1. Introduction The term “code postal” (French for postal code ) denotes the series of digits (and sometimes letters) that identify a specific geographic area for the purpose of sorting and delivering mail. While the concept is universal, each country has developed its own conventions, lengths, and hierarchical structures.
df = pd.read_csv('postal_codes.csv', dtype=str) # keep leading zeros print(df.head()) print(df['postal_code'].nunique(), "unique postal codes") If GIS data is present ( postal_codes.geojson ):
-- Update changed rows UPDATE postal_codes p SET city = s.city, lat = s.lat, lng = s.lng FROM postal_codes_stg s WHERE p.code = s.code AND (p.city <> s.city OR p.lat <> s.lat OR p.lng <> s.lng); Code postal new folder 582.rar
-- Delete obsolete codes DELETE FROM postal_codes p USING postal_codes_stg s WHERE p.code = s.code AND s.is_active = FALSE; -- assuming a flag in the new file
# Install unrar if not present sudo apt-get install unrar # Debian/Ubuntu brew install unrar # macOS (Homebrew) df = pd
-- Insert new codes INSERT INTO postal_codes (code, city, lat, lng) SELECT s.code, s.city, s.lat, s.lng FROM postal_codes_stg s LEFT JOIN postal_codes p ON p.code = s.code WHERE p.code IS NULL;
# Extract unrar x 582.rar # preserves full paths # or unrar e 582.rar # extracts all files into the current directory A folder (often named 582 or the name encoded inside the archive) containing the files listed above. 4.3 Quick Data Exploration Assuming the primary file is postal_codes.csv : import geopandas as gpd import pandas as pd
In many digital‑mailing or logistics projects, data sets of postal codes are exchanged as compressed archives (ZIP, RAR, 7z, etc.). One such file that you may encounter is – a RAR archive that often contains a collection of postal‑code‑related resources (e.g., CSV tables, GIS shapefiles, documentation, or scripts).
import geopandas as gpd
import pandas as pd