The Power Imbalance in Gaza’s Conflict?

economy
python
The disproportionate nature of the Gaza conflict.
Published

Oct 14, 2026

Keywords

war

Summary

The graphic shows the disproportionate nature of the Gaza conflict, where Israel’s advanced military and robust economy contrast with Gaza’s limited resources, fragile economy, and vulnerable population.

Code 
# Libraries
# =====================================================================
import os
from io import BytesIO
import requests
import wbgapi as wb
import pandas as pd
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
import matplotlib.ticker as ticker
from matplotlib.offsetbox import OffsetImage, AnnotationBbox

# Data Extraction (Countries)
# =====================================================================
# Crear el DataFrame
data = {
    'year': ['2024', '2024'],
    'iso3': ['PSE', 'ISR'],
    'country': ['Palestine', 'Israel'],
    'ngdpdpc': [2.592, 54.176],
    'lp': [5.3, 10] 
}

df = pd.DataFrame(data)
df['ngdpd'] = df['ngdpdpc'] * df['lp']

# Data Manipulation
# =====================================================================
# Add calculated fields
df['lp_percent'] = df['lp'] / df['lp'].sum()
df['ngdpd_percent'] = df['ngdpd'] / df['ngdpd'].sum()
df['gap'] = df['ngdpd_percent'] - df['lp_percent']

# Ordenar por gap
df = df.sort_values(by='gap', ascending=True)

# Calculate cumulative and left positions
df['lp_cum'] = df['lp'].cumsum()
df['lp_per'] = df['lp'] / df['lp'].sum()
df['lp_cum_per'] = df['lp_cum'] / df['lp_cum'].max()
df['left'] = df['lp_cum_per'] - df['lp_per']

print(df)

# Data Visualization
# =====================================================================
# Font and style
plt.rcParams.update({'font.family': 'sans-serif', 'font.sans-serif': ['Franklin Gothic'], 'font.size': 9})
sns.set(style="white", palette="muted")

# Create figure
fig, ax = plt.subplots(figsize=(10, 6))

# Create a palette
palette = sns.color_palette("coolwarm", as_cmap=True).reversed()
gdp_min = -0.05
gdp_max = 0.05
norm = plt.Normalize(gdp_min, gdp_max)
colors = palette(norm(df['gap']))

# Barplot
bars = plt.bar(
    df['left'],
    df['ngdpdpc'],
    width=df['lp_per'],
    alpha=1,
    align='edge',
    edgecolor='grey',
    color=colors,
    linewidth=0.1
)

# Add title and subtitle
fig.add_artist(plt.Line2D([0.095, 0.095], [0.87, 0.97], linewidth=6, color='#203764', solid_capstyle='butt'))
plt.text(0.02, 1.13, f'The Power Imbalance in Gaza’s Conflict', fontsize=16, fontweight='bold', ha='left', transform=plt.gca().transAxes)
plt.text(0.02, 1.09, f'Israel''s economic superiority and its dominant power in the conflict', fontsize=11, color='#262626', ha='left', transform=plt.gca().transAxes)
plt.text(0.02, 1.05, f'(gross domestic product in $USD)', fontsize=9, color='#262626', ha='left', transform=plt.gca().transAxes)

# Remove spines
ax = plt.gca()
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
ax.spines['bottom'].set(color='gray', linewidth=1)
ax.spines['left'].set_linewidth(False)

# Configuration
plt.xlim(0, df['lp_cum_per'].max())
ax.set_xticks([])
plt.ylim(0, 60)
ax.yaxis.set_major_locator(ticker.MultipleLocator(5))
plt.ylabel('GDP per capita ($)', fontsize=10, fontweight='bold')
plt.xlabel('Population (M)', fontsize=10, fontweight='bold', labelpad=15)
plt.tick_params(axis='y', labelsize=9)
plt.gca().yaxis.set_major_formatter(ticker.FuncFormatter(lambda x, _: f'{round(x*1000, 1):,.0f}'))

# Define flags
flag_urls = {
    'PSE': 'https://raw.githubusercontent.com/matahombres/CSS-Country-Flags-Rounded/master/flags/PS.png',
    'ISR': 'https://raw.githubusercontent.com/matahombres/CSS-Country-Flags-Rounded/master/flags/IL.png'

}

# Load flags once
flags = {country: mpimg.imread(BytesIO(requests.get(url).content)) 
         for country, url in flag_urls.items()}

# For each bar, add the corresponding flag and country name
for bar, iso3 in zip(bars, df['iso3']):
    if iso3 in flags:
        img = flags[iso3]
        imagebox = OffsetImage(img, zoom=0.04)
        x = bar.get_x() + bar.get_width() / 2

        offset = 1.5
        text_offset = 5

        # Positioning logic
        if bar.get_height() >= 0:
            y_flag = bar.get_height() + offset
            box_align = (0.5, 0)
            text_y = y_flag + text_offset
            va_text = 'bottom'
        else:
            y_flag = bar.get_height() - offset
            box_align = (0.5, 1)
            text_y = y_flag - text_offset
            va_text = 'top'

        # Add flag
        ab = AnnotationBbox(imagebox, (x, y_flag), frameon=False, box_alignment=box_align)
        ax.add_artist(ab)

        # Add country name
        country_name = df.loc[df['iso3'] == iso3, 'country'].values[0]
        ax.text(x, text_y, country_name, ha='center', va=va_text, fontsize=9, fontweight='bold', color='#404040')
        
        # Add population
        population = df.loc[df['iso3'] == iso3, 'lp'].values[0]
        formatted_pop = f'{round(population*100, 1):,.0f}'.replace(',', '.')
        ax.text(x, -1, formatted_pop, ha='center', va='top', fontsize=9, color="#000000")
        
        # Add country name
        if iso3 == 'ISR':
            ax.text(x, text_y-35, "40-fold", ha='center', va=va_text, fontsize=30, fontweight='bold', color="#FFFFFF")
            ax.text(x, text_y-38, "Gross Domestic Product of Palestine", ha='center', va=va_text, fontsize=10, fontweight='bold', color="#FFFFFF")

# Add Year label
plt.text(1, 1.15, f'{df['year'].max()}',
    transform=plt.gca().transAxes,
    fontsize=22, ha='right', va='top',
    fontweight='bold', color='#D3D3D3',
    bbox=dict(facecolor='white', edgecolor='none', boxstyle='square,pad=0.3'))

# Add Data Source
plt.text(0, -0.1, 'Data Source:',
    transform=plt.gca().transAxes, 
    fontsize=8,
    fontweight='bold',
    color='gray')
space = " " * 23
plt.text(0, -0.1, space + 'World Bank (2024)', 
    transform=plt.gca().transAxes, 
    fontsize=8,
    color='gray')

# Adjust layout
plt.tight_layout()

# Save it...
max_year = df['year'].max()
download_folder = os.path.join(os.path.expanduser("~"), "Downloads")
filename = os.path.join(download_folder, f"FIG_WB_Israel_Dominance_{max_year}.png")
plt.savefig(filename, dpi=300, bbox_inches='tight')

# Show :)
plt.show()

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