create database for visualisation pipeline

visualisation_pipeline/EDGAR_fossil_CO2_1970-2023.py

@@ -0,0 +1,16 @@
+from sqlmodel import SQLModel, Field, create_engine, Session
+import pandas as pd
+
+DB_URL = "postgresql://u4axloluqibskgvdikuy:g2rXgpHSbztokCbFxSyR@bk8htvifqendwt1wlzat-postgresql.services.clever-cloud.com:7327/bk8htvifqendwt1wlzat"
+
+engine = create_engine(DB_URL)
+SQLModel.metadata.create_all(engine)
+
+file = pd.read_csv("visualisation_pipeline/data/EDGAR_fossil_CO2_1970-2023.csv", delimiter=';')
+file.drop(columns=["Substance", "EDGAR Country Code"], inplace=True)
+file_t = file.set_index('Country')
+file_t = file_t.transpose().reset_index().rename(columns={'index': 'year'})
+file_t.columns.name = None
+file_t.index.name = None
+file_t.dropna(how='all', axis=1, inplace=True)
+file_t.to_sql(name="EDGAR_fossil_CO2_1970-2023", con=engine, if_exists="replace", index=False)

visualisation_pipeline/EDGAR_fossil_CO2_1970-2023_melted.py

@@ -0,0 +1,13 @@
+from sqlmodel import SQLModel, Field, create_engine, Session
+import pandas as pd
+
+DB_URL = "postgresql://u4axloluqibskgvdikuy:g2rXgpHSbztokCbFxSyR@bk8htvifqendwt1wlzat-postgresql.services.clever-cloud.com:7327/bk8htvifqendwt1wlzat"
+
+engine = create_engine(DB_URL)
+SQLModel.metadata.create_all(engine)
+
+file = pd.read_csv("visualisation_pipeline/data/EDGAR_fossil_CO2_1970-2023.csv", delimiter=';')
+file.drop(columns=["Substance", "EDGAR Country Code"], inplace=True)
+file_t = pd.melt(file, id_vars=["Country"], var_name="Year", value_name="CO2 Emissions")
+file_t.dropna(how='all', axis=1, inplace=True)
+file_t.to_sql(name="EDGAR_fossil_CO2_1970-2023_melted", con=engine, if_exists="replace", index=False)