kripso / climathon-fiit-re

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Catastral/Ownership data #1

Open kripso opened 11 months ago

kripso commented 11 months ago

https://geoportal.bratislava.sk/pfa/apps/webappviewer/index.html?id=aa99305d298242a0a8396bbde599a347

on average:

martinkatkovcin commented 11 months ago

Aggregations per Bratislava district

Image

roep_vkm_vmuo.csv

martinkatkovcin commented 11 months ago

DB with columns

Image

martinkatkovcin commented 11 months ago

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()

`

martinkatkovcin commented 11 months ago

Data

cadastral_metadata.csv cadastral_area.csv

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