I am trying to collect the ALL information (electronic, mechanical, physical etc) about Li_3P from the MP data base. For this I have tried using:
from pymatgen import MPRester
m = MPRester("***")
data =m.get_data(“Li3P”)
However, I could not find data about # of atoms per unit cell, volume per unit cell, # of atoms in a particular radius of say 4A, # anions in a unit cell, electronegativity information etc.
Is there a way to collect all relevant information about the same using a single query?
Currently there is no one query that will give you all the information you want. That query provides what we feel are materials properties. You can extract more information from that data set, for instance the number of atoms per unit cell, volume per unit cell can both be extracted by converting the structure sub-dictionary into a pymatgen structure object. From that you can query pymatgen’s internal dataset of atomic properties to get more information there and arrange the resulting data in your own format.
It sounds like you might be trying do some data extraction, for which you might look at the matminer package on github.
There is also a discussion of this on the pymatgen thread with a few more instructions:
“The only way I know to do this would be to list out every root key in the MAPIdoc (https://github.com/materialsproject/mapidoc/tree/master/materials) in the properties key - either manually or by writing some script to extract all the root properties from the MAPIdoc repo.”
I would actually vote that there be a way to easily get all data, especially for a single materials id (maybe excluding very large data like bandstructure and DOS for which the user might need to issue a separate query or add some flags). I can see the usefulness of trying to be complete in data extraction up front and then deciding later what information to leverage for various studies. But it is really up to MP if they want to support this.
You would have to calculate this yourself, since we can’t report all possible variants of this question. Pymatgen’s Structure.get_sites_in_sphere() method might be able to help you.