electricsheepafrica/nigerian-telecom-voice-data-sms-usage-patterns

Voice Data SMS Usage Patterns

Dataset Description

Monthly usage statistics per customer including voice minutes, data consumption, and SMS counts

Dataset Information

• Category: Customer and User Behavior
• Format: CSV, Parquet
• Rows: 500,000
• Columns: 11
• Date Generated: 2025-10-05
• Location: data/voice_data_sms_usage_patterns/

Schema

Column	Type	Sample Values
customer_id	String	CUST9540788
phone_number	String	+2349075150857
operator	String	Airtel
month	String	2025-09
customer_segment	String	light
voice_minutes	Integer	100
data_gb	Float	1.85
sms_count	Integer	13
city	String	Kaduna
network_type	String	4G
account_type	String	prepaid

Sample Data

customer_id   phone_number operator   month customer_segment  voice_minutes  data_gb  sms_count   city network_type account_type
CUST9540788 +2349075150857   Airtel 2025-09            light            100     1.85         13 Kaduna           4G      prepaid
CUST4856981 +2348039340439      MTN 2025-09            light             21     0.85         22    Aba           4G     postpaid
CUST8119831 +2349096800725  9mobile 2025-09            heavy            830    46.99        352  Lagos           2G      prepaid

Nigerian Context

This dataset incorporates authentic Nigerian telecommunications characteristics:

• Geographic Coverage: Major Nigerian cities including Lagos, Abuja, Kano, Port Harcourt, Ibadan
• Operators: MTN, Airtel, Glo, 9mobile with realistic market shares
• Phone Numbers: Nigerian format (+234 prefixes)
• Currency: Nigerian Naira (NGN)
• Time Zone: West Africa Time (WAT, UTC+1)
• Network Types: 2G, 3G, 4G, 5G distribution

File Formats

CSV

data/voice_data_sms_usage_patterns/voice_data_sms_usage_patterns.csv

Parquet (Recommended)

data/voice_data_sms_usage_patterns/voice_data_sms_usage_patterns.parquet

Loading the Dataset

Python (Pandas)

import pandas as pd

# Load CSV
df = pd.read_csv('data/voice_data_sms_usage_patterns/voice_data_sms_usage_patterns.csv')

# Load Parquet (recommended for large datasets)
df = pd.read_parquet('data/voice_data_sms_usage_patterns/voice_data_sms_usage_patterns.parquet')

Python (PyArrow)

import pyarrow.parquet as pq

# Load Parquet
table = pq.read_table('data/voice_data_sms_usage_patterns/voice_data_sms_usage_patterns.parquet')
df = table.to_pandas()

License

MIT License - For educational and research purposes

Citation

Nigerian Telecom Datasets - Voice Data SMS Usage Patterns
Generated: 2025-10-05
Category: Customer and User Behavior
Rows: 500,000

Related Datasets

This dataset is part of the Nigerian Telecom Datasets collection, which includes 34 datasets covering network performance, customer behavior, financial transactions, infrastructure, geospatial data, customer experience, and emerging technologies.