21 lines
1.5 KiB
Markdown
Vendored
21 lines
1.5 KiB
Markdown
Vendored
[//]: # (title: Hierarchical data structures)
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[`DataFrame`](DataFrame.md) can represent hierarchical data structures using two special types of columns:
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* [`ColumnGroup`](DataColumn.md#columngroup) is a group of [columns](DataColumn.md)
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* [`FrameColumn`](DataColumn.md#framecolumn) is a column of [dataframes](DataFrame.md)
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You can read [`DataFrame`](DataFrame.md) [from json](read.md#read-from-json) or [from in-memory object graph](createDataFrame.md#todataframe) preserving original tree structure.
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Hierarchical columns can also appear as a result of some [modification operations](modify.md):
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* [group](group.md) produces [`ColumnGroup`](DataColumn.md#columngroup)
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* [groupBy](groupBy.md) produces [`FrameColumn`](DataColumn.md#framecolumn)
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* [pivot](pivot.md) may produce [`FrameColumn`](DataColumn.md#framecolumn)
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* [split](split.md) of [`FrameColumn`](DataColumn.md#framecolumn) will produce several [`ColumnGroup`](DataColumn.md#columngroup)
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* [implode](implode.md) converts [`ColumnGroup`](DataColumn.md#columngroup) into [`FrameColumn`](DataColumn.md#framecolumn)
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* [explode](explode.md) converts [`FrameColumn`](DataColumn.md#framecolumn) into [`ColumnGroup`](DataColumn.md#columngroup)
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* [merge](merge.md) converts [`ColumnGroup`](DataColumn.md#columngroup) into [`FrameColumn`](DataColumn.md#framecolumn)
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* etc.
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Operations in the navigation tree are grouped such that you can find operations and their respective inverse together, like `group` and `ungroup`. This allows you to quickly find out how to simplify any hierarchical structure you come across.
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