1084_159_242.py

# -*- coding: utf-8 -*-
"""1084.159.242

Automatically generated by Colab.

Original file is located at
    https://colab.research.google.com/drive/16y68gc0r9IhP7zQrYaHn726QzpMNc-uz
"""

import pandas as pd
df = pd.read_csv('/content/Cost_of_Living_Index_by_Country_2024.csv')

df.head()

df.describe().T

import geopandas as gpd
import matplotlib.pyplot as plt

world = gpd.read_file(gpd.datasets.get_path('naturalearth_lowres'))

filtered_world = world[world['name'].isin(df['Country'])]

merged = filtered_world.set_index('name').join(
    pd.DataFrame(df).set_index('Country')
)

fig, ax = plt.subplots(1, 1, figsize=(15, 10))
world.boundary.plot(ax=ax)
merged.plot(column='Cost of Living Index', ax=ax, legend=True, legend_kwds={'label': "Cost of Living Index", 'orientation': "horizontal"})

plt.title('Country by Cost of Living Index')
plt.show()

import plotly.express as px
world = gpd.read_file(gpd.datasets.get_path('naturalearth_lowres'))

world = world.rename(columns={'name': 'Country'})
merged = world.merge(df, on='Country')

fig = px.choropleth(
    merged,
    locations='Country',
    locationmode='country names',
    color="Cost of Living Index",
    hover_name="Country",
    hover_data={
        'Cost of Living Index': True,
        'Rent Index': True,
        'Cost of Living Plus Rent Index': True,
        'Groceries Index': True,
        'Restaurant Price Index': True,
        'Local Purchasing Power Index': True
    },
    color_continuous_scale=px.colors.sequential.Plasma,
    title="Countries by Cost of Living Index"
)

fig.show()