scanpy.read#
- scanpy.read(filename, backed=None, *, sheet=None, ext=None, delimiter=None, first_column_names=False, backup_url=None, cache=False, cache_compression=_empty, **kwargs)[source]#
Read file and return
AnnDataobject.To speed up reading, consider passing
cache=True, which creates an hdf5 cache file.- Parameters:
- filename
PathLike[str] |str If the filename has no file extension, it is interpreted as a key for generating a filename via
sc.settings.writedir / (filename + sc.settings.file_format_data). This is the same behavior as insc.read(filename, ...).- backed
Optional[Literal['r','r+']] (default:None) If
'r', loadAnnDatainbackedmode instead of fully loading it into memory (memorymode). If you want to modify backed attributes of the AnnData object, you need to choose'r+'.- sheet
str|None(default:None) Name of sheet/table in hdf5 or Excel file.
- ext
str|None(default:None) Extension that indicates the file type. If
None, uses extension of filename.- delimiter
str|None(default:None) Delimiter that separates data within text file. If
None, will split at arbitrary number of white spaces, which is different from enforcing splitting at any single white space' '.- first_column_names
bool(default:False) Assume the first column stores row names. This is only necessary if these are not strings: strings in the first column are automatically assumed to be row names.
- backup_url
str|None(default:None) Retrieve the file from an URL if not present on disk.
- cache
bool(default:False) If
False, read from source, ifTrue, read from fast ‘h5ad’ cache.- cache_compression
Union[Literal['gzip','lzf'],None,Empty] (default:_empty) See the h5py Filter pipeline. (Default:
settings.cache_compression)- kwargs
Parameters passed to
read_loom().
- filename
- Return type:
- Returns:
An
AnnDataobject