Package rdkit :: Package Chem :: Module PandasTools

[hide private]
[frames] | no frames]

# Module PandasTools

source code

    Importing pandasTools enables several features that allow for using RDKit molecules as columns of a Pandas dataframe.
    If the dataframe is containing a molecule format in a column (e.g. smiles), like in this example:
    >>> from rdkit.Chem import PandasTools
    >>> import pandas as pd
    >>> import os
    >>> from rdkit import RDConfig
    >>> antibiotics = pd.DataFrame(columns=['Name','Smiles'])
    >>> antibiotics = antibiotics.append({'Smiles':'CC1(C(N2C(S1)C(C2=O)NC(=O)CC3=CC=CC=C3)C(=O)O)C','Name':'Penicilline G'}, ignore_index=True)#Penicilline G
    >>> antibiotics = antibiotics.append({'Smiles':'CC1(C2CC3C(C(=O)C(=C(C3(C(=O)C2=C(C4=C1C=CC=C4O)O)O)O)C(=O)N)N(C)C)O','Name':'Tetracycline'}, ignore_index=True)#Tetracycline
    >>> antibiotics = antibiotics.append({'Smiles':'CC1(C(N2C(S1)C(C2=O)NC(=O)C(C3=CC=CC=C3)N)C(=O)O)C','Name':'Ampicilline'}, ignore_index=True)#Ampicilline
    >>> print([str(x) for x in  antibiotics.columns])
    ['Name', 'Smiles']
    >>> print(antibiotics)
                Name                                             Smiles
    0  Penicilline G    CC1(C(N2C(S1)C(C2=O)NC(=O)CC3=CC=CC=C3)C(=O)O)C
    1   Tetracycline  CC1(C2CC3C(C(=O)C(=C(C3(C(=O)C2=C(C4=C1C=CC=C4...
    2  Ampicilline  CC1(C(N2C(S1)C(C2=O)NC(=O)C(C3=CC=CC=C3)N)C(=O...

    a new column can be created holding the respective RDKit molecule objects. The fingerprint can be included to accelerate substructure searches on the dataframe.

    >>> PandasTools.AddMoleculeColumnToFrame(antibiotics,'Smiles','Molecule',includeFingerprints=True)
    >>> print([str(x) for x in  antibiotics.columns])
    ['Name', 'Smiles', 'Molecule']

    A substructure filter can be applied on the dataframe using the RDKit molecule column, because the ">=" operator has been modified to work as a substructure check.
    Such the antibiotics containing the beta-lactam ring "C1C(=O)NC1" can be obtained by

    >>> beta_lactam = Chem.MolFromSmiles('C1C(=O)NC1')
    >>> beta_lactam_antibiotics = antibiotics[antibiotics['Molecule'] >= beta_lactam]
    >>> print(beta_lactam_antibiotics[['Name','Smiles']])
                Name                                             Smiles
    0  Penicilline G    CC1(C(N2C(S1)C(C2=O)NC(=O)CC3=CC=CC=C3)C(=O)O)C
    2  Ampicilline  CC1(C(N2C(S1)C(C2=O)NC(=O)C(C3=CC=CC=C3)N)C(=O...

    It is also possible to load an SDF file can be load into a dataframe.

    >>> sdfFile = os.path.join(RDConfig.RDDataDir,'NCI/first_200.props.sdf')
    >>> frame = PandasTools.LoadSDF(sdfFile,smilesName='SMILES',molColName='Molecule',includeFingerprints=True)
    >>> frame.info # doctest: +SKIP
    <bound method DataFrame.info of <class 'pandas.core.frame.DataFrame'>
    Int64Index: 200 entries, 0 to 199
    Data columns:
    AMW                       200  non-null values
    CLOGP                     200  non-null values
    CP                        200  non-null values
    CR                        200  non-null values
    DAYLIGHT.FPG              200  non-null values
    DAYLIGHT_CLOGP            200  non-null values
    FP                        200  non-null values
    ID                        200  non-null values
    ISM                       200  non-null values
    LIPINSKI_VIOLATIONS       200  non-null values
    NUM_HACCEPTORS            200  non-null values
    NUM_HDONORS               200  non-null values
    NUM_HETEROATOMS           200  non-null values
    NUM_LIPINSKIHACCEPTORS    200  non-null values
    NUM_LIPINSKIHDONORS       200  non-null values
    NUM_RINGS                 200  non-null values
    NUM_ROTATABLEBONDS        200  non-null values
    P1                        30  non-null values
    SMILES                    200  non-null values
    Molecule                  200  non-null values
    dtypes: object(20)>

