Saving

Save a table to a file

save sales as "outputs/sales.csv"
save summary as "outputs/summary.parquet"

The file format is inferred from the destination suffix. Pandas supports CSV, Parquet, JSON Lines, Feather, Excel, and pickle. Polars and DuckDB support the formats available through their backends.

Spark DataFrames can also write Delta destinations:

save sales as "dbfs:/mnt/results/sales.delta"

Save a managed table

save sales as table "main.analytics.sales"

Managed table saves use the active backend. Spark DataFrames use saveAsTable; DuckDB and SQL compilation use CREATE OR REPLACE TABLE.

Save a data package

save package as "outputs/my_analysis"

This saves all tables, charts, rendered tables, and Pivotal parameters in the current session.

save package as "~/projects/output/my_analysis"
    format parquet
    chart_format svg
    include sales, summary, chart1
    exclude raw, debug_plot

Option	Description
format <fmt>	Table format: csv (default) or parquet
chart_format <fmt>	Chart image format: png (default) or svg
include <names>	Comma-separated list of objects to include
exclude <names>	Comma-separated list of objects to exclude

The earlier save "<package_name>" form remains supported for compatibility, but new code should use save package as "<path>".

Loading a saved package

python import pivotal; _pivotal_pkg = pivotal.Package.open("my_analysis")

Then load package tables from Python:

tables = _pivotal_pkg.load_all()
sales = _pivotal_pkg.load_table("sales")

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delete - remove a table

Remove a table from the current session to free memory:

delete raw_import
delete scratch

In Jupyter, this is equivalent to del raw_import in Python.