - - - - - - - - - - - Contributing - BioPandas - - - - - - - - - - - - - - - - - - - -
-
-
- -

How to Contribute

-

I would be very happy about any kind of contributions that help to improve and extend the functionality of biopandas.

-

Quick Contributor Checklist

-

This is a quick checklist about the different steps of a typical contribution to biopandas and -other open source projects. Consider copying this list to a local text file (or the issue tracker) -and checking off items as you go.

-
    -
  1. [ ] Open a new "issue" on GitHub to discuss the new feature / bug fix
    2. -
  2. [ ] Fork the biopandas repository from GitHub (if not already done earlier)
    3. -
  3. [ ] Create and checkout a new topic branch
    4. -
  4. [ ] Implement new feature or apply the bug-fix
    5. -
  5. [ ] Add appropriate unit test functions
    6. -
  6. [ ] Run nosetests -sv and make sure that all unit tests pass
    7. -
  7. [ ] Check/improve the test coverage by running nosetests --with-coverage
    8. -
  8. [ ] Add a note about the change to the ./docs/sources/CHANGELOG.md file
    9. -
  9. [ ] Modify documentation in the appropriate location under biopandas/docs/sources/
    10. -
  10. [ ] Push the topic branch to the server and create a pull request
    11. -
  11. [ ] Check the Travis-CI build passed at https://travis-ci.org/rasbt/biopandas
    12. -
  12. [ ] Check/improve the unit test coverage at https://coveralls.io/github/rasbt/biopandas
    13. -
  13. [ ] Check/improve the code health at https://landscape.io/github/rasbt/biopandas
    14. -
  14. [ ] Squash many small commits to a larger commit
    15. -
-


-

Getting Started - Creating a New Issue and Forking the Repository

-
    -
  • If you don't have a GitHub account yet, please create one to contribute to this project.
    • -
  • Please submit a ticket for your issue to discuss the fix or new feature before too much time and effort is spent for the implementation.
    • -
-

-
    -
  • Fork the biopandas repository from the GitHub web interface.
    • -
-

-
    -
  • Clone the biopandas repository to your local machine
      -
    • git clone https://github.com/<your_username>/biopandas.git
      • -
    -
    • -
-

Syncing an Existing Fork

-

If you already forked biopandas earlier, you can bring you "Fork" up to date -with the master branch as follows:

-

1. Configuring a remote that points to the upstream repository on GitHub

-

List the current configured remote repository for your fork by executing

-
$ git remote -v
-
- -

If you see something like

-
origin  https://github.com/<your username>/biopandas.git (fetch)
-origin  https://github.com/<your username>/biopandas.git (push)
-
- -

you need to specify a new remote upstream repository via

-
$ git remote add upstream https://github.com/rasbt/biopandas.git
-
- -

Now, verify the new upstream repository you've specified for your fork by executing

-
$ git remote -v
-
- -

You should see following output if everything is configured correctly:

-
origin  https://github.com/<your username>/biopandas.git (fetch)
-origin  https://github.com/<your username>/biopandas.git (push)
-upstream    https://github.com/rasbt/biopandas.git (fetch)
-upstream    https://github.com/rasbt/biopandas.git (push)
-
- -

2. Syncing your Fork

-

First, fetch the updates of the original project's master branch by executing:

-
$ git fetch upstream
-
- -

You should see the following output

-
remote: Counting objects: xx, done.
-remote: Compressing objects: 100% (xx/xx), done.
-remote: Total xx (delta xx), reused xx (delta x)
-Unpacking objects: 100% (xx/xx), done.
-From https://github.com/rasbt/biopandas
- * [new branch]      master     -> upstream/master
-
- -

This means that the commits to the rasbt/biopandas master branch are now -stored in the local branch upstream/master.

-

If you are not already on your local project's master branch, execute

-
$ git checkout master
-
- -

Finally, merge the changes in upstream/master to your local master branch by -executing

-
$ git merge upstream/master
-
- -

which will give you an output that looks similar to

-
Updating xxx...xxx
-Fast-forward
-SOME FILE1                    |    12 +++++++
-SOME FILE2                    |    10 +++++++
-2 files changed, 22 insertions(+),
-
- -

Making Changes in a New Topic Branch

-

1. Creating a new feature branch

-

Please avoid working directly on the master branch but create a new feature branch:

-
$ git branch <new_feature>
-
- -

Switch to the new feature branch by executing

-
$ git checkout <new_feature>
-
- -

2. Developing the new feature / bug fix

-

3. Testing your code

-

Adding/modifying the unit tests and check if they pass:

-
$ nosetests -sv
-
- -
$ nosetests --with-coverage
-
- -

4. Documenting the changes

-

Please add an entry to the biopandas/docs/sources/CHANGELOG.md file. -If it is a new feature, it would also be nice if you could update the documentation in appropriate location in biopandas/sources.

-

5. Committing the changes

-

When you are ready to commit the changes, please provide a meaningful commit message:

-
$ git add <modifies_files> # or `git add .`
-$ git commit -m '<meaningful commit message>'
-
- -

6. Optional: squashing commits

-

If you made multiple smaller commits, it would be nice if you could group them into a larger, summarizing commit. First, list your recent commit via

-
$ git log
-
- -

which will list the commits from newest to oldest in the following format by default:

-
commit 046e3af8a9127df8eac879454f029937c8a31c41
-Author: rasbt <mail@sebastianraschka.com>
-Date:   Tue Nov 24 03:46:37 2015 -0500
-
-    fixed setup.py
-
-commit c3c00f6ba0e8f48bbe1c9081b8ae3817e57ecc5c
-Author: rasbt <mail@sebastianraschka.com>
-Date:   Tue Nov 24 03:04:39 2015 -0500
-
-        documented feature x
-
-commit d87934fe8726c46f0b166d6290a3bf38915d6e75
-Author: rasbt <mail@sebastianraschka.com>
-Date:   Tue Nov 24 02:44:45 2015 -0500
-
-        added support for feature x
-
- -

