Data

Project data consists of columns, rows, and series. Define a stable schema first so manual entry, CSV import, calculations, and visualizations interpret values consistently.

Columns

Columns describe each value in a row. Supported input types include text, numbers, dates, datetimes, and colors. A required column must have a valid value in every imported row. Calculated columns derive their value from other data and are not imported directly.

Changing a column after data exists can affect validation and visualizations, so preview dependent work after schema changes.

Rows and series

Each row is one ranked item or observation with values matching the project columns. Series describe values across the visualization timeline. Keep names and date formats consistent so sorting and playback produce predictable results.

CSV import

1. Create the destination columns first.
2. Open the row import workflow and select a CSV file.
3. Review detected columns and validation messages.
4. Correct every blocking error before importing.
5. Confirm the import count and inspect representative rows afterward.

An import is all-or-nothing when validation reports errors; invalid input is not partially inserted. Extra calculated-column values are ignored because RankGlide computes them.

Export and quality checks

CSV export includes project rows according to the selected settings and requires at least one project column. Before building a visualization, check missing required values, number and date formats, duplicate items, and unexpectedly large changes between series.

When the data is ready, continue to visualizations.