data.py

import pandas as pd
import geopandas as gpd

sdg_data = pd.read_csv(
    "https://raw.githubusercontent.com/francheska-vicente/datapre-project/main_v2/data_output/combined_data.csv"
)
sdg_columns = sdg_data.columns[:-15]
population_df = sdg_data [['Geolocation', 'Year', 'Population']]
sdg_data = sdg_data[sdg_columns]

sdg_score = pd.read_csv("data/sdg_target_score.csv")
sdg_info = pd.read_csv("data/sdg_infov3.csv")
region_info = pd.read_csv("data/region_infov1.csv")

sdg_regions_available = sdg_data["Geolocation"].unique()[1:]
sdg_indicators_available = sdg_data.columns[2:]

goals_name = sdg_info["Main SDG"].unique()

region = gpd.read_file('./data/gadm_regions_updated.geojson').set_index('Geolocation')
region_area = pd.read_csv('./data/region_area.csv')

gdf_shp = gpd.read_file('data/geospatial_data/regional/regional_data.shp')
regional = gpd.read_file('data/geospatial_data/regional/regional_data.geojson').set_index('Geolocation')

for i in range(len(sdg_data.columns)):
    name_map = {gdf_shp.columns[i] : sdg_data.columns[i]}
    gdf_shp.rename(columns=name_map, inplace=True)