Catastral/Ownership data about climathon-fiit-re HOT 4 OPEN

Aggregations per Bratislava district

roep_vkm_vmuo.csv

from climathon-fiit-re.

DB with columns

from climathon-fiit-re.

Create database (I made postgresql with 5555 port and default credentials - in code)

`
import pandas as pd
import sqlalchemy
from sqlalchemy.orm import declarative_base, sessionmaker

engine = sqlalchemy.create_engine("postgresql://postgres:postgres@localhost:5555/postgres")

Session = sessionmaker(bind=engine)
session = Session()
Base = declarative_base()

def fill_database() -> None:
cadastral_area = pd.read_csv("data/cadastral_area.csv", skiprows=1, encoding='Windows-1250 ', on_bad_lines='skip', delimiter=";")
cadastral_area = cadastral_area.loc[:, 'okres':'názov']
cadastral_area.columns = ['id_okres', 'skratka_okresu', 'kod', 'vymera', 'nazov_obce', 'kod_katastra', 'vymera_drop', 'nazov']
cadastral_area['skratka_okresu'] = cadastral_area.groupby('id_okres')['skratka_okresu'].transform(
lambda x: x.ffill().bfill())
cadastral_area = cadastral_area.drop(columns=['vymera_drop'])
cadastral_area.to_sql('cadastral_area', engine, if_exists='replace', index=False)

cadastral_metadata = pd.read_csv("data/cadastral_metadata.csv", encoding='Windows-1250 ', on_bad_lines='skip', delimiter=";")
replaced_columns = ['datum_aktualizacie_objectu', 'autor', 'horizontalna_presnost', 'aktualny_stav_objektu',
                    'kod_katastralneho_uzemia', 'nazov_katastralneho_uzemia', 'cislo_obce', 'nazov_obce',
                    'cislo_okresu', 'nazov_okresu', 'cislo_kraja', 'nazov_kraja', 'vymera', 'NUTS1', 'NUTS1_CODE',
                    'NUTS2', 'NUTS2_CODE', 'NUTS3', 'NUTS3_CODE', 'LAU1', 'LAU1_CODE', 'LAU2', 'LAU2_CODE']
cadastral_metadata.columns = replaced_columns
cadastral_metadata.to_sql('cadastral_metadata', engine, if_exists='replace', index=False)

if name=="main":
fill_database()

`

from climathon-fiit-re.

Data

cadastral_metadata.csv
cadastral_area.csv

Directory tree:
src/fill_database.py
data/*.csv

from climathon-fiit-re.