Netflix Dashboard Analysis

An MS Excel dashboard project utilizing Pivot Tables to analyze 6,000+ titles.

Project Overview

  View Full Project on GitHub

Built an interactive Netflix dashboard in MS Excel using Pivot Tables, Pivot Charts, and Slicers to analyze 6,000+ titles across 543 locations.

Key Achievements: - Derived insights on content distribution (Movies vs TV Shows), top genres, audience ratings, and global presence. - Identified content growth trends (1925–2020) and delivered a visual report showcasing viewer preferences and market expansion.

Demonstrating Content Distribution with Python

While the original dashboard was built in Excel, below I recreate the Content Distribution pie chart using Python (pandas and matplotlib) to demonstrate my cross-platform analytical skills.

import pandas as pd
import matplotlib.pyplot as plt

# Recreating the statistics found in the dashboard
data = {'Category': ['Movies', 'TV Shows'], 'Share': [68, 32]}
df = pd.DataFrame(data)

# Visualizing with matplotlib
fig, ax = plt.subplots(figsize=(6, 6))
colors = ['#E50914', '#221F1F'] # Netflix brand colors
ax.pie(df['Share'], labels=df['Category'], autopct='%1.0f%%', startangle=90, colors=colors, textprops={'color':"w", 'weight':'bold'})
ax.set_title("Content Distribution: Movies vs TV Shows", fontsize=14, weight='bold')

# Add legend outside
ax.legend(labels=df['Category'], loc="center left", bbox_to_anchor=(1, 0.5))

plt.tight_layout()
plt.show()

Figure 1: Netflix Content Distribution Breakdown

As illustrated in Figure 1, Movies make up the predominant share of the content catalog.