text: # -*- coding: utf-8 -*-
  # import sys
  import matplotlib.pyplot as plt
  from utils.base import save_fig
  from global_variable import MAP_IMAGE_PATH
  import logging
  import geopandas
  from mpl_toolkits.axes_grid1 import make_axes_locatable
  
  # sys.path.append("..")
  logging.captureWarnings(True)
  
  
  def map_projected(col, df):
      """
  
      :param col: pd.Series, one selected column from the data sheet
      :param df: pd.DataFrame, the data sheet
      """
      # Create point geometries
      geometry = geopandas.points_from_xy(df['LONGITUDE'], df['LATITUDE'])
      geo_df = geopandas.GeoDataFrame(df[[col.name, 'LONGITUDE', 'LATITUDE']], geometry=geometry)
      world = geopandas.read_file(geopandas.datasets.get_path('naturalearth_lowres'))
  
      # Make figure
      fig, ax = plt.subplots(figsize=(24, 18))
      divider = make_axes_locatable(ax)
      cax = divider.append_axes("right", size="5%", pad=0.1)
      world.plot(ax=ax, alpha=0.4, color='grey', edgecolor='black')
      geo_df.plot(col.name, ax=ax, s=20, cmap='gist_heat_r', cax=cax, legend=True)
      plt.title('colorbar')
      save_fig(f"map projection - {col.name}", MAP_IMAGE_PATH)
  