datamanagement

What problem does it solve?

This Skill addresses the challenges of data management, wrangling, and transformation in R, providing a comprehensive solution for data scientists and analysts.

Core Features & Use Cases

• Data Import: Handles CSV, Excel, SPSS, Stata, and SAS files with support for multiple files and sheets.
• Data Cleaning: Renames columns, converts data types, handles missing data, and recodes variables.
• Data Transformation: Utilizes dplyr for row and column operations, summarizing data, and reshaping datasets.
• Joining/Merging: Performs various join operations like left, inner, semi, and anti joins.
• Functional Programming: Implements purrr for list manipulation and functional programming patterns.
• Epidemiological Data: Provides patterns for WHO NCD STEPS data preparation and surveillance/line-list cleaning.
• Data Validation: Includes assertion checks and summary validation for data quality assurance.
• Shiny Integration: Combines with shinyskill for data processing in Shiny apps.

Quick Start

Use the datamanagement skill to clean and transform your dataset named 'data.csv'.