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Diego Ripley f93e4d0cec Initial commit
2025-05-24 13:37:31 -04:00

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3.5 KiB
Python
Executable File

#!/usr/bin/env python
# coding: utf-8
import os
import sys
import numpy as np
import pandas as pd
from sqlalchemy import create_engine
filename = sys.argv[1]
DATABASE = os.environ.get("POSTGRES_DB")
USER = os.environ.get("POSTGRES_USER")
PASSWORD = os.environ.get("POSTGRES_PASSWORD")
engine = create_engine(f"postgresql://{USER}:{PASSWORD}@db:5432/{DATABASE}")
"""
Data dictionary is here:
https://web.archive.org/web/20240918110218/https://www150.statcan.gc.ca/n1/pub/92-151-g/2021001/tbl/tbl4_1-eng.htm
This processes the entire DGUID hierarchy and other useful fields
"""
print(f"Processing {filename}")
params = {
'filepath_or_buffer': filename,
'encoding': 'latin-1',
'usecols': ['PRDGUID_PRIDUGD', 'CDDGUID_DRIDUGD',
'FEDDGUID_CEFIDUGD', 'CSDDGUID_SDRIDUGD',
'DPLDGUID_LDIDUGD', 'ERDGUID_REIDUGD',
'CCSDGUID_SRUIDUGD', 'SACTYPE_CSSGENRE', 'SACCODE_CSSCODE', 'CMAPDGUID_RMRPIDUGD', 'CMADGUID_RMRIDUGD',
'CMATYPE_RMRGENRE', 'CTDGUID_SRIDUGD', 'POPCTRRAPDGUID_CTRPOPRRPIDUGD', 'POPCTRRADGUID_CTRPOPRRIDUGD',
'DADGUID_ADIDUGD', 'DBDGUID_IDIDUGD',
# 2021 Block population, private dwellings, usual residents
'DBPOP2021_IDPOP2021', 'DBTDWELL2021_IDTLOG2021', 'DBURDWELL2021_IDRHLOG2021',
# 2021 Census Indian reserve refusal flag
'DBIR2021_IDRI2021',
'ADADGUID_ADAIDUGD'
],
# Apparently they have to be int64 because there's NA values
'dtype': {
'DBPOP2021_IDPOP2021': "Int64",
'DBTDWELL2021_IDTLOG2021': "Int64",
'DBURDWELL2021_IDRHLOG2021': "Int64"
}
}
gaf_2021_df = pd.read_csv(**params)
# Rename columns, replace french portion
gaf_2021_df.rename(columns={
'PRDGUID_PRIDUGD': 'pr_dguid',
'CDDGUID_DRIDUGD': 'cd_dguid',
'FEDDGUID_CEFIDUGD': 'fed_dguid',
'CSDDGUID_SDRIDUGD': 'csd_dguid',
'DPLDGUID_LDIDUGD': 'dpl_dguid',
'ERDGUID_REIDUGD': 'er_dguid',
'CCSDGUID_SRUIDUGD': 'ccs_dguid',
'SACTYPE_CSSGENRE': 'sac_type',
'SACCODE_CSSCODE': 'sac_code',
'CMAPDGUID_RMRPIDUGD': 'cma_p_dguid',
'CMADGUID_RMRIDUGD': 'cma_dguid',
'CTDGUID_SRIDUGD': 'ct_dguid',
'POPCTRRAPDGUID_CTRPOPRRPIDUGD': 'pop_ctr_p_dguid',
'POPCTRRADGUID_CTRPOPRRIDUGD': 'pop_ctr_dguid',
'DADGUID_ADIDUGD': 'da_dguid',
'DBDGUID_IDIDUGD': 'db_dguid',
'DBPOP2021_IDPOP2021': 'db_pop_2021',
# This one needs work
'DBTDWELL2021_IDTLOG2021': 'db_total_private_dwell_2021',
# I don't particularly like this one
'DBURDWELL2021_IDRHLOG2021': 'db_usual_residents_dwellings_2021',
'DBIR2021_IDRI2021': 'db_ir_2021',
'ADADGUID_ADAIDUGD': 'ada_dguid'
}, inplace=True)
columns_ordered = ['pr_dguid', 'fed_dguid', 'er_dguid', 'cd_dguid',
'dpl_dguid', 'ccs_dguid', 'csd_dguid', 'sac_type', 'sac_code',
'cma_p_dguid', 'cma_dguid',
'pop_ctr_p_dguid', 'pop_ctr_dguid',
'ada_dguid', 'ct_dguid', 'da_dguid', 'db_dguid',
'db_pop_2021', 'db_total_private_dwell_2021', 'db_usual_residents_dwellings_2021', 'db_ir_2021']
gaf_2021_df = gaf_2021_df.reindex(columns_ordered, axis=1)
print("Loading 2021 geographic attribute file to PostgreSQL as gaf_2021")
gaf_2021_df.to_sql(name='gaf_2021',
con=engine,
index=False,
chunksize=50000,
if_exists='replace',
schema='silver'
)