Assuming that it would make sense to group these 3 commits into one, we can execute

-
$ git rebase -i HEAD~3
-
- -

which will bring our default git editor with the following contents:

-
pick d87934f added support for feature x
-pick c3c00f6 documented feature x
-pick 046e3af fixed setup.py
-
- -

Since c3c00f6 and 046e3af are related to the original commit of feature x, let's keep the d87934f and squash the 2 following commits into this initial one by changes the lines to

-
pick d87934f added support for feature x
-squash c3c00f6 documented feature x
-squash 046e3af fixed setup.py
-
- -

Now, save the changes in your editor. Now, quitting the editor will apply the rebase changes, and the editor will open a second time, prompting you to enter a new commit message. In this case, we could enter support for feature x to summarize the contributions.

-

7. Uploading the changes

-

Push your changes to a topic branch to the git server by executing:

-
$ git push origin <feature_branch>
-
- -

8. Submitting a pull request

-

Go to your GitHub repository online, select the new feature branch, and submit a new pull request:

-

-

Notes for the Developers

-

Building the documentation

-

The documentation is built via MkDocs; to ensure that the documentation is rendered correctly, you can view the documentation locally by executing mkdocs serve from the biopandas/docs directory.

-

For example,

-
~/github/biopandas/docs$ mkdocs serve
-
- -

1. Editing the Tutorials

-

Please note that documents containing code examples are generated from IPython Notebook files and converted to markdown via

-
~/github/biopandas/docs/sources/tutorials$ nbconvert --to markdown <file.ipynb>
-
- -

The markdown file should be placed into the documentation directory at biopandas/docs/sources to build the documentation via MkDocs. -If you are adding a new document, please also include it in the pages section in the biopandas/docs/mkdocs.yml file.

-

2. Building the API documentation

-

To build the API documentation, navigate to biopandas/docs and execute the make_api.py file from this directory via

-
~/github/biopandas/docs$ python make_api.py
-
- -

This should place the API documentation into the correct directories in biopandas/docs/sources/api.

-

3. Building static HTML files of the documentation

-

Build the static HTML files of the biopandas documentation via

-
~/github/biopandas/docs$ mkdocs build --clean
-
- -

To deploy the documentation, execute

-
~/github/biopandas/docs$ mkdocs gh-deploy --clean
-
- -

Uploading a new version to PyPI

-

1. Creating a new testing environment

-

Assuming we are using conda, create a new python environment via

-
$ conda create -n 'biopandas-testing' python=3 pandas
-
- -

Next, activate the environment by executing

-
$ source activate biopandas-testing
-
- -

2. Installing the package from local files

-

Test the installation by executing

-
$ python setup.py install --record files.txt
-
- -

the --record files.txt flag will create a files.txt file listing the locations where these files will be installed.

-

Try to import the package to see if it works, for example, by executing

-
$ python -c 'import biopandas; print(biopandas.__file__)'
-
- -

If everything seems to be fine, remove the installation via

-
$ cat files.txt | xargs rm -rf ; rm files.txt
-
- -

Next, test if pip is able to install the packages. First, navigate to a different directory, and from there, install the package:

-
$ pip install code/biopandas/
-
- -

and uninstall it again

-
$ pip uninstall biopandas
-
- -

3. Deploying the package

-

Consider deploying the package to the PyPI test server first. The setup instructions can be found here.

-
$ python setup.py sdist bdist_wheel upload -r https://testpypi.python.org/pypi
-
- -

Test if it can be installed from there by executing

-
$ pip install -i https://testpypi.python.org/pypi biopandas
-
- -

and uninstall it

-
$ pip uninstall biopandas
-
- -

After this dry-run succeeded, repeat this process using the "real" PyPI:

-
$ python setup.py sdist bdist_wheel upload
-
- -

4. Removing the virtual environment

-

Finally, to cleanup our local drive, remove the virtual testing environment via

-
$ conda remove --name 'biopandas-testing' --all
-
-
- - - - - - - - - - - - diff --git a/site/api_modules/biopandas.mol2/PandasMol2/index.html b/site/api_modules/biopandas.mol2/PandasMol2/index.html deleted file mode 100644 index d97e6aa..0000000 --- a/site/api_modules/biopandas.mol2/PandasMol2/index.html +++ /dev/null @@ -1,378 +0,0 @@ - - - - - - - - - - - - PandasMol2 - BioPandas - - - - - - - - - - - - - - - - - - - -
-
-
- -

PandasMol2

-

PandasMol2()

-

Object for working with Tripos Mol2 structure files.

-

Attributes

-
    -
  • -

    df : pandas.DataFrame

    -

    DataFrame of a Mol2's ATOM section

    -
    • -
  • -

    mol2_text : str

    -

    Mol2 file contents in string format

    -
    • -
  • -

    code : str

    -

    ID, code, or name of the molecule stored

    -
    • -
  • -

    pdb_path : str

    -

    Location of the MOL2 file that was read in via read_mol2

    -
    • -
-

Methods

-
- -

distance(xyz=(0.0, 0.0, 0.0))

-

Computes Euclidean distance between atoms in - self.df and a 3D point.

-

Parameters

-
    -
  • -

    xyz : tuple (0.00, 0.00, 0.00)

    -

    X, Y, and Z coordinate of the reference center for the distance -computation

    -
    • -
-

Returns

-
    -
  • -

    pandas.Series : Pandas Series object containing the Euclidean

    -

    distance between the atoms in the atom section and xyz.

    -
    • -
-
- -

distance_df(df, xyz=(0.0, 0.0, 0.0))

-

Computes Euclidean distance between atoms and a 3D point.

