metadata
license: gpl
language:
- en
tags:
- finance
- banking
size_categories:
- 1K<n<10K
Africa Automated Teller Machines (ATMs) (per 100,000 adults) Dataset
Overview
This dataset contains automated teller machines (atms) (per 100,000 adults) data for African countries from the World Bank.
Data Details
- Indicator Code: FB.ATM.TOTL.P5
- Description: Automated Teller Machines (ATMs) (per 100,000 adults)
- Geographic Coverage: 52 African countries
- Time Period: 2004-2023
- Data Points: 858 observations
- Coverage: 24.44% of possible country-year combinations
File Formats
Main Dataset (fb_atm_totl_p5_africa.csv)
- Rows: 54 countries
- Columns: 65 years (1960-2024)
- Structure: Countries as rows, years as columns
- Missing Value Treatment: Interpolation → Forward Fill → Backward Fill
- Use Case: Cross-sectional analysis, heatmaps, correlation analysis
Data Quality
Coverage Statistics
- Total Observations: 858
- Coverage Rate: 24.44%
- Earliest Data: 2004
- Latest Data: 2023
Countries with No Data
2 countries have no observations: Eritrea, Somalia
Usage Examples
Python
import pandas as pd
# Load main dataset
df = pd.read_csv('fb_atm_totl_p5_africa.csv', index_col=[0, 1])
R
# Load main dataset
df <- read.csv('fb_atm_totl_p5_africa.csv', row.names=c(1,2))
Source
World Bank Open Data - Automated Teller Machines (ATMs) (per 100,000 adults)
- Original File: API_FB.ATM.TOTL.P5_DS2_en_excel_v2_21147.xls
- Processed: 2025-08-18
License
This dataset is derived from World Bank Open Data and is available under the Creative Commons Attribution 4.0 International License.