87 lines
2.8 KiB
Python
87 lines
2.8 KiB
Python
"""
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Read SAS sas7bdat or xport files.
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"""
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from pandas.io.common import _stringify_path
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def read_sas(
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filepath_or_buffer,
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format=None,
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index=None,
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encoding=None,
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chunksize=None,
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iterator=False,
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):
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"""
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Read SAS files stored as either XPORT or SAS7BDAT format files.
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Parameters
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----------
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filepath_or_buffer : str, path object or file-like object
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Any valid string path is acceptable. The string could be a URL. Valid
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URL schemes include http, ftp, s3, and file. For file URLs, a host is
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expected. A local file could be:
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``file://localhost/path/to/table.sas``.
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If you want to pass in a path object, pandas accepts any
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``os.PathLike``.
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By file-like object, we refer to objects with a ``read()`` method,
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such as a file handler (e.g. via builtin ``open`` function)
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or ``StringIO``.
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format : string {'xport', 'sas7bdat'} or None
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If None, file format is inferred from file extension. If 'xport' or
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'sas7bdat', uses the corresponding format.
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index : identifier of index column, defaults to None
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Identifier of column that should be used as index of the DataFrame.
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encoding : string, default is None
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Encoding for text data. If None, text data are stored as raw bytes.
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chunksize : int
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Read file `chunksize` lines at a time, returns iterator.
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iterator : bool, defaults to False
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If True, returns an iterator for reading the file incrementally.
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Returns
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-------
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DataFrame if iterator=False and chunksize=None, else SAS7BDATReader
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or XportReader
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"""
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if format is None:
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buffer_error_msg = (
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"If this is a buffer object rather "
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"than a string name, you must specify "
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"a format string"
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)
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filepath_or_buffer = _stringify_path(filepath_or_buffer)
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if not isinstance(filepath_or_buffer, str):
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raise ValueError(buffer_error_msg)
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fname = filepath_or_buffer.lower()
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if fname.endswith(".xpt"):
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format = "xport"
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elif fname.endswith(".sas7bdat"):
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format = "sas7bdat"
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else:
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raise ValueError("unable to infer format of SAS file")
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if format.lower() == "xport":
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from pandas.io.sas.sas_xport import XportReader
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reader = XportReader(
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filepath_or_buffer, index=index, encoding=encoding, chunksize=chunksize
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)
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elif format.lower() == "sas7bdat":
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from pandas.io.sas.sas7bdat import SAS7BDATReader
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reader = SAS7BDATReader(
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filepath_or_buffer, index=index, encoding=encoding, chunksize=chunksize
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)
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else:
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raise ValueError("unknown SAS format")
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if iterator or chunksize:
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return reader
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data = reader.read()
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reader.close()
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return data
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