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SQL to R DataFrame Converter

Transform SQL database dumps into R data frame code for statistical analysis and data science with automatic type detection

SQL Input

Convert SQL to other formats

SQL to ActionScriptSQL to ASCIISQL to AsciiDocSQL to ASPSQL to AvroSQL to BBCodeSQL to CSVSQL to DAX

R Code Output

Convert other formats to R DataFrame

CSV to R DataFrameExcel to R DataFrameHTML to R DataFrameJSON to R DataFrameLaTeX to R DataFrameMarkdown to R DataFrameMediaWiki to R DataFrameMySQL to R DataFrame

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About SQL to R DataFrame Converter

Convert SQL database dumps (CREATE TABLE and INSERT statements) to R data frame code with automatic type detection. Perfect for statistical analysis, data science, and machine learning workflows in R and RStudio.

Key Features

  • Automatic Type Detection: Detects logical, integer, numeric, and character types
  • data.frame() Generation: Creates proper R data frame code
  • Column Name Sanitization: Converts to valid R variable names
  • NA Handling: Properly handles missing values with NA
  • Type Comments: Includes comments showing detected types
  • Usage Examples: Includes print() and summary() statements
  • stringsAsFactors: Uses modern R practices (FALSE by default)
  • File Download: Save as .R file for RStudio

How to Use

  1. Input SQL Data: Paste your SQL CREATE TABLE and INSERT statements or upload a .sql file
  2. Review Output: The R code generates automatically with type detection
  3. Copy or Download: Use the Copy or Download button to save your R code
  4. Run in R: Execute the code in R, RStudio, or R Markdown

Type Detection

The converter automatically determines the appropriate R type:

  • logical: For TRUE/FALSE values
  • integer: For whole numbers
  • numeric: For decimal/floating-point values
  • character: For text values (default)
  • NA: For NULL or empty values

Example Conversion

SQL Input:

CREATE TABLE products (
  id INT,
  name VARCHAR(100),
  price DECIMAL(10,2),
  inStock BOOLEAN
);

INSERT INTO products VALUES (1, 'Laptop', 999.99, true);
INSERT INTO products VALUES (2, 'Mouse', 24.99, true);

R Output:

# R data frame generated from SQL table: products

products <- data.frame(
  id = c(1, 2)  # integer
  ,name = c("Laptop", "Mouse")  # character
  ,price = c(999.99, 24.99)  # numeric
  ,inStock = c(TRUE, TRUE)  # logical
  ,
  stringsAsFactors = FALSE
)

# View the data frame
print(products)

Common Use Cases

  • Statistical Analysis: Import database data for statistical tests
  • Data Science: Prepare data for machine learning models
  • Visualization: Create plots with ggplot2 from database data
  • Research: Analyze research data from databases
  • Reporting: Generate R Markdown reports from SQL data
  • Data Exploration: Explore database tables in RStudio
  • Teaching: Create datasets for R programming courses

R Data Frame Features

  • Column-based Structure: Each column is a vector of the same type
  • Named Columns: Access columns by name (df$column)
  • Row Names: Automatic row numbering
  • Type Safety: Each column maintains its data type
  • Subsetting: Easy filtering and selection
  • Compatible: Works with tidyverse, dplyr, ggplot2

Variable Name Sanitization

  • Special Characters: Replaced with underscores
  • Numbers: Prefixed with 'X' if starting with digit
  • Spaces: Converted to underscores
  • Reserved Words: Handled to avoid R keyword conflicts

Modern R Practices

  • stringsAsFactors = FALSE: Keeps strings as character vectors
  • c() Vectors: Explicit vector creation for clarity
  • Type Comments: Documents the intended data type
  • Print Statement: Includes code to view the data frame

Compatible R Packages

The generated data frames work seamlessly with:

  • tidyverse: dplyr, tidyr, ggplot2, readr
  • data.table: High-performance data manipulation
  • caret: Machine learning workflows
  • shiny: Interactive web applications
  • rmarkdown: Dynamic documents and reports

Supported SQL Syntax

  • CREATE TABLE: Extracts column names for data frame columns
  • INSERT INTO: Parses data values for type detection
  • Data Types: Handles all SQL data types (VARCHAR, INT, DECIMAL, BOOLEAN, etc.)
  • Quoted Strings: Handles single and double quotes with proper escaping
  • NULL Values: Converts to R's NA

Privacy & Security

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

FAQ

Does this tool connect to my database?

No. The converter only parses the SQL text you provide (CREATE TABLE and INSERT statements). It never connects to a live database or executes SQL commands.

How are R column types chosen?

The tool inspects values in each column and assigns a suitable R type such as logical, integer, numeric, or character. Ambiguous or mixed columns default to character.

What happens to NULL or empty values?

SQL NULL and empty values are converted to NA in the generated R code, which is the standard missing-value representation in R.

Can I use the output in tidyverse and other packages?

Yes. The generated data frame is a regular base R data.frame with stringsAsFactors = FALSE, so it works seamlessly with tidyverse, data.table, and most other R packages.

Is my SQL data uploaded anywhere?

No. All parsing and code generation runs directly in your browser. Your SQL input and the generated R code are never sent to any remote server.