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How Much of the World Has Access to the Internet?

📖 Background

You work for a policy consulting firm. One of the firm's principals is preparing to give a presentation on the state of internet access in the world. She needs your help answering some questions about internet accessibility across the world.

💾 The data

The research team compiled the following tables (source):
internet
  • "Entity" - The name of the country, region, or group.
  • "Code" - Unique id for the country (null for other entities).
  • "Year" - Year from 1990 to 2019.
  • "Internet_usage" - The share of the entity's population who have used the internet in the last three months.
people
  • "Entity" - The name of the country, region, or group.
  • "Code" - Unique id for the country (null for other entities).
  • "Year" - Year from 1990 to 2020.
  • "Users" - The number of people who have used the internet in the last three months for that country, region, or group.
broadband
  • "Entity" - The name of the country, region, or group.
  • "Code" - Unique id for the country (null for other entities).
  • "Year" - Year from 1998 to 2020.
  • "Broadband_Subscriptions" - The number of fixed subscriptions to high-speed internet at downstream speeds >= 256 kbit/s for that country, region, or group.

Acknowledgments: Max Roser, Hannah Ritchie, and Esteban Ortiz-Ospina (2015) - "Internet." OurWorldInData.org.

💪 Challenge

Create a report to answer the principal's questions. Include:

  1. What are the top 5 countries with the highest internet use (by population share)?
  2. How many people had internet access in those countries in 2019?
  3. What are the top 5 countries with the highest internet use for each of the following regions: 'Middle East & North Africa', 'Latin America & Caribbean', 'East Asia & Pacific', 'South Asia', 'North America', 'Europe & Central Asia'?
  4. Create a visualization for those five regions' internet usage over time.
  5. What are the 5 countries with the most internet users?
  6. What is the correlation between internet usage (population share) and broadband subscriptions for 2019?
  7. Summarize your findings.

Note: This is how the World Bank defines the different regions.

Imports

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns

sns.set_style("whitegrid")

pd.set_option('display.float_format', '{:,.2f}'.format)
# Read the broadband table
broadband = pd.read_csv('data/broadband.csv')

# Read the internet table
internet = pd.read_csv('data/internet.csv')

# Read the people table
people = pd.read_csv('data/people.csv')

# regions
region_df = pd.read_excel('data/CLASS.xlsx')

Q1. What are the top 5 countries with the highest internet use (by population share)?

year = 2019

merge = internet.groupby('Entity')['Year'].max().reset_index()
merge = merge[merge['Year'] == year]
df = pd.merge(internet, merge, on = ['Entity', 'Year'], how = 'inner').sort_values(by = "Internet_Usage", ascending = False).reset_index(drop = True).head()
df
plt.figure(figsize = (16, 4))
sns.barplot(data = df, y = 'Entity', x = 'Internet_Usage')
plt.tight_layout()

Q2. How many people had internet access in those countries in 2019?

countries = df['Entity'].values
tmp = people[(people['Entity'].isin(countries)) & (people['Year'] == 2019)]
tmp = pd.merge(df, tmp, on = 'Code', how = 'inner').drop(['Entity_y','Year_y'], axis = 1)
tmp.columns = ['Entity','Code','Year','Internet_Usage','Users']
tmp = tmp.head(5)
tmp
plt.figure(figsize = (10, 8))
ax = sns.scatterplot(data = tmp, x = 'Users', y = 'Internet_Usage')

# Annotate each point in the scatter plot
for i in range(tmp.shape[0]):
    ax.text(tmp['Users'][i] + 0.1,  # use proper indexing for DataFrame columns
            tmp['Internet_Usage'][i] + 0.1,  # use proper indexing for DataFrame columns
            tmp['Entity'][i],  # use proper indexing for DataFrame columns
            horizontalalignment='left',
            size='small', color='black', weight='semibold')

plt.ylim(0, 110)
plt.title("Internet users vs. Internet Usages as a percent of the total population")
plt.tight_layout()

Q3. What are the top 5 countries with the highest internet use for each of the following regions: 'Middle East & North Africa', 'Latin America & Caribbean', 'East Asia & Pacific', 'South Asia', 'North America', 'Europe & Central Asia'?


regions = sorted([x for x in region_df['Region'].dropna().unique()])

fig, axs = plt.subplots(2, 4, figsize = (16, 8), sharex = True)
axs = axs.flatten()

max_years = internet.groupby('Entity')['Year'].max().reset_index()
tmp = pd.merge(internet, region_df, on = 'Code', how = 'left')
tmp = pd.merge(tmp, max_years, on = ['Entity', 'Year'], how = 'inner')
tmp = tmp[['Region','Entity','Code','Year','Internet_Usage']].sort_values(by = "Internet_Usage", ascending = False)

i = 0
for region in regions:
    tmp2 = tmp[tmp['Region'] == region].head(5)
    sns.barplot(data = tmp2, x = 'Internet_Usage', y = 'Entity', ax = axs[i])
    axs[i].set_title(f"{region}")
    axs[i].set_xlabel("% Internet Usage")
    i += 1

axs[i].remove()

plt.tight_layout()
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