gsolve.GravityObservations.from_excel

classmethod GravityObservations.from_excel(excel_file, sheet_name=None, ignore_unknown_fields=False, parse_split_datetime=True, mapper=None, **kwargs)

Create an object from an Excel file.

Parameters:

excel_filestr or PathLike

The path to the Excel file.

sheet_namestr, int, or list-like, optional

The name or index of the worksheet to read. If None, then try to use the default sheet name(s) defined in the class.

ignore_unknown_fieldsbool, default False

Only include known fields in the resulting object.

parse_split_datetime: bool, default False

If True, parse discrete year, month, day columns into a single datetime column and drop the original columns. Expected columns are [year, month, day, hour, minute, second, microsecond, nanosecond], with at least year, month, and day being required.

mapperdict-like or function, default None

Dict-like or function transformations to apply to column names before. Allows non-standard column/field names to be corrected prior to object creation. The simplest use case is to provide a dict of input_name, output_name pairs e.g. {'lat': 'latitude', ...}

kwargs

Additional keyword arguments to be passed to pandas.read_excel.

Returns:

GSolveTable

See also

pandas.read_excel

For available kwargs .

pandas.DataFrame.rename

For full details of mapper argument.