hloopy/plotters.py
def extracts_as_df(self):
        """After plotting, get all extracts in a dataframe with rows like:

        "/Path/to/hloop/data, label, avg_val, xcoords, ycoords, indices"

        If you want the actual extracts just grab them from 
        GridPlot.extract_instances, which is a dict keyed by fpaths and with
        lists of extacts as values.
        """
        from pandas import DataFrame
        d = defaultdict(list)
        for fpath, extracts in self.extract_instances.items():
            for e in extracts:
                d['fpath'].append(fpath)
                d['label'].append(e.label)
                d['avg_val'].append(e.avg_val)
                d['xcoords'].append(e.xcoords)
                d['ycoords'].append(e.ycoords)
                d['indices'].append(e.indices)
        return DataