polars.read_ods

polars.read_ods(
    source: FileSource,
    *,
    sheet_id: int | Sequence[int] | None = None,
    sheet_name: str | list[str] | tuple[str,
    ...] | None = None,
    has_header: bool = True,
    columns: Sequence[int] | Sequence[str] | None = None,
    schema_overrides: SchemaDict | None = None,
    infer_schema_length: int | None = 100,
    include_file_paths: str | None = None,
    drop_empty_rows: bool = True,
    drop_empty_cols: bool = True,
    raise_if_empty: bool = True,
) → DataFrame | dict[str, DataFrame]

Read OpenOffice (ODS) spreadsheet data into a DataFrame.

Parameters:

source

Path to a file or a file-like object (by “file-like object” we refer to objects that have a read() method, such as a file handler like the builtin open function, or a BytesIO instance). For file-like objects, the stream position may not be updated accordingly after reading.

sheet_id

Sheet number(s) to convert, starting from 1 (set 0 to load all worksheets as DataFrames) and return a {sheetname:frame,} dict. (Defaults to 1 if neither this nor sheet_name are specified). Can also take a sequence of sheet numbers.

sheet_name

Sheet name(s) to convert; cannot be used in conjunction with sheet_id. If more than one is given then a {sheetname:frame,} dict is returned.

has_header

Indicate if the first row of the table data is a header or not. If False, column names will be autogenerated in the following format: column_x, with x being an enumeration over every column in the dataset, starting at 1.

columns

Columns to read from the sheet; if not specified, all columns are read. Can be given as a sequence of column names or indices.

schema_overrides

Support type specification or override of one or more columns.

infer_schema_length

The maximum number of rows to scan for schema inference. If set to None, the entire dataset is scanned to determine the dtypes, which can slow parsing for large workbooks.

include_file_paths

Include the path of the source file(s) as a column with this name.

drop_empty_rows

Indicate whether to omit empty rows when reading data into the DataFrame.

drop_empty_cols

Indicate whether to omit empty columns (with no headers) when reading data into the DataFrame (note that empty column identification may vary depending on the underlying engine being used).

raise_if_empty

When there is no data in the sheet,`NoDataError` is raised. If this parameter is set to False, an empty DataFrame (with no columns) is returned instead.

Returns:

DataFrame, or a {sheetname: DataFrame, ...} dict if reading multiple sheets.

See also

read_excel

Examples

Read the “data” worksheet from an OpenOffice spreadsheet file into a DataFrame.

>>> pl.read_ods(
...     source="test.ods",
...     sheet_name="data",
... )  

If the correct dtypes can’t be determined, use the schema_overrides parameter to specify them, or increase the inference length with infer_schema_length.

>>> pl.read_ods(
...     source="test.ods",
...     sheet_id=3,
...     schema_overrides={"dt": pl.Date},
...     raise_if_empty=False,
... )