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# load_table

load_table(filename: str | Path, sep: str | None = None, reader: Callable | None = None, digits: int = 4, space: int = 4, title: str = '', missing_data: str = '', max_width: int = 10000000000000000159028911097599180468360808563945281389781327557747838772170381060813469985856815104, index_name: str | None = None, legend: str = '', column_templates: dict | None = None, static_column_types: bool = False, limit: int | None = None, format_name: str = 'simple', skip_inconsistent: bool = False, **kwargs) → Table
  Parameters:
    filename

      path to file containing a tabular data

    sep

      the delimiting character between columns

    reader

      a parser for reading filename. This approach assumes the first row returned by the reader will be the header row.

    static_column_types

      if True, and reader is None, identifies columns with a numeric/bool data types from the first non-header row. This assumes all subsequent entries in that column are of the same type. Default is False.

    digits

      floating point resolution

    space

      number of spaces between columns or a string

    title

      as implied

    missing_data

      character assigned if a row has no entry for a column

    max_width

      maximum column width for printing

    index_name

      column name with values to be used as row identifiers and keys for slicing. All column values must be unique.

    legend

      table legend

    column_templates

      dict of column headings or a function that will handle the formatting.

    limit

      exits after this many lines. Only applied for non pickled data file types.

    format_name

      output format when using str(Table)

    skip_inconsistent

      skips rows that have different length to header row