    In order to support rendering the molecules as images in the HTML export of the dataframe, the __str__ method is monkey-patched to return a base64 encoded PNG:
    >>> molX = Chem.MolFromSmiles('Fc1cNc2ccccc12')
    >>> print(molX) # doctest: +SKIP
    <img src="data:image/png;base64,..." alt="Mol"/>
    This can be reverted using the ChangeMoleculeRendering method
    >>> ChangeMoleculeRendering(renderer='String')
    >>> print(molX) # doctest: +SKIP
    <rdkit.Chem.rdchem.Mol object at 0x10d179440>
    >>> ChangeMoleculeRendering(renderer='PNG')
    >>> print(molX) # doctest: +SKIP
    <img src="data:image/png;base64,..." alt="Mol"/>

Functions | [hide private]

patchPandasHTMLrepr(self, **kwargs) Patched default escaping of HTML control characters to allow molecule image rendering dataframes | source code

patchPandasHeadMethod(self, n=5) Ensure inheritance of patched to_html in "head" subframe... | source code

_get_image(x) displayhook function for PIL Images, rendered as PNG | source code

_molge(x, y) Allows for substructure check using the >= operator (X has substructure Y -> X >= Y) by... | source code

PrintAsBase64PNGString(x, renderer=None) returns the molecules as base64 encoded PNG image... | source code

PrintDefaultMolRep(x) | source code

_MolPlusFingerprint(m) Precomputes fingerprints and stores results in molecule objects to accelerate substructure matching... | source code

RenderImagesInAllDataFrames(images=True) Changes the default dataframe rendering to not escape HTML characters, thus allowing rendered images in all dataframes. | source code

AddMoleculeColumnToFrame(frame, smilesCol='Smiles', molCol='ROMol', includeFingerprints=False) Converts the molecules contains in "smilesCol" to RDKit molecules and appends them to the dataframe "frame" using the specified column name. | source code

ChangeMoleculeRendering(frame=None, renderer='PNG') Allows to change the rendering of the molecules between base64 PNG images and string representations. | source code

LoadSDF(filename, idName='ID', molColName='ROMol', includeFingerprints=False, isomericSmiles=False, smilesName=None) Read file in SDF format and return as Pandas data frame | source code

WriteSDF(df, out, molColumn, properties=None, allNumeric=False, titleColumn=None) Write an SD file for the molecules in the dataframe. | source code

RemoveSaltsFromFrame(frame, molCol='ROMol') Removes salts from mols in pandas DataFrame's ROMol column | source code

SaveSMILESFromFrame(frame, outFile, molCol='ROMol', NamesCol='', isomericSmiles=False) Saves smi file. | source code

SaveXlsxFromFrame(frame, outFile, molCol='ROMol', size=(300,300)) Saves pandas DataFrame as a xlsx file with embedded images. | source code

FrameToGridImage(frame, column='ROMol', legendsCol=None, **kwargs) Draw grid image of mols in pandas DataFrame. | source code

AddMurckoToFrame(frame, molCol='ROMol', MurckoCol='Murcko_SMILES', Generic=False) Adds column with SMILES of Murcko scaffolds to pandas DataFrame. | source code

AlignMol(mol, scaffold) Aligns mol (RDKit mol object) to scaffold (SMILES string) | source code

AlignToScaffold(frame, molCol='ROMol', scaffoldCol='Murcko_SMILES') Aligns molecules in molCol to scaffolds in scaffoldCol | source code