-

Parameters

-
    -
  • -

    df : DataFrame

    -

    DataFrame containing entries similar to the PandasMol2.df -format for the -the distance computation to the xyz reference coordinates.

    -
    • -
  • -

    xyz : tuple (0.00, 0.00, 0.00)

    -

    X, Y, and Z coordinate of the reference center for the distance -computation

    -
    • -
-

Returns

-
    -
  • -

    pandas.Series : Pandas Series object containing the Euclidean

    -

    distance between the atoms in the atom section and xyz.

    -
    • -
-
- -

read_mol2(path, columns=None)

-

Reads Mol2 files (unzipped or gzipped) from local drive

-
Note that if your mol2 file contains more than one molecule,
-only the first molecule is loaded into the DataFrame
-
-

Attributes

-
    -
  • -

    path : str

    -

    Path to the Mol2 file in .mol2 format or gzipped format (.mol2.gz)

    -
    • -
  • -

    columns : dict or None (default: None)

    -

    If None, this methods expects a 9-column ATOM section that contains -the following columns:

    -

    {0:('atom_id', int), 1:('atom_name', str), -2:('x', float), 3:('y', float), 4:('z', float), -5:('atom_type', str), 6:('subst_id', int), -7:('subst_name', str), 8:('charge', float)}

    -

    If your Mol2 files are formatted differently, you can provide your -own column_mapping dictionary in a format similar to the one above. -However, note that not all assert_raise_message methods -may be supported then.

    -
    • -
-

Returns

-

self

-
- -

read_mol2_from_list(mol2_lines, mol2_code, columns=None)

-

Reads Mol2 file from a list into DataFrames

-

Attributes

-
    -
  • -

    mol2_lines : list

    -

    A list of lines containing the mol2 file contents. For example, -['@MOLECULE\n', -'ZINC38611810\n', -' 65 68 0 0 0\n', -'SMALL\n', -'NO_CHARGES\n', -'\n', -'@ATOM\n', -' 1 C1 -1.1786 2.7011 -4.0323 C.3 1 <0> -0.1537\n', -' 2 C2 -1.2950 1.2442 -3.5798 C.3 1 <0> -0.1156\n', -...]

    -
    • -
  • -

    mol2_code : str or None

    -

    Name or ID of the molecule.

    -
    • -
  • -

    columns : dict or None (default: None)

    -

    If None, this methods expects a 9-column ATOM section that contains -the following columns: -{0:('atom_id', int), 1:('atom_name', str), -2:('x', float), 3:('y', float), 4:('z', float), -5:('atom_type', str), 6:('subst_id', int), -7:('subst_name', str), 8:('charge', float)} -If your Mol2 files are formatted differently, you can provide your -own column_mapping dictionary in a format similar to the one above. -However, note that not all assert_raise_message methods may be -supported then.

    -
    • -
-

Returns

-

self

-
- -

rmsd(df1, df2, heavy_only=True)

-

Compute the Root Mean Square Deviation between molecules

-

Parameters

-
    -
  • -

    df1 : pandas.DataFrame

    -

    DataFrame with HETATM, ATOM, and/or ANISOU entries

    -
    • -
  • -

    df2 : pandas.DataFrame

    -

    Second DataFrame for RMSD computation against df1. Must have the -same number of entries as df1

    -
    • -
  • -

    heavy_only : bool (default: True)

    -

    Which atoms to compare to compute the RMSD. If True (default), -computes the RMSD between non-hydrogen atoms only.

    -
    • -
-

Returns

-
    -
  • -

    rmsd : float

    -

    Root Mean Square Deviation between df1 and df2

    -
    • -
-

Properties

-
- -

df

-

Acccesses the pandas DataFrame

-
- - - - - - - - - - - - diff --git a/site/api_modules/biopandas.mol2/split_multimol2/index.html b/site/api_modules/biopandas.mol2/split_multimol2/index.html deleted file mode 100644 index 4c200f0..0000000 --- a/site/api_modules/biopandas.mol2/split_multimol2/index.html +++ /dev/null @@ -1,223 +0,0 @@ - - - - - - - - - - - - Split multimol2 - BioPandas - - - - - - - - - - - - - - - - - - - -
-
-
- -

split_multimol2

-

split_multimol2(mol2_path)

-

Splits a multi-mol2 file into individual Mol2 file contents.

-

Parameters

-
    -
  • -

    mol2_path : str

    -

    Path to the multi-mol2 file. Parses gzip files if the filepath -ends on .gz.

    -
    • -
-

Returns

-

A generator object for lists for every extracted mol2-file. Lists contain - the molecule ID and the mol2 file contents. - e.g., ['ID1234', ['@MOLECULE\n', '...']]. Note that bytestrings - are returned (for reasons of efficieny) if the Mol2 content is read - from a gzip (.gz) file.

-
- - - - - - - - - - - - diff --git a/site/api_modules/biopandas.pdb/PandasPdb/index.html b/site/api_modules/biopandas.pdb/PandasPdb/index.html deleted file mode 100644 index bc0beda..0000000 --- a/site/api_modules/biopandas.pdb/PandasPdb/index.html +++ /dev/null @@ -1,479 +0,0 @@ - - - - - - - - - - - - PandasPdb - BioPandas - - - - - - - - - - - - - - - - - - - -
-
-
- -

PandasPdb

-

PandasPdb()

-

Object for working with Protein Databank structure files.

-

Attributes

-
    -
  • -

    df : dict

    -

    Dictionary storing pandas DataFrames for PDB record sections. -The dictionary keys are {'ATOM', 'HETATM', 'ANISOU', 'OTHERS'} -where 'OTHERS' contains all entries that are not parsed as -'ATOM', 'HETATM', or 'ANISOU'.

