load_table#
- load_table(filename: str | Path, sep=None, reader=None, digits=4, space=4, title='', missing_data='', max_width=1e+100, index_name=None, legend='', column_templates=None, static_column_types=False, limit=None, format='simple', skip_inconsistent=False, **kwargs)#
- 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
output format when using str(Table)
- skip_inconsistent
skips rows that have different length to header row