Cemetery Data Analysis Report
Summary
This report analyzes a dataset of 26612 burial records from various cemeteries, primarily in Morocco, spanning from 1689-03-24 to 2022-04-19. The data includes demographic details (gender, age), burial locations, years, names, and regions. Key findings include a significant male bias in recorded burials (27.2% male vs. 20.6% female), an average age of 57 years, and a concentration of burials in Casablanca Ben M'Sik. The analysis reveals temporal trends, with a peak in burials during the 1950s, and highlights the prevalence of certain surnames like Harrouch.
Interesting Fact: The dataset shows an unusual spike in burials in 1905 (1609 records), which is significantly higher than surrounding years, suggesting a possible historical event or data collection anomaly that warrants further investigation.
Key Metrics
Metric | Value |
---|---|
total_records | 26612.00 |
male_count | 7243.00 |
female_count | 5475.00 |
male_percentage | 27.20 |
female_percentage | 20.60 |
avg_age | 57.00 |
avg_years_since_burial | 76.00 |
oldest_burial | 1689-03-24 |
oldest_burial_years | 336.09 |
most_recent_burial | 2022-04-19 |
most_recent_burial_years | 3.03 |
Burial Distribution by Cemetery

Burial Trends by Decade

Most Common Surnames

Top 10 Surnames
Name | Count | Percentage | Rank |
---|---|---|---|
Harrouch | 71 | 0.77% | 1 |
Nadjar | 61 | 0.66% | 2 |
Hadjadj | 53 | 0.57% | 3 |
Drai | 49 | 0.53% | 4 |
Hayoun | 48 | 0.52% | 5 |
Tourdjeman | 44 | 0.48% | 6 |
Hammou | 43 | 0.47% | 7 |
Chemouil | 41 | 0.44% | 8 |
Sayagh | 41 | 0.44% | 9 |
Sebaoun | 39 | 0.42% | 10 |
Burial Distribution by Region

Conclusion
The analysis of the cemetery dataset provides valuable insights into burial patterns in Morocco over several centuries. The concentration of burials in urban centers like Casablanca Ben M'Sik, the peak in the mid-20th century, and the prevalence of specific surnames suggest cultural and historical influences on the dataset. The 1905 spike is a notable anomaly that could reflect a significant event or data collection bias. Future research could explore the socio-historical context of these patterns and validate the dataset's completeness.