    -
    • -
  • -

    pdb_text : str

    -

    PDB file contents in raw text format.

    -
    • -
  • -

    pdb_path : str

    -

    Location of the PDB file that was read in via read_pdb -or URL of the page where the PDB content was fetched from -if fetch_pdb was called.

    -
    • -
  • -

    header : str

    -

    PDB file description.

    -
    • -
  • -

    code : str

    -

    PDB code

    -
    • -
-

Methods

-
- -

amino3to1(record='ATOM', residue_col='residue_name', fillna='?')

-

Creates 1-letter amino acid codes from DataFrame

-
Non-canonical amino-acids are converted as follows:
-ASH (protonated ASP) => D
-CYX (disulfide-bonded CYS) => C
-GLH (protonated GLU) => E
-HID/HIE/HIP (different protonation states of HIS) = H
-HYP (hydroxyproline) => P
-MSE (selenomethionine) => M
-
-

Parameters

-
    -
  • -

    record : str, default: 'ATOM'

    -

    Specfies the record DataFrame.

    -
    • -
  • -

    residue_col : str, default: 'residue_name'

    -

    Column in record DataFrame to look for 3-letter amino acid -codes for the conversion.

    -
    • -
  • -

    fillna : str, default: '?'

    -

    Placeholder string to use for unknown amino acids.

    -
    • -
-

Returns

-
    -
  • -

    pandas.DataFrame : Pandas DataFrame object consisting of two columns,

    -

    'chain_id' and 'residue_name', where the former contains -the chain ID of the amino acid and the latter -contains the 1-letter amino acid code, respectively.

    -
    • -
-
- -

distance(xyz=(0.0, 0.0, 0.0), records=('ATOM', 'HETATM'))

-

Computes Euclidean distance between atoms and a 3D point.

-

Parameters

-
    -
  • -

    xyz : tuple, default: (0.00, 0.00, 0.00)

    -

    X, Y, and Z coordinate of the reference center for the distance -computation.

    -
    • -
  • -

    records : iterable, default: ('ATOM', 'HETATM')

    -

    Specify which record sections to consider. For example, to consider -both protein and ligand atoms, set records=('ATOM', 'HETATM'). -This setting is ignored if df is not set to None. -For downward compatibility, a string argument is still supported -but deprecated and will be removed in future versions.

    -
    • -
-

Returns

-
    -
  • -

    pandas.Series : Pandas Series object containing the Euclidean

    -

    distance between the atoms in the record section and xyz.

    -
    • -
-
- -

distance_df(df, xyz=(0.0, 0.0, 0.0))

-

Computes Euclidean distance between atoms and a 3D point.

-

Parameters

-
    -
  • -

    df : DataFrame

    -

    DataFrame containing entries in the PandasPdb.df['ATOM'] -or PandasPdb.df['HETATM'] format for the -the distance computation to the xyz reference coordinates.

    -
    • -
  • -

    xyz : tuple, default: (0.00, 0.00, 0.00)

    -

    X, Y, and Z coordinate of the reference center for the distance -computation.

    -
    • -
-

Returns

-
    -
  • -

    pandas.Series : Pandas Series object containing the Euclidean

    -

    distance between the atoms in the record section and xyz.

    -
    • -
-
- -

fetch_pdb(pdb_code)

-

Fetches PDB file contents from the Protein Databank at rcsb.org.

-

Parameters

-
    -
  • -

    pdb_code : str

    -

    A 4-letter PDB code, e.g., "3eiy".

    -
    • -
-

Returns

-

self

-
- -

get(s, df=None, invert=False, records=('ATOM', 'HETATM'))

-

Filter PDB DataFrames by properties

-

Parameters

-
    -
  • -

    s : str in {'main chain', 'hydrogen', 'c-alpha', 'heavy'}

    -

    String to specify which entries to return.

    -
    • -
  • -

    df : pandas.DataFrame, default: None

    -

    Optional DataFrame to perform the filter operation on. -If df=None, filters on self.df['ATOM'].

    -
    • -
  • -

    invert : bool, default: True

    -

    Inverts the search query. For example if s='hydrogen' and -invert=True, all but hydrogen entries are returned.

    -
    • -
  • -

    records : iterable, default: ('ATOM', 'HETATM')

    -

    Specify which record sections to consider. For example, to consider -both protein and ligand atoms, set records=('ATOM', 'HETATM'). -This setting is ignored if df is not set to None. -For downward compatibility, a string argument is still supported -but deprecated and will be removed in future versions.

    -
    • -
-

Returns

-
    -
  • -

    df : pandas.DataFrame

    -

    Returns a DataFrame view on the filtered entries.

    -
    • -
-
- -

impute_element(records=('ATOM', 'HETATM'), inplace=False)

-

Impute element_symbol from atom_name section.

-

Parameters

-
    -
  • -

    records : iterable, default: ('ATOM', 'HETATM')

    -

    Coordinate sections for which the element symbols should be -imputed.

    -
    • -
  • -

    inplace : bool, (default: False

    -

    Performs the operation in-place if True and returns a copy of the -PDB DataFrame otherwise.

    -
    • -
-

Returns

-

DataFrame

-
- -

parse_sse()

-

Parse secondary structure elements

-
- -

read_pdb(path)

-

Read PDB files (unzipped or gzipped) from local drive

-

Attributes

-
    -
  • -

    path : str

    -

    Path to the PDB file in .pdb format or gzipped format (.pdb.gz).

    -
    • -
-

Returns

-

self

-
- -

rmsd(df1, df2, s=None, invert=False)

-

Compute the Root Mean Square Deviation between molecules.

-

Parameters

-
    -
  • -

    df1 : pandas.DataFrame

    -

    DataFrame with HETATM, ATOM, and/or ANISOU entries.

