polars.DataFrame.estimated_size#

DataFrame.estimated_size(unit: SizeUnit = 'b') → int | float[source]#

Return an estimation of the total (heap) allocated size of the DataFrame.

Estimated size is given in the specified unit (bytes by default).

This estimation is the sum of the size of its buffers, validity, including nested arrays. Multiple arrays may share buffers and bitmaps. Therefore, the size of 2 arrays is not the sum of the sizes computed from this function. In particular, [StructArray]’s size is an upper bound.

When an array is sliced, its allocated size remains constant because the buffer unchanged. However, this function will yield a smaller number. This is because this function returns the visible size of the buffer, not its total capacity.

FFI buffers are included in this estimation.

Parameters:

unit{‘b’, ‘kb’, ‘mb’, ‘gb’, ‘tb’}: Scale the returned size to the given unit.

Examples

>>> df = pl.DataFrame(
...     {
...         "x": list(reversed(range(1_000_000))),
...         "y": [v / 1000 for v in range(1_000_000)],
...         "z": [str(v) for v in range(1_000_000)],
...     },
...     schema=[("x", pl.UInt32), ("y", pl.Float64), ("z", pl.String)],
... )
>>> df.estimated_size()
17888890
>>> df.estimated_size("mb")
17.0601749420166