EDA of antimicrobial susceptibility in Gram-negative uropathogens in South West Nigeria
# Antimicrobial susceptibility patterns of Gram-negative uropathogens :
# Exploratory data analysis of a South West Nigeria tertiary hospital dataset,examining resistance patterns across organisms and antibiotics
## Dataset
Source: Otaigbe, Idemudia; ELIKWU, CHARLES; Ebeigbe, Ejime (2023), “Dataset on Antibiotic susceptibility patterns of Gram negative uropathogens from patients in a tertiary hospital in South west Nigeria”, Mendeley Data, V1,
Description: This dataset contains 3613 rows and 29 columns. Each row represents an antibiotic susceptibility test result for a bacterial isolate obtained from a patient sample. Key variables include sex, ward/clinic, specimen, culture, organisms, antibiotics tested, antimicrobial susceptibility results
## Objectives
1. To identify the most frequently isolated Gram-negative uropathogens
2. To determine the antimicrobial susceptibility profiles of the isolates
3. To determine the prevalence of multi-drug resistance among gram-negative isolates
4. To identify antimicrobial agents with comparatively high and low resistance rates among the gram-negative isolates
## Methodology
Workflow:
Tools:tidyverse, janitor, readxl, skimr, stringr, scales, ggplot2
## Results and Data Presentation
Refer to report (Project_Report_Elizabeth_Baidoo_capstone)
## Repository structure
├── data/
│ ├── raw/ # Original dataset (as sourced from Mendeley Data)
│ └── processed/ # Cleaned dataset used for analysis
├── scripts/ # R scripts for cleaning, transformation, and analysis
├── outputs/
│ ├── figures/ # Charts and visualizations (refer to report)
│ └── tables/ # Summary tables (refer to report
├── report/ # Full project report
└── README.md
## How to Reproduce
Clone this repository.
Open the R project/scripts in RStudio (or your preferred R environment).
Run the cleaning script(s) to reproduce the tidied dataset from the raw data.
Run the analysis script(s) to reproduce the summ …