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Analyze tabular and JSON data interactively with code execution and variable tracking.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "dataHill" yet — see the docs or source repo.
Load ./sales_2024.xlsx, inspect columns and missing values, summarize sales by region, and use Python code to provide a monthly trend analysis.
A dataset overview, data quality checks, regional summary table, and monthly trend analysis with code and findings.
Read ./api_logs.json, count error types, calculate daily request volume, and keep key variables available for follow-up questions.
Error category statistics, daily request trends, and reusable intermediate variables for later session queries.
In the current session, load ./users.csv, write and run code to deduplicate records and normalize email fields, then show record counts before and after processing.
Executable code, a preview of cleaned results, and a comparison of record counts before and after cleaning.
Load datasets, compute statistics, and create charts for data exploration.
Explore CSV datasets with summaries, cleaning, correlations, and statistical tests.
Analyze local CSV or Parquet datasets and generate insights without full uploads.
Profile new datasets to assess structure, quality, distributions, and analysis priorities.
Turn analyzed data into a shareable Excel-like spreadsheet with formulas and tables.
Perform advanced data analysis and dataframe operations with comprehensive Pandas capabilities.