MySQL to R DataFrame Converter
Transform MySQL database dumps into R DataFrame code with automatic type detection
MySQL Input
R DataFrame Output
About MySQL to R DataFrame Converter
Convert MySQL database dumps (CREATE TABLE and INSERT statements) to R data frame code. Perfect for statistical analysis, data science workflows, and R programming with MySQL 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 MySQL column names to valid R variable names
- NA Handling: Properly handles missing and NULL values as NA
- MySQL Parser: Accurately parses MySQL CREATE TABLE and INSERT syntax
- Type Comments: Includes helpful comments about data types
- Copy & Download: Save as .R file for RStudio
How to Use
- Input MySQL Data: Paste your MySQL CREATE TABLE and INSERT statements or upload a .sql file
- Review Output: The R DataFrame code generates automatically
- Copy or Download: Use the Copy or Download button to save your .R file
- 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
MySQL Input:
CREATE TABLE employees ( id INT PRIMARY KEY, name VARCHAR(100), age INT, city VARCHAR(50) ); INSERT INTO employees VALUES (1, 'John Doe', 28, 'New York'); INSERT INTO employees VALUES (2, 'Jane Smith', 34, 'London');
R DataFrame Output:
# Rows: 2, Columns: 4
# Column types: id (integer), name (character), age (integer), city (character)
df <- data.frame(
id = c(1, 2),
name = c("John Doe", "Jane Smith"),
age = c(28, 34),
city = c("New York", "London"),
stringsAsFactors = FALSE
)
print(df) Common Use Cases
- Statistical Analysis: Import MySQL data for R statistical analysis
- Data Science: Use MySQL tables in data science workflows
- Machine Learning: Prepare MySQL data for ML models in R
- Visualization: Create plots and charts with ggplot2
- Research: Analyze research data from MySQL databases
- 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 and NULL values converted to NA
- Type Preservation: Maintains numeric and logical types
- Print Statement: Includes print(df) for immediate output
Column Name Sanitization
MySQL column names 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
Supported MySQL Data Types
- Numeric: INT, BIGINT, DECIMAL, FLOAT, DOUBLE → integer/numeric
- String: VARCHAR, CHAR, TEXT, MEDIUMTEXT, LONGTEXT → character
- Boolean: BOOLEAN, TINYINT(1) → logical
- NULL: NULL values → NA in R
Using in R
- Copy or download the generated R code
- Open RStudio or R console
- Paste and run the code
- The data frame 'df' will be created and displayed
- 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 MySQL data has clear column names from CREATE TABLE
- Use consistent data types within columns
- Avoid special characters in column 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 MySQL data is never uploaded to any server, ensuring complete privacy and security.