    -
    • -
  • -

    df2 : pandas.DataFrame

    -

    Second DataFrame for RMSD computation against df1. Must have the -same number of entries as df1.

    -
    • -
  • -

    s : {'main chain', 'hydrogen', 'c-alpha', 'heavy', 'carbon'} or None,

    -

    default: None -String to specify which entries to consider. If None, considers -all atoms for comparison.

    -
    • -
  • -

    invert : bool, default: False

    -

    Inverts the string query if true. For example, the setting -s='hydrogen', invert=True computes the RMSD based on all -but hydrogen atoms.

    -
    • -
-

Returns

-
    -
  • -

    rmsd : float

    -

    Root Mean Square Deviation between df1 and df2

    -
    • -
-
- -

to_pdb(path, records=None, gz=False, append_newline=True)

-

Write record DataFrames to a PDB file or gzipped PDB file.

-

Parameters

-
    -
  • -

    path : str

    -

    A valid output path for the pdb file

    -
    • -
  • -

    records : iterable, default: None

    -

    A list of PDB record sections in -{'ATOM', 'HETATM', 'ANISOU', 'OTHERS'} that are to be written. -Writes all lines to PDB if records=None.

    -
    • -
  • -

    gz : bool, default: False

    -

    Writes a gzipped PDB file if True.

    -
    • -
  • -

    append_newline : bool, default: True

    -

    Appends a new line at the end of the PDB file if True

    -
    • -
-

Properties

-
- -

df

-

Acccess dictionary of pandas DataFrames for PDB record sections.

-
- - - - - - - - - - - - diff --git a/site/api_modules/biopandas.testutils/assert_raises/index.html b/site/api_modules/biopandas.testutils/assert_raises/index.html deleted file mode 100644 index 5806552..0000000 --- a/site/api_modules/biopandas.testutils/assert_raises/index.html +++ /dev/null @@ -1,230 +0,0 @@ - - - - - - - - - - - - Assert raises - BioPandas - - - - - - - - - - - - - - - - - - - -
-
-
- -

assert_raises

-

assert_raises(exception_type, message, func, args, *kwargs)

-

Check that an exception is raised with a specific message

-

Parameters

-
    -
  • -

    exception_type : exception

    -

    The exception that should be raised

    -
    • -
  • -

    message : str (default: None)

    -

    The error message that should be raised. Ignored if False or None

    -
    • -
  • -

    func : callable

    -

    The function that raises the exception

    -
    • -
  • -

    *args : positional arguments to func

    -
    • -
  • -

    **kwargs : keyword arguments to func

    -
    • -
-
- - - - - - - - - - - - diff --git a/site/api_subpackages/biopandas.mol2/index.html b/site/api_subpackages/biopandas.mol2/index.html deleted file mode 100644 index 4acddb1..0000000 --- a/site/api_subpackages/biopandas.mol2/index.html +++ /dev/null @@ -1,407 +0,0 @@ - - - - - - - - - - - - biopandas.mol2 - BioPandas - - - - - - - - - - - - - - - - - - - -
-
-
- -

biopandas version: 0.2.5

-

PandasMol2

-

PandasMol2()

-

Object for working with Tripos Mol2 structure files.

-

Attributes

-
    -
  • -

    df : pandas.DataFrame

    -

    DataFrame of a Mol2's ATOM section

    -
    • -
  • -

    mol2_text : str

    -

    Mol2 file contents in string format

    -
    • -
  • -

    code : str

    -

    ID, code, or name of the molecule stored

    -
    • -
  • -

    pdb_path : str

    -

    Location of the MOL2 file that was read in via read_mol2

    -
    • -
-

Methods

-
- -

distance(xyz=(0.0, 0.0, 0.0))

-

Computes Euclidean distance between atoms in - self.df and a 3D point.

-

Parameters

-
    -
  • -

    xyz : tuple (0.00, 0.00, 0.00)

    -

    X, Y, and Z coordinate of the reference center for the distance -computation

    -
    • -
-

Returns

-
    -
  • -

    pandas.Series : Pandas Series object containing the Euclidean

    -

    distance between the atoms in the atom section and xyz.

    -
    • -
-
- -

distance_df(df, xyz=(0.0, 0.0, 0.0))

-

Computes Euclidean distance between atoms and a 3D point.

-

Parameters

-
    -
  • -

    df : DataFrame

    -

    DataFrame containing entries similar to the PandasMol2.df -format for the -the distance computation to the xyz reference coordinates.

    -
    • -
  • -

    xyz : tuple (0.00, 0.00, 0.00)

    -

    X, Y, and Z coordinate of the reference center for the distance -computation

    -
    • -
-

Returns

-
    -
  • -

    pandas.Series : Pandas Series object containing the Euclidean

    -

    distance between the atoms in the atom section and xyz.

    -
    • -
-
- -

read_mol2(path, columns=None)

-

Reads Mol2 files (unzipped or gzipped) from local drive

-
Note that if your mol2 file contains more than one molecule,
-only the first molecule is loaded into the DataFrame
-
-

Attributes

-
    -
  • -

    path : str

    -

    Path to the Mol2 file in .mol2 format or gzipped format (.mol2.gz)

    -
    • -
  • -

    columns : dict or None (default: None)

    -

    If None, this methods expects a 9-column ATOM section that contains -the following columns:

    -

    {0:('atom_id', int), 1:('atom_name', str), -2:('x', float), 3:('y', float), 4:('z', float), -5:('atom_type', str), 6:('subst_id', int), -7:('subst_name', str), 8:('charge', float)}

    -

    If your Mol2 files are formatted differently, you can provide your -own column_mapping dictionary in a format similar to the one above. -However, note that not all assert_raise_message methods -may be supported then.

