MediaWiki to R DataFrame Converter

About MediaWiki to R DataFrame Converter

Convert MediaWiki table markup to R data frame code. Perfect for statistical analysis, data science workflows, and R programming with wiki data.

Key Features

• Automatic Type Detection: Infers column types (logical, integer, numeric, character)
• data.frame() Generation: Creates ready-to-run R code
• Column Name Sanitization: Converts headers to valid R variable names
• NA Handling: Properly handles missing values as NA
• MediaWiki Parser: Accurately parses MediaWiki table syntax
• Type Comments: Includes helpful comments about data types
• Copy & Download: Save as .R file for RStudio

How to Use

1. Input MediaWiki Table: Paste your MediaWiki table markup or upload a .wiki file
2. Review Output: The R DataFrame code generates automatically
3. Copy or Download: Use the Copy or Download button to save your .R file
4. Run in R: Execute the code in R, RStudio, or Jupyter notebooks

Type Detection

The converter automatically detects column types based on data values:

• logical: Values matching "TRUE" or "FALSE" (case-insensitive)
• integer: Whole numbers without decimal points
• numeric: Numbers with decimal points or scientific notation
• character: Text values (default type)

Example Conversion

MediaWiki Input:

{| class="wikitable" border="1"
! Name !! Age !! City !! Department
|-
| John Doe || 28 || New York || Engineering
|-
| Jane Smith || 34 || London || Marketing
|}

R DataFrame Output:

# Rows: 2, Columns: 4
# Column types: Name (character), Age (integer), City (character), Department (character)

df <- data.frame(
  Name = c("John Doe", "Jane Smith"),
  Age = c(28, 34),
  City = c("New York", "London"),
  Department = c("Engineering", "Marketing"),
  stringsAsFactors = FALSE
)

print(df)

Common Use Cases

• Statistical Analysis: Import wiki data for R statistical analysis
• Data Science: Use wiki tables in data science workflows
• Machine Learning: Prepare wiki data for ML models in R
• Visualization: Create plots and charts with ggplot2
• Research: Analyze research data from wiki documentation
• Reporting: Generate reports with R Markdown

R DataFrame Features

• stringsAsFactors = FALSE: Prevents automatic factor conversion
• c() Vectors: Uses R's combine function for column data
• NA Values: Empty cells converted to NA
• Type Preservation: Maintains numeric and logical types
• Print Statement: Includes print(df) for immediate output

Column Name Sanitization

MediaWiki headers are automatically converted to valid R variable names:

• Replaces special characters with underscores
• Removes leading/trailing underscores
• Prefixes numbers with 'X' (e.g., "1st" becomes "X1st")
• Handles duplicate names with numeric suffixes (_2, _3, etc.)
• Generates default names (column_1, column_2) for empty headers

MediaWiki Table Syntax

Supports standard MediaWiki table markup:

• {|: Table opening with optional attributes
• ! Header: Exclamation mark for header cells (separated by !!)
• |-: Row separator
• | Data: Pipe for data cells (separated by ||)
• |}: Table closing

Using in R

1. Copy or download the generated R code
2. Open RStudio or R console
3. Paste and run the code
4. The data frame 'df' will be created and displayed
5. Use df in your analysis, visualizations, or models

R Packages Compatibility

The generated data frames work seamlessly with popular R packages:

• dplyr: Data manipulation and transformation
• ggplot2: Data visualization and plotting
• tidyr: Data tidying and reshaping
• caret: Machine learning and modeling
• data.table: High-performance data operations
• rmarkdown: Dynamic reporting

Tips for Best Results

• Ensure MediaWiki table has clear header rows
• Use consistent data types within columns
• Avoid special characters in header names when possible
• Test with sample data before processing large tables
• Review column types in comments and adjust if needed
• Use stringsAsFactors = TRUE if you need factor columns

Privacy & Security

All conversions happen locally in your browser. Your MediaWiki data is never uploaded to any server, ensuring complete privacy and security.