Variables | [hide private]

| v = `pd.version.version.split('.')`
| defPandasRendering = `pd.core.frame.DataFrame.to_html`
| pd = `None` hash(x)
| highlightSubstructures = `True`
| _fingerprinter = `lambda x, y:`
| remover = `SaltRemover.SaltRemover()`

Imports: b64encode, types, copy, BytesIO, Chem, Draw, DataStructs, pyAvalonTools, SDWriter, SaltRemover, np, os, StringIO, MurckoScaffold, AllChem

Function Details | [hide private]

### patchPandasHeadMethod(self, n=5)

source code

    Ensure inheritance of patched to_html in "head" subframe

### _molge(x, y)

source code

    Allows for substructure check using the >= operator (X has substructure Y -> X >= Y) by
    monkey-patching the __ge__ function
    This has the effect that the pandas/numpy rowfilter can be used for substructure filtering (filtered = dframe[dframe['RDKitColumn'] >= SubstructureMolecule])

### PrintAsBase64PNGString(x, renderer=None)

source code

    returns the molecules as base64 encoded PNG image

### _MolPlusFingerprint(m)

source code

    Precomputes fingerprints and stores results in molecule objects to accelerate substructure matching

### RenderImagesInAllDataFrames(images=True)

source code

    Changes the default dataframe rendering to not escape HTML characters, thus allowing rendered images in all dataframes.
    IMPORTANT: THIS IS A GLOBAL CHANGE THAT WILL AFFECT TO COMPLETE PYTHON SESSION. If you want to change the rendering only
    for a single dataframe use the "ChangeMoleculeRendering" method instead.

### AddMoleculeColumnToFrame(frame, smilesCol='Smiles', molCol='ROMol', includeFingerprints=False)

source code

    Converts the molecules contains in "smilesCol" to RDKit molecules and appends them to the dataframe "frame" using the specified column name.
    If desired, a fingerprint can be computed and stored with the molecule objects to accelerate substructure matching

### ChangeMoleculeRendering(frame=None, renderer='PNG')

source code

    Allows to change the rendering of the molecules between base64 PNG images and string representations.
    This serves two purposes: First it allows to avoid the generation of images if this is not desired and, secondly, it allows to enable image rendering for
    newly created dataframe that already contains molecules, without having to rerun the time-consuming AddMoleculeColumnToFrame. Note: this behaviour is, because some pandas methods, e.g. head()
    returns a new dataframe instance that uses the default pandas rendering (thus not drawing images for molecules) instead of the monkey-patched one.

### WriteSDF(df, out, molColumn, properties=None, allNumeric=False, titleColumn=None)

source code

    Write an SD file for the molecules in the dataframe. Dataframe columns can be exported as SDF tags if specific in the "properties" list.
    The "allNumeric" flag allows to automatically include all numeric columns in the output.
    "titleColumn" can be used to select a column to serve as molecule title. It can be set to "RowID" to use the dataframe row key as title.

### SaveSMILESFromFrame(frame, outFile, molCol='ROMol', NamesCol='', isomericSmiles=False)

source code

    Saves smi file. SMILES are generated from column with RDKit molecules. Column with names is optional.

### SaveXlsxFromFrame(frame, outFile, molCol='ROMol', size=(300,300))

source code

    Saves pandas DataFrame as a xlsx file with embedded images.
    It maps numpy data types to excel cell types:
    int, float -> number
    datetime -> datetime
    object -> string (limited to 32k character - xlsx limitations)

    Cells with compound images are a bit larger than images due to excel.
    Column width weirdness explained (from xlsxwriter docs):
    The width corresponds to the column width value that is specified in Excel.
    It is approximately equal to the length of a string in the default font of Calibri 11.
    Unfortunately, there is no way to specify "AutoFit" for a column in the Excel file format.
    This feature is only available at runtime from within Excel.

### AddMurckoToFrame(frame, molCol='ROMol', MurckoCol='Murcko_SMILES', Generic=False)

source code

    Adds column with SMILES of Murcko scaffolds to pandas DataFrame. Generic set to true results in SMILES of generic framework.