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Data/__init__.py

@@ -1,5 +1,10 @@
-import pandas as pd
+import geopandas as gpd
+import numpy as np
 import os
+import pandas as pd
+import xarray as xr
+
+from Plots.colors import colors
 
 # We make relevant datasets contained in this folder available across the project, for easier integration and plotting.
 # The base directory points to the folder containing this file:
@@ -14,7 +19,6 @@ countries_by_region['Middle East'] = countries_by_region.pop('Western Asia')
 countries_by_region['South Asia'] = countries_by_region.pop('Southern Asia')
 
 # Make the world shapefile available for plotting
-import geopandas as gpd
 world = gpd.read_file(os.path.join(base_dir, "world_shapefile/ne_50m_admin_0_countries.shp"))
 world.to_crs("EPSG:3857", inplace=True) # Mercator projection by default
 
@@ -24,8 +28,6 @@ coordinates = dict((k, (coordinates['Latitude'][k], coordinates['Longitude'][k])
 
 # Load the various comparison datasets into a dictionary for easy plotting, assigning consistent colours
 # and markers for each.
-from Plots.colors import colors
-import xarray as xr
 flow_dsets = {
     "Quantmig": dict(
         data=xr.open_dataset(os.path.join(base_dir, "Flow_data/QuantMig_data/Quantmig_flows.nc")),
@@ -58,7 +60,6 @@ NatStat_net_migration = xr.open_dataarray(os.path.join(base_dir, "Net_migration/
 WPP_data = xr.open_dataset(os.path.join(base_dir, "UN_WPP_data/UN_WPP_data.nc"))
 
 # Calculate the fraction of population alive at start of 1990 in each destination country still alive at start of year
-import numpy as np
 gamma = (1-death_rate.sel({"Year": range(1989, 2024)})).assign_coords({"Year": np.arange(1990, 2025, 1)}).rename({
     "Country ISO": "Destination ISO"})
 gamma.loc[{"Year": 1990}] = 1.0