unique#
- astropy.table.unique(input_table, keys=None, silent=False, keep='first')[source]#
Return a new table with unique rows, sorted by
keys.- Parameters:
- input_tableastropy:table-like
- keys
strorlistofstr Name(s) of column(s) used to create unique rows. Default is to use all columns.
- silentbool
If
True, masked value column(s) are silently removed fromkeys. IfFalse, an exception is raised whenkeyscontains masked value column(s). Default isFalse.- keep{‘first’, ‘last’, ‘none’}
Whether to keep the first or last row for each set of duplicates. If ‘none’, all rows that are duplicate are removed, leaving only rows that are already unique in the input. Default is ‘first’.
- Returns:
Examples
>>> from astropy.table import unique, Table >>> import numpy as np >>> table = Table(data=[[1,2,3,2,3,3], ... [2,3,4,5,4,6], ... [3,4,5,6,7,8]], ... names=['col1', 'col2', 'col3'], ... dtype=[np.int32, np.int32, np.int32]) >>> table <Table length=6> col1 col2 col3 int32 int32 int32 ----- ----- ----- 1 2 3 2 3 4 3 4 5 2 5 6 3 4 7 3 6 8 >>> unique(table, keys='col1') <Table length=3> col1 col2 col3 int32 int32 int32 ----- ----- ----- 1 2 3 2 3 4 3 4 5 >>> unique(table, keys=['col1'], keep='last') <Table length=3> col1 col2 col3 int32 int32 int32 ----- ----- ----- 1 2 3 2 5 6 3 6 8 >>> unique(table, keys=['col1', 'col2']) <Table length=5> col1 col2 col3 int32 int32 int32 ----- ----- ----- 1 2 3 2 3 4 2 5 6 3 4 5 3 6 8 >>> unique(table, keys=['col1', 'col2'], keep='none') <Table length=4> col1 col2 col3 int32 int32 int32 ----- ----- ----- 1 2 3 2 3 4 2 5 6 3 6 8 >>> unique(table, keys=['col1'], keep='none') <Table length=1> col1 col2 col3 int32 int32 int32 ----- ----- ----- 1 2 3