return a single column from the table. This is generally only useful to select an indexable .. warning:: Pandas uses PyTables for reading and writing HDF5 files, which allows serializing object-dtype data with pickle when using the "fixed" format.
(
self,
key: str,
column: str,
start: int | None = None,
stop: int | None = None,
)
| 968 | return tbl.read_coordinates(where=where, start=start, stop=stop) |
| 969 | |
| 970 | def select_column( |
| 971 | self, |
| 972 | key: str, |
| 973 | column: str, |
| 974 | start: int | None = None, |
| 975 | stop: int | None = None, |
| 976 | ): |
| 977 | """ |
| 978 | return a single column from the table. This is generally only useful to |
| 979 | select an indexable |
| 980 | |
| 981 | .. warning:: |
| 982 | |
| 983 | Pandas uses PyTables for reading and writing HDF5 files, which allows |
| 984 | serializing object-dtype data with pickle when using the "fixed" format. |
| 985 | Loading pickled data received from untrusted sources can be unsafe. |
| 986 | |
| 987 | See: https://docs.python.org/3/library/pickle.html for more. |
| 988 | |
| 989 | Parameters |
| 990 | ---------- |
| 991 | key : str |
| 992 | column : str |
| 993 | The column of interest. |
| 994 | start : int or None, default None |
| 995 | stop : int or None, default None |
| 996 | |
| 997 | Raises |
| 998 | ------ |
| 999 | raises KeyError if the column is not found (or key is not a valid |
| 1000 | store) |
| 1001 | raises ValueError if the column can not be extracted individually (it |
| 1002 | is part of a data block) |
| 1003 | |
| 1004 | """ |
| 1005 | tbl = self.get_storer(key) |
| 1006 | if not isinstance(tbl, Table): |
| 1007 | raise TypeError("can only read_column with a table") |
| 1008 | return tbl.read_column(column=column, start=start, stop=stop) |
| 1009 | |
| 1010 | def select_as_multiple( |
| 1011 | self, |