vastorbit.VastFrame.del_catalog¶

VastFrame.del_catalog() → VastFrame¶

Deletes the current VastFrame catalog.

Returns:: self
Return type:: VastFrame

Examples

Aggregate results are cached to optimize computation. Sometimes cached results can be problemtic or not desired. In those cases del_catalog can be used to delete all cached aggregates.

Let us look at the below example:

Let’s begin by importing vastorbit.

import vastorbit as vo

Hint

By assigning an alias to vastorbit, we mitigate the risk of code collisions with other libraries. This precaution is necessary because vastorbit uses commonly known function names like “average” and “median”, which can potentially lead to naming conflicts. The use of an alias ensures that the functions from vastorbit are used as intended without interfering with functions from other libraries.

We have a dummy data:

vdf = vo.VastFrame({"val": [0, 10, 20]})

	123 val Integer
1	0
2	10
3	20

Rows: 1-3 | Column: val | Type: integer

We can create the summary of the VastFrame using:

vdf.describe()

	count	mean	std	min	approx_25%	approx_50%	approx_75%	max
"val"	3.0	10.0	10.0	0.0	0.0	10.0	20.0	20.0

Rows: 1-1 | Columns: 9

No if we look at the cache, we can see the stored values:

vdf["val"]._catalog

In order to erase the stored values we can use:

vdf.del_catalog()

Now there will not be any stored values:

vdf["val"]._catalog