    -
    • -
-

Returns

-

self

-
- -

read_mol2_from_list(mol2_lines, mol2_code, columns=None)

-

Reads Mol2 file from a list into DataFrames

-

Attributes

-
    -
  • -

    mol2_lines : list

    -

    A list of lines containing the mol2 file contents. For example, -['@MOLECULE\n', -'ZINC38611810\n', -' 65 68 0 0 0\n', -'SMALL\n', -'NO_CHARGES\n', -'\n', -'@ATOM\n', -' 1 C1 -1.1786 2.7011 -4.0323 C.3 1 <0> -0.1537\n', -' 2 C2 -1.2950 1.2442 -3.5798 C.3 1 <0> -0.1156\n', -...]

    -
    • -
  • -

    mol2_code : str or None

    -

    Name or ID of the molecule.

    -
    • -
  • -

    columns : dict or None (default: None)

    -

    If None, this methods expects a 9-column ATOM section that contains -the following columns: -{0:('atom_id', int), 1:('atom_name', str), -2:('x', float), 3:('y', float), 4:('z', float), -5:('atom_type', str), 6:('subst_id', int), -7:('subst_name', str), 8:('charge', float)} -If your Mol2 files are formatted differently, you can provide your -own column_mapping dictionary in a format similar to the one above. -However, note that not all assert_raise_message methods may be -supported then.

    -
    • -
-

Returns

-

self

-
- -

rmsd(df1, df2, heavy_only=True)

-

Compute the Root Mean Square Deviation between molecules

-

Parameters

-
    -
  • -

    df1 : pandas.DataFrame

    -

    DataFrame with HETATM, ATOM, and/or ANISOU entries

    -
    • -
  • -

    df2 : pandas.DataFrame

    -

    Second DataFrame for RMSD computation against df1. Must have the -same number of entries as df1

    -
    • -
  • -

    heavy_only : bool (default: True)

    -

    Which atoms to compare to compute the RMSD. If True (default), -computes the RMSD between non-hydrogen atoms only.

    -
    • -
-

Returns

-
    -
  • -

    rmsd : float

    -

    Root Mean Square Deviation between df1 and df2

    -
    • -
-

Properties

-
- -

df

-

Acccesses the pandas DataFrame

-

split_multimol2

-

split_multimol2(mol2_path)

-

Splits a multi-mol2 file into individual Mol2 file contents.

-

Parameters

-
    -
  • -

    mol2_path : str

    -

    Path to the multi-mol2 file. Parses gzip files if the filepath -ends on .gz.

    -
    • -
-

Returns

-

A generator object for lists for every extracted mol2-file. Lists contain - the molecule ID and the mol2 file contents. - e.g., ['ID1234', ['@MOLECULE\n', '...']]. Note that bytestrings - are returned (for reasons of efficieny) if the Mol2 content is read - from a gzip (.gz) file.

-
- - - - - - - - - - - - diff --git a/site/api_subpackages/biopandas.pdb/index.html b/site/api_subpackages/biopandas.pdb/index.html deleted file mode 100644 index 3486afa..0000000 --- a/site/api_subpackages/biopandas.pdb/index.html +++ /dev/null @@ -1,490 +0,0 @@ - - - - - - - - - - - - biopandas.pdb - BioPandas - - - - - - - - - - - - - - - - - - - -
-
-
- -

biopandas version: 0.2.5

-

PandasPdb

-

PandasPdb()

-

Object for working with Protein Databank structure files.

-

Attributes

-
    -
  • -

    df : dict

    -

    Dictionary storing pandas DataFrames for PDB record sections. -The dictionary keys are {'ATOM', 'HETATM', 'ANISOU', 'OTHERS'} -where 'OTHERS' contains all entries that are not parsed as -'ATOM', 'HETATM', or 'ANISOU'.

    -
    • -
  • -

    pdb_text : str

    -

    PDB file contents in raw text format.

    -
    • -
  • -

    pdb_path : str

    -

    Location of the PDB file that was read in via read_pdb -or URL of the page where the PDB content was fetched from -if fetch_pdb was called.

    -
    • -
  • -

    header : str

    -

    PDB file description.

    -
    • -
  • -

    code : str

    -

    PDB code

    -
    • -
-

Methods

-
- -

amino3to1(record='ATOM', residue_col='residue_name', fillna='?')

-

Creates 1-letter amino acid codes from DataFrame

-
Non-canonical amino-acids are converted as follows:
-ASH (protonated ASP) => D
-CYX (disulfide-bonded CYS) => C
-GLH (protonated GLU) => E
-HID/HIE/HIP (different protonation states of HIS) = H
-HYP (hydroxyproline) => P
-MSE (selenomethionine) => M
-
-

Parameters

-
    -
  • -

    record : str, default: 'ATOM'

    -

    Specfies the record DataFrame.

    -
    • -
  • -

    residue_col : str, default: 'residue_name'

    -

    Column in record DataFrame to look for 3-letter amino acid -codes for the conversion.

    -
    • -
  • -

    fillna : str, default: '?'

    -

    Placeholder string to use for unknown amino acids.

    -
    • -
-

Returns

-
    -
  • -

    pandas.DataFrame : Pandas DataFrame object consisting of two columns,

    -

    'chain_id' and 'residue_name', where the former contains -the chain ID of the amino acid and the latter -contains the 1-letter amino acid code, respectively.

    -
    • -
-
- -

distance(xyz=(0.0, 0.0, 0.0), records=('ATOM', 'HETATM'))

-

Computes Euclidean distance between atoms and a 3D point.

-

Parameters

-
    -
  • -

    xyz : tuple, default: (0.00, 0.00, 0.00)

    -

    X, Y, and Z coordinate of the reference center for the distance -computation.

    -
    • -
  • -

    records : iterable, default: ('ATOM', 'HETATM')

    -

    Specify which record sections to consider. For example, to consider -both protein and ligand atoms, set records=('ATOM', 'HETATM'). -This setting is ignored if df is not set to None. -For downward compatibility, a string argument is still supported -but deprecated and will be removed in future versions.

