Life expectancy comparison between Australian and Cambodian populations between 1950 and 2023

Introduction

We wanted to look at life expectancy and population over tie between Australia and Cambodia to compare differences bettwen diferent regions We used the popultion csvand extracted data from Janyary population column and also identified australia and Cambodia We generated graphs using seaborn and can see the effect of the war in Cambodiaduring the late 70s

# Set up code
import pandas as pd


import pandas as pd

import matplotlib.pyplot as plt

import seaborn as sns



df_raw = pd.read_csv("../../data_sources/population.csv")

df = df_raw.copy()

plt.show()

df_raw.shape

df_raw.columns

World=df.loc[df["Region"]=="World"]

sns.lineplot(data=World, x="Year", y="Jan.Population")


 

df_raw = pd.read_csv("../../data_sources/population.csv")

plt.show()

df_raw.shape

df_raw.columns

 

df["Jan.Population"]

Australia=df.loc[df["Region"]=="Australia"]

sns.lineplot(data=Australia, x="Year", y="Life.Expectancy.at.Birth..both.sexes..years.")

Cambodia=df.loc[df["Region"]=="Cambodia"]

sns.lineplot(data=Cambodia, x="Year", y="Life.Expectancy.at.Birth..both.sexes..years.")



sns.lineplot(data=Cambodia, x="Year", y="Jan.Population")

            

countries = ["Australia", "Cambodia",]

df_countries = df[df["Region"].isin(countries)].copy()

 

plt.figure(figsize=(10, 6))

for country in countries:

    subset = df_countries[df_countries["Region"] == country]

    plt.plot(subset["Year"], subset["Jan.Population"], label=country)

plt.xlabel("Year")

plt.ylabel("Population")

plt.title("Population Over Time")

plt.legend()

plt.grid(True)

plt.show()

 

plt.figure(figsize=(10, 6))

for country in countries:

    subset = df_countries[df_countries["Region"] == country]

    plt.plot(subset["Year"], subset["Life.Expectancy.at.Birth..both.sexes..years."], label=country)

plt.xlabel("Year")

plt.ylabel("Life Expectancy at Birth")

plt.title("Life Expectancy Over Time")

plt.legend()

plt.grid(True)

plt.show()