<jupyter_start><jupyter_text>Mapping the Sea Level change to the elevation and VLMAE=E−SL+VLM<jupyter_code>from datetime import datetime
df_SLR.columns
today = datetime.today()
current_year =  today.year 
current_year
df_final = df_elevation.copy(deep=True)
df_SLR
dates = [2030, 2050, 2080, 2100]
scenario = ['0.3 - LOW']
for i in dates:
    df_final['AdjustedElevation_'+ str(i)] = df_final['Elevation'] + df_final['VLM'] - df_SLR['RSL in '+ str(i) +' (cm)'].loc[scenario[0]]
df_final 
import matplotlib.pyplot as plt
cm = plt.cm.get_cmap('RdYlBu')

x = df_final['Longitude'].values
y = df_final['Latitude'].values
z = df_final['AdjustedElevation_2030'].values
# sc = plt.scatter(x, y, c=z, vmin=min(z), vmax=max(z), cmap=cm)
sc = plt.scatter(x, y, c=z, vmin=min(z), vmax=max(z))
plt.colorbar(sc)
plt.show()
cm = plt.cm.get_cmap('RdYlBu')

x = df_final['Longitude'].values
y = df_final['Latitude'].values
z = df_final['AdjustedElevation_2050'].values
# sc = plt.scatter(x, y, c=z, vmin=min(z), vmax=max(z), cmap=cm)
sc = plt.scatter(x, y, c=z, vmin=min(z), vmax=max(z))
plt.colorbar(sc)
plt.show()
cm = plt.cm.get_cmap('RdYlBu')

x = df_final['Longitude'].values
y = df_final['Latitude'].values
z = df_final['AdjustedElevation_2080'].values
# sc = plt.scatter(x, y, c=z, vmin=min(z), vmax=max(z), cmap=cm)
sc = plt.scatter(x, y, c=z, vmin=min(z), vmax=max(z))
plt.colorbar(sc)
plt.show()
for i in dates:
    sns.lmplot(x='Longitude', y='Latitude', data = df_final, hue='AdjustedElevation_'+str(i),legend =False, fit_reg=False ).fig.suptitle("Graph (AdjustedElevation_"+str(i))<jupyter_output><empty_output>
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