I have the following code:
import plotly.express as px
import pandas as pd
import numpy as np
import io
df = wb.data.DataFrame('FP.CPI.TOTL.ZG')
df1 = df['YR2021']
df1 = df1.dropna()
df1 = pd.Series(df1,name="counts")
df1 = df1.reset_index()
fig = px.choropleth(df1, locations="economy",
locationmode='ISO-3',
color="counts",
title="Global Inflation Rate 2021",
hover_name="economy",
scope ='asia',
color_continuous_scale=px.colors.sequential.Reds)
fig.update_layout(title_text='Global Inflation Rate 2021', title_x=0.5)
fig.show()
It produces the following plot:

The problem I am facing is that the color are not deep enough for visual distinction since the data which I am using is global data. Is there anyway I can deepen the color contract so visually it is apparent in the Asia context or any other scope? Or could you advise how can I remove all Non-Asian country without marking each off one by one; since it wound be very time consuming especially when other continents to specify each country.
