datascience.tables.Table.as_text

Table.as_text(max_rows=0, sep=' | ')

Format table as text

Args:

max_rows(int) The maximum number of rows to be present in the converted string of table. (Optional Argument) sep(str) The seperator which will appear in converted string between the columns. (Optional Argument)

Returns:

String form of the table

The table is just converted to a string with columns seperated by the seperator(argument- default(’ | ‘)) and rows seperated by ‘n’

Few examples of the as_text() method are as follows:

>>> table = Table().with_columns({'name': ['abc', 'xyz', 'uvw'], 'age': [12,14,20],'height': [5.5,6.0,5.9],})
>>> table
name | age  | height
abc  | 12   | 5.5
xyz  | 14   | 6
uvw  | 20   | 5.9

>>> table_astext = table.as_text()
>>> table_astext
'name | age  | height\nabc  | 12   | 5.5\nxyz  | 14   | 6\nuvw  | 20   | 5.9'

>>> type(table)
<class 'datascience.tables.Table'>

>>> type(table_astext)
<class 'str'>

>>> sizes = Table(['size', 'count']).with_rows([     ['small', 50],     ['medium', 100],     ['big', 50], ])
>>> sizes
size   | count
small  | 50
medium | 100
big    | 50

>>> sizes_astext = sizes.as_text()
>>> sizes_astext
'size   | count\nsmall  | 50\nmedium | 100\nbig    | 50'

>>> sizes_astext = sizes.as_text(1)
>>> sizes_astext
'size  | count\nsmall | 50\n... (2 rows omitted)'

>>> sizes_astext = sizes.as_text(2, ' - ')
>>> sizes_astext
'size   - count\nsmall  - 50\nmedium - 100\n... (1 rows omitted)'