Add new method pyvcf.VcfFrame.duplicated

CHANGELOG.rst

@@ -6,6 +6,7 @@ Changelog
 
 * Update ``pyvcf`` submodule to accept "sites-only" VCF.
 * Add new method :meth:`pyvcf.VcfFrame.filter_gsa`.
+* Add new method :meth:`pyvcf.VcfFrame.duplicated`.
 
 0.35.0 (2022-07-12)
 -------------------

fuc/api/pyvcf.py

@@ -5945,6 +5945,73 @@ def rename(self, names, indicies=None):
  vf.df.columns = columns
  return vf
 
+ def duplicated(self, subset=None, keep='first'):
+ """
+ Return boolean Series denoting duplicate rows in VcfFrame.
+
+ This method essentially wraps the :meth:`pandas.DataFrame.duplicated`
+ method.
+
+ Considering certain columns is optional.
+
+ Parameters
+ ----------
+ subset : column label or sequence of labels, optional
+ Only consider certain columns for identifying duplicates, by
+ default use all of the columns.
+ keep : {'first', 'last', False}, default 'first'
+ Determines which duplicates (if any) to keep.
+
+ - ``first`` : Mark duplicates as ``True`` except for the first
+ occurrence.
+ - ``last`` : Mark duplicates as ``True`` except for the last
+ occurrence.
+ - False : Mark all duplicates as ``True``.
+
+ Returns
+ -------
+ Series
+ Boolean series for each duplicated rows.
+
+ Examples
+ --------
+
+ >>> from fuc import pyvcf
+ >>> data = {
+ ... 'CHROM': ['chr1', 'chr1', 'chr2', 'chr2'],
+ ... 'POS': [100, 100, 200, 200],
+ ... 'ID': ['.', '.', '.', '.'],
+ ... 'REF': ['A', 'A', 'C', 'C'],
+ ... 'ALT': ['C', 'T', 'G', 'G,A'],
+ ... 'QUAL': ['.', '.', '.', '.'],
+ ... 'FILTER': ['.', '.', '.', '.'],
+ ... 'INFO': ['.', '.', '.', '.'],
+ ... 'FORMAT': ['GT', 'GT', 'GT', 'GT'],
+ ... 'A': ['0/1', './.', '0/1', './.'],
+ ... 'B': ['./.', '0/1', './.', '1/2'],
+ ... }
+ >>> vf = pyvcf.VcfFrame.from_dict([], data)
+ >>> vf.df
+ CHROM POS ID REF ALT QUAL FILTER INFO FORMAT A B
+ 0 chr1 100 . A C . . . GT 0/1 ./.
+ 1 chr1 100 . A T . . . GT ./. 0/1
+ 2 chr2 200 . C G . . . GT 0/1 ./.
+ 3 chr2 200 . C G,A . . . GT ./. 1/2
+ >>> vf.duplicated(['CHROM', 'POS', 'REF'])
+ 0 False
+ 1 True
+ 2 False
+ 3 True
+ dtype: bool
+ >>> vf.duplicated(['CHROM', 'POS', 'REF'], keep='last')
+ 0 True
+ 1 False
+ 2 True
+ 3 False
+ dtype: bool
+ """
+ return self.df.duplicated(subset=subset, keep=keep)
+
  def drop_duplicates(self, subset=None, keep='first'):
  """
  Return VcfFrame with duplicate rows removed.