    -
    • -
-

Returns

-
    -
  • -

    pandas.Series : Pandas Series object containing the Euclidean

    -

    distance between the atoms in the record section and xyz.

    -
    • -
-
- -

distance_df(df, xyz=(0.0, 0.0, 0.0))

-

Computes Euclidean distance between atoms and a 3D point.

-

Parameters

-
    -
  • -

    df : DataFrame

    -

    DataFrame containing entries in the PandasPdb.df['ATOM'] -or PandasPdb.df['HETATM'] format for the -the distance computation to the xyz reference coordinates.

    -
    • -
  • -

    xyz : tuple, default: (0.00, 0.00, 0.00)

    -

    X, Y, and Z coordinate of the reference center for the distance -computation.

    -
    • -
-

Returns

-
    -
  • -

    pandas.Series : Pandas Series object containing the Euclidean

    -

    distance between the atoms in the record section and xyz.

    -
    • -
-
- -

fetch_pdb(pdb_code)

-

Fetches PDB file contents from the Protein Databank at rcsb.org.

-

Parameters

-
    -
  • -

    pdb_code : str

    -

    A 4-letter PDB code, e.g., "3eiy".

    -
    • -
-

Returns

-

self

-
- -

get(s, df=None, invert=False, records=('ATOM', 'HETATM'))

-

Filter PDB DataFrames by properties

-

Parameters

-
    -
  • -

    s : str in {'main chain', 'hydrogen', 'c-alpha', 'heavy'}

    -

    String to specify which entries to return.

    -
    • -
  • -

    df : pandas.DataFrame, default: None

    -

    Optional DataFrame to perform the filter operation on. -If df=None, filters on self.df['ATOM'].

    -
    • -
  • -

    invert : bool, default: True

    -

    Inverts the search query. For example if s='hydrogen' and -invert=True, all but hydrogen entries are returned.

    -
    • -
  • -

    records : iterable, default: ('ATOM', 'HETATM')

    -

    Specify which record sections to consider. For example, to consider -both protein and ligand atoms, set records=('ATOM', 'HETATM'). -This setting is ignored if df is not set to None. -For downward compatibility, a string argument is still supported -but deprecated and will be removed in future versions.

    -
    • -
-

Returns

-
    -
  • -

    df : pandas.DataFrame

    -

    Returns a DataFrame view on the filtered entries.

    -
    • -
-
- -

impute_element(records=('ATOM', 'HETATM'), inplace=False)

-

Impute element_symbol from atom_name section.

-

Parameters

-
    -
  • -

    records : iterable, default: ('ATOM', 'HETATM')

    -

    Coordinate sections for which the element symbols should be -imputed.

    -
    • -
  • -

    inplace : bool, (default: False

    -

    Performs the operation in-place if True and returns a copy of the -PDB DataFrame otherwise.

    -
    • -
-

Returns

-

DataFrame

-
- -

parse_sse()

-

Parse secondary structure elements

-
- -

read_pdb(path)

-

Read PDB files (unzipped or gzipped) from local drive

-

Attributes

-
    -
  • -

    path : str

    -

    Path to the PDB file in .pdb format or gzipped format (.pdb.gz).

    -
    • -
-

Returns

-

self

-
- -

rmsd(df1, df2, s=None, invert=False)

-

Compute the Root Mean Square Deviation between molecules.

-

Parameters

-
    -
  • -

    df1 : pandas.DataFrame

    -

    DataFrame with HETATM, ATOM, and/or ANISOU entries.

    -
    • -
  • -

    df2 : pandas.DataFrame

    -

    Second DataFrame for RMSD computation against df1. Must have the -same number of entries as df1.

    -
    • -
  • -

    s : {'main chain', 'hydrogen', 'c-alpha', 'heavy', 'carbon'} or None,

    -

    default: None -String to specify which entries to consider. If None, considers -all atoms for comparison.

    -
    • -
  • -

    invert : bool, default: False

    -

    Inverts the string query if true. For example, the setting -s='hydrogen', invert=True computes the RMSD based on all -but hydrogen atoms.

    -
    • -
-

Returns

-
    -
  • -

    rmsd : float

    -

    Root Mean Square Deviation between df1 and df2

    -
    • -
-
- -

to_pdb(path, records=None, gz=False, append_newline=True)

-

Write record DataFrames to a PDB file or gzipped PDB file.

-

Parameters

-
    -
  • -

    path : str

    -

    A valid output path for the pdb file

    -
    • -
  • -

    records : iterable, default: None

    -

    A list of PDB record sections in -{'ATOM', 'HETATM', 'ANISOU', 'OTHERS'} that are to be written. -Writes all lines to PDB if records=None.

    -
    • -
  • -

    gz : bool, default: False

    -

    Writes a gzipped PDB file if True.

    -
    • -
  • -

    append_newline : bool, default: True

    -

    Appends a new line at the end of the PDB file if True

    -
    • -
-

Properties

-
- -

df

-

Acccess dictionary of pandas DataFrames for PDB record sections.

