tools/perf/cli_tools/flakiness_cli/analysis.py
def ResultsKey():
  """Create a DataFrame with information about result values."""
  return pandas.DataFrame.from_records([
      ('P', 'PASS', '-', 0.0),
      ('N', 'NO DATA', ' ', 0.0),
      ('X', 'SKIP', '~', 0.0),
      ('Q', 'FAIL', 'F', 1.0),
      ('Y', 'NOTRUN', '?', 0.1),
      ('L', 'FLAKY', '!', 0.5),
  ], columns=('code', 'result', 'char', 'badness'), index='code')
Create a DataFrame with information about result values.
Create a DataFrame with information about result values.
Create a DataFrame with information about result values .
def ResultsKey():
  return pandas.DataFrame.from_records([
      ('P', 'PASS', '-', 0.0),
      ('N', 'NO DATA', ' ', 0.0),
      ('X', 'SKIP', '~', 0.0),
      ('Q', 'FAIL', 'F', 1.0),
      ('Y', 'NOTRUN', '?', 0.1),
      ('L', 'FLAKY', '!', 0.5),
  ], columns=('code', 'result', 'char', 'badness'), index='code')
def ResultsKey ( ) : return pandas . DataFrame . from_records ( [ ( 'P' , 'PASS' , '-' , 0.0 ) , ( 'N' , 'NO DATA' , ' ' , 0.0 ) , ( 'X' , 'SKIP' , '~' , 0.0 ) , ( 'Q' , 'FAIL' , 'F' , 1.0 ) , ( 'Y' , 'NOTRUN' , '?' , 0.1 ) , ( 'L' , 'FLAKY' , '!' , 0.5 ) , ] , columns = ( 'code' , 'result' , 'char' , 'badness' ) , index = 'code' )
Create a DataFrame with information about result values.
Create a DataFrame with information about result values .
"""Create a DataFrame with information about result values."""