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# `lenu - Legal Entity Name Understanding` by GLEIF and Sociovestix Labs
# Written in 2022 by Sociovestix Labs
# To the extent possible under law, the author(s) have dedicated all copyright
# and related and neighboring rights to this software to the public domain
# worldwide. This software is distributed without any warranty.
#
# You should have received a copy of the CC0 Public Domain Dedication along
# with this software.
# If not, see <http://creativecommons.org/publicdomain/zero/1.0/>.
"""This helper script creates the classnames variable for lenu.py"""
from lenu import URL
import pandas
relevant_cols = [
"LEI",
"Entity.LegalName",
"Entity.LegalForm.EntityLegalFormCode",
"Entity.LegalJurisdiction",
"Entity.EntityCategory",
"Entity.EntityStatus",
"Registration.RegistrationStatus",
]
COL_LEI, COL_NAME, COL_ELF, COL_JUR, COL_CAT, COL_ESTATUS, COL_RSTATUS = relevant_cols
if __name__ == "__main__":
d = pandas.read_csv(
URL,
compression="zip",
low_memory=True,
dtype=str,
# the following will prevent pandas from converting words like 'NA' to NaN. We want to work with the LEI data as is.
na_values=[""],
keep_default_na=False,
usecols=relevant_cols,
)
d_issued = d[(d[COL_ESTATUS] == "ACTIVE") & (d[COL_RSTATUS] == "ISSUED")]
classnames = {
jur: classes
for jur, classes in d_issued.groupby(COL_JUR)[COL_ELF]
.unique()
.apply(list)
.to_dict()
.items()
if jur
in [
"AT",
"AU",
"CH",
"CN",
"CZ",
"DE",
"DK",
"EE",
"ES",
"FI",
"GB",
"HU",
"IE",
"JP",
"KY",
"LU",
"NL",
"NO",
"PL",
"SE",
"US-CA",
"US-DE",
"US-NY",
"VG",
"LI",
"ZA",
] # not CA, BE, FR, BG
}
print("Please copy the following snippet into lenu.py:")
print("")
print("classnames = ", classnames)
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