Studio Data

Analisis, transformasi, dan visualisasikan data CSV dalam lingkungan kerja terintegrasi.

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Cara menggunakan Studio Data

Selesaikan tugasmu dengan sempurna dalam tiga langkah mudah.

1

Unggah CSV

Muat file CSV ke dalam studio.

2

Analisis dan transformasi

Filter, urutkan, transformasi, dan gabungkan kolom dalam satu tampilan.

3

Ekspor

Unduh hasilnya sebagai CSV, JSON, atau Excel.

Pertanyaan yang sering ditanyakan

Semua yang perlu kamu ketahui tentang Studio Data.

Apa itu studio data?

Lingkungan terintegrasi untuk analisis CSV — filter, transformasi, dan pratinjau dalam satu tab.

Apakah data diunggah?

Tidak. Semua berjalan lokal.

Bisakah saya menyimpan transformasi?

Ya — ekspor pipeline transformasi sebagai JSON untuk digunakan kembali.

Batas ukuran?

Proses file hingga batas memori browser.

Format ekspor?

CSV, JSON, dan Excel.

Can I load multiple CSV files and JOIN them?

Yes. Upload multiple files using the multi-file drop zone. Each file becomes its own table. Write a standard SQL JOIN across the table names, and DuckDB executes the join in-memory. For example: SELECT a.name, b.revenue FROM customers a JOIN sales b ON a.id = b.customer_id. This is a common workflow for analysts combining a CRM export with a billing export.

What SQL dialect does Data Studio support?

Data Studio uses DuckDB's SQL dialect, which is largely compatible with PostgreSQL syntax. It supports CTEs (WITH clauses), window functions (ROW_NUMBER, RANK, LAG, LEAD), ARRAY functions, JSON functions, PIVOT, and UNNEST. DuckDB also supports reading Parquet and JSON natively, in addition to CSV.

What Python libraries are available in the Python mode?

Pyodide ships with a large set of pre-compiled scientific Python packages: Pandas, NumPy, Matplotlib, SciPy, scikit-learn, and many others. Pure-Python packages from PyPI can also be installed at runtime using micropip.install('package-name'). C-extension packages that are not pre-compiled for WASM are not supported.