-
- - - - - - - - - - - - diff --git a/site/api_subpackages/biopandas.testutils/index.html b/site/api_subpackages/biopandas.testutils/index.html deleted file mode 100644 index d287f35..0000000 --- a/site/api_subpackages/biopandas.testutils/index.html +++ /dev/null @@ -1,231 +0,0 @@ - - - - - - - - - - - - Biopandas.testutils - BioPandas - - - - - - - - - - - - - - - - - - - -
-
-
- -

biopandas version: 0.2.5

-

assert_raises

-

assert_raises(exception_type, message, func, args, *kwargs)

-

Check that an exception is raised with a specific message

-

Parameters

-
    -
  • -

    exception_type : exception

    -

    The exception that should be raised

    -
    • -
  • -

    message : str (default: None)

    -

    The error message that should be raised. Ignored if False or None

    -
    • -
  • -

    func : callable

    -

    The function that raises the exception

    -
    • -
  • -

    *args : positional arguments to func

    -
    • -
  • -

    **kwargs : keyword arguments to func

    -
    • -
-
- - - - - - - - - - - - diff --git a/site/citing/index.html b/site/citing/index.html deleted file mode 100644 index b4870e2..0000000 --- a/site/citing/index.html +++ /dev/null @@ -1,234 +0,0 @@ - - - - - - - - - - - - Citing - BioPandas - - - - - - - - - - - - - - - - - - - -
-
-
- -

Citing

-

If you use BioPandas as part of your workflow in a scientific publication, please consider citing the BioPandas repository with the following DOI:

-
    -
  • Sebastian Raschka. Biopandas: Working with molecular structures in pandas dataframes. The Journal of Open Source Software, 2(14), jun 2017. doi: 10.21105/joss.00279. URL http://dx.doi.org/10.21105/joss.00279.
    • -
-
@article{raschkas2017biopandas,
-  doi = {10.21105/joss.00279},
-  url = {http://dx.doi.org/10.21105/joss.00279},
-  year  = {2017},
-  month = {jun},
-  publisher = {The Open Journal},
-  volume = {2},
-  number = {14},
-  author = {Sebastian Raschka},
-  title = {BioPandas: Working with molecular structures in pandas DataFrames},
-  journal = {The Journal of Open Source Software}
-}
-
-
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- - - - - - - - - - - - -

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Logo

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Working with molecular structures in pandas DataFrames

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Continuous Integration -PyPI Version -License -Python 2.7 -Python 3.6 -JOSS -Discuss

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About

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If you are a computational biologist, chances are that you cursed one too many times about protein structure files. Yes, I am talking about ye Goode Olde Protein Data Bank format, aka "PDB files." Nothing against PDB, it's a neatly structured format (if deployed correctly); yet, it is a bit cumbersome to work with PDB files in "modern" programming languages -- I am pretty sure we all agree on this.

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As machine learning and "data science" person, I fell in love with pandas DataFrames for handling just about everything that can be loaded into memory.
-So, why don't we take pandas to the structural biology world? Working with molecular structures of biological macromolecules (from PDB and MOL2 files) in pandas DataFrames is what BioPandas is all about!

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Examples

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3eiy

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# Initialize a new PandasPdb object
-# and fetch the PDB file from rcsb.org
->>> from biopandas.pdb import PandasPdb
->>> ppdb = PandasPdb().fetch_pdb('3eiy')
->>> ppdb.df['ATOM'].head()
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3eiy head

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3eiy head

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# Load structures from your drive and compute the
-# Root Mean Square Deviation
->>> from biopandas.pdb import PandasPdb
->>> pl1 = PandasPdb().read_pdb('./docking_pose_1.pdb')
->>> pl2 = PandasPdb().read_pdb('./docking_pose_2.pdb')
->>> r = PandasPdb.rmsd(pl1.df['HETATM'], pl2.df['HETATM'])
->>> print('RMSD: %.4f Angstrom' % r)
-RMSD: 2.6444 Angstrom
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# Producing quick summary plots
->>> import matplotlib.pyplot as plt
->>> ppdb.df['ATOM']['b_factor'].plot(kind='hist')
->>> plt.title('Distribution of B-Factors')
->>> plt.xlabel('B-factor')
->>> plt.ylabel('count')
->>> plt.show()
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>>> ppdb.df['ATOM']['b_factor'].plot(kind='line')
->>> plt.title('B-Factors Along the Amino Acid Chain')
->>> plt.xlabel('Residue Number')
->>> plt.ylabel('B-factor in $A^2$')
->>> plt.show()
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Cite as

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If you use BioPandas as part of your workflow in a scientific publication, please consider citing the BioPandas repository with the following DOI:

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    -
  • Sebastian Raschka. Biopandas: Working with molecular structures in pandas dataframes. The Journal of Open Source Software, 2(14), jun 2017. doi: 10.21105/joss.00279. URL http://dx.doi.org/10.21105/joss.00279.
    • -
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@article{raschkas2017biopandas,
-  doi = {10.21105/joss.00279},
-  url = {http://dx.doi.org/10.21105/joss.00279},
-  year  = {2017},
-  month = {jun},
-  publisher = {The Open Journal},
-  volume = {2},
-  number = {14},
-  author = {Sebastian Raschka},
-  title = {BioPandas: Working with molecular structures in pandas DataFrames},
-  journal = {The Journal of Open Source Software}
-}
-
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- - - - - - - - - - - - - - diff --git a/site/installation/index.html b/site/installation/index.html deleted file mode 100644 index ea72132..0000000 --- a/site/installation/index.html +++ /dev/null @@ -1,254 +0,0 @@ - - - - - - - - - - - - Installation - BioPandas - - - - - - - - - - - - - - - - - - - -
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Installing BioPandas

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Requirements

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BioPandas requires the following software and packages:

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PyPI

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You can install the latest stable release of biopandas directly from Python's package index via pip by executing the following code from your command line:

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pip install biopandas  
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Conda-forge

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Versions of biopandas are now also available via conda-forge; you can install it via

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conda install biopandas -c conda-forge
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or simply

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conda install biopandas
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if you have conda-forge already added to your channels.

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Latest GitHub Source Code

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You want to try out the latest features before they go live on PyPI? Install the biopandas dev-version latest development version from the GitHub repository by executing

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pip install git+git://github.com/rasbt/biopandas.git
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Alternatively, you download the package manually from PYPI or GitHub, unzip it, navigate into the package, and execute the command:

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python setup.py install
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