See your data. Understand your environment. Act on it instantly.
AiR stays in sync with your R session in real time. Explore every dataframe, inspect columns, discover correlations, and take action with one click - all from the panel inside RStudio.
Get Started FreeAlways in sync with your R session
Every time your R environment changes - new dataframes loaded, variables updated, packages installed - AiR picks it up automatically. No manual refresh required.
Dataframes
Every loaded dataframe with row counts, column counts, and memory usage.
Columns
Full metadata for each column: type, unique values, missing %, range, and sample values.
Project Files
Your project structure: R scripts, data files, Rmd documents, and their relationships.
Active File
The file currently open in your editor, including cursor position and any selected code.
See your actual data, not just summaries
The Preview tab shows a scrollable table of real rows from your dataset. Sort by any column, see the actual values, and get a sense of your data before running any analysis.
| carat | cut | color | clarity | depth | price |
|---|---|---|---|---|---|
| 0.23 | Ideal | E | SI2 | 61.5 | $326 |
| 0.21 | Premium | E | SI1 | 59.8 | $326 |
| 0.23 | Good | E | VS1 | 56.9 | $327 |
| 0.29 | Premium | I | VS2 | 62.4 | $334 |
| 0.31 | Good | J | SI2 | 63.3 | $335 |
Inspect every column at a glance
The Columns tab gives you a sortable, searchable list of every variable. See data types, unique value counts, missing data percentages, ranges, and sample values. Click any column for a detailed distribution view.
Click any column to see its full distribution - histogram for numeric, bar chart for categorical. Includes summary statistics, percentiles, and outlier flags.
Discover relationships between variables
The Correlations tab automatically computes pairwise correlations for all numeric variables and ranks them by strength. Quickly identify the strongest predictors and multicollinearity risks.
From exploration to action in one click
The Data Explorer isn't just for looking. Every insight has an action button. Plot a column, run a full EDA report, clean the dataset, or summarize a variable - all without writing code.
Generate a ggplot visualization for any column. Histograms for numeric, bar charts for categorical. Opens in the Plots pane.
Launch a full exploratory data analysis on the selected dataset. Generates a complete R Markdown report with visualizations and insights.
Open the dataset in the Tidy tab for a full data preparation workflow. Audit issues, apply transforms, and export a clean copy.
Get a quick statistical summary of any column: mean, median, SD, quartiles, missing count, and unique values.
Data quality issues surfaced automatically
AiR scans every dataset for common issues and shows a quality banner at the top of the Data tab. Missing values, duplicate rows, constant columns, and type inconsistencies are flagged before you even start working.
3 columns have >20% missing values: income (24%), education_years (31%), occupation (22%)
847 duplicate rows detected (1.6% of dataset). Consider deduplication before analysis.
All column types are consistent. No mixed numeric/character columns detected.
Context makes every feature better
Smart Context isn't just a feature - it's the foundation. Every other AiR capability uses your environment data to produce better results.
Error Fixing
Knows your data shapes, so fixes account for actual column names and types - not guesses.
Code Editing
Sees your loaded packages and variables, so edits reference the right objects.
EDA Reports
Reads column metadata to plan the right visualizations - histograms for numeric, bar charts for factors.
Model Builder
Auto-detects regression vs classification from your target variable's type.
Data Cleaning
Identifies missing data patterns, type issues, and outliers from actual data profiles.
Chat Assistant
Answers questions about your data with real numbers - not hypothetical examples.
Your data, always at your fingertips
Load a dataset in R and AiR instantly knows everything about it.