Convert dask Array to dask Dataframe Parameters ---------- columns: list or string list of column names if DataFrame, single string if Series index : dask.dataframe.Index, optional An optional *dask* Index to use for the output Series or DataF
(self, columns=None, index=None, meta=None)
| 1827 | return to_hdf5(filename, datapath, self, **kwargs) |
| 1828 | |
| 1829 | def to_dask_dataframe(self, columns=None, index=None, meta=None): |
| 1830 | """Convert dask Array to dask Dataframe |
| 1831 | |
| 1832 | Parameters |
| 1833 | ---------- |
| 1834 | columns: list or string |
| 1835 | list of column names if DataFrame, single string if Series |
| 1836 | index : dask.dataframe.Index, optional |
| 1837 | An optional *dask* Index to use for the output Series or DataFrame. |
| 1838 | |
| 1839 | The default output index depends on whether the array has any unknown |
| 1840 | chunks. If there are any unknown chunks, the output has ``None`` |
| 1841 | for all the divisions (one per chunk). If all the chunks are known, |
| 1842 | a default index with known divisions is created. |
| 1843 | |
| 1844 | Specifying ``index`` can be useful if you're conforming a Dask Array |
| 1845 | to an existing dask Series or DataFrame, and you would like the |
| 1846 | indices to match. |
| 1847 | meta : object, optional |
| 1848 | An optional `meta` parameter can be passed for dask |
| 1849 | to specify the concrete dataframe type to use for partitions of |
| 1850 | the Dask dataframe. By default, pandas DataFrame is used. |
| 1851 | |
| 1852 | See Also |
| 1853 | -------- |
| 1854 | dask.dataframe.from_dask_array |
| 1855 | """ |
| 1856 | from dask.dataframe import from_dask_array |
| 1857 | |
| 1858 | return from_dask_array(self, columns=columns, index=index, meta=meta) |
| 1859 | |
| 1860 | def to_backend(self, backend: str | None = None, **kwargs): |
| 1861 | """Move to a new Array backend |