Input/Output

Pandas objects are the main data structures used for collections of molecules. scikit-chem provides convenience functions to load objects into pandas.DataFrames from common file formats in cheminformatics.

Reading files

The scikit-chem functionality is modelled after the pandas API. To load an csv file using pandas you would call:



In [1]:

    
df = pd.read_csv('https://archive.org/download/scikit-chem_example_files/iris.csv', 
                 header=None); df









    Out[1]:






  
    
      
      0
      1
      2
      3
      4
    
  
  
    
      0
      5.1
      3.5
      1.4
      0.2
      Iris-setosa
    
    
      1
      4.9
      3.0
      1.4
      0.2
      Iris-setosa
    
    
      2
      4.7
      3.2
      1.3
      0.2
      Iris-setosa
    
    
      3
      4.6
      3.1
      1.5
      0.2
      Iris-setosa
    
    
      4
      5.0
      3.6
      1.4
      0.2
      Iris-setosa

Analogously with scikit-chem:



In [2]:

    
smi = skchem.read_smiles('https://archive.org/download/scikit-chem_example_files/example.smi')

Currently available:



In [3]:

    
[method for method in skchem.io.__dict__ if method.startswith('read_')]









    Out[3]:





['read_sdf', 'read_smiles']

scikit-chem also adds convenience methods onto pandas.DataFrame objects.



In [4]:

    
pd.DataFrame.from_smiles('https://archive.org/download/scikit-chem_example_files/example.smi')









    Out[4]:






  
    
      
      structure
      1
    
  
  
    
      0
      <Mol: CC>
      ethane
    
    
      1
      <Mol: CCC>
      propane
    
    
      2
      <Mol: c1ccccc1>
      benzene
    
    
      3
      <Mol: CC(=O)[O-].[Na+]>
      sodium acetate
    
    
      4
      <Mol: NC(CO)C(=O)O>
      serine

Writing files

Again, this is analogous to pandas:



In [5]:

    
from io import StringIO
sio = StringIO()
df.to_csv(sio)
sio.seek(0)
print(sio.read())









    



,0,1,2,3,4
0,5.1,3.5,1.4,0.2,Iris-setosa
1,4.9,3.0,1.4,0.2,Iris-setosa
2,4.7,3.2,1.3,0.2,Iris-setosa
3,4.6,3.1,1.5,0.2,Iris-setosa
4,5.0,3.6,1.4,0.2,Iris-setosa



In [6]:

    
sio = StringIO()
smi.iloc[:2].to_sdf(sio) # don't write too many!
sio.seek(0)
print(sio.read())









    



0
     RDKit          

  2  1  0  0  0  0  0  0  0  0999 V2000
    0.0000    0.0000    0.0000 C   0  0  0  0  0  0  0  0  0  0  0  0
    0.0000    0.0000    0.0000 C   0  0  0  0  0  0  0  0  0  0  0  0
  1  2  1  0
M  END
>  <1>  (1) 
ethane

$$$$
1
     RDKit          

  3  2  0  0  0  0  0  0  0  0999 V2000
    0.0000    0.0000    0.0000 C   0  0  0  0  0  0  0  0  0  0  0  0
    0.0000    0.0000    0.0000 C   0  0  0  0  0  0  0  0  0  0  0  0
    0.0000    0.0000    0.0000 C   0  0  0  0  0  0  0  0  0  0  0  0
  1  2  1  0
  2  3  1  0
M  END
>  <1>  (2) 
propane

$$$$

	0	1	2	3	4
0	5.1	3.5	1.4	0.2	Iris-setosa
1	4.9	3.0	1.4	0.2	Iris-setosa
2	4.7	3.2	1.3	0.2	Iris-setosa
3	4.6	3.1	1.5	0.2	Iris-setosa
4	5.0	3.6	1.4	0.2	Iris-setosa

	structure	1
0	<Mol: CC>	ethane
1	<Mol: CCC>	propane
2	<Mol: c1ccccc1>	benzene
3	<Mol: CC(=O)[O-].[Na+]>	sodium acetate
4	<Mol: NC(CO)C(=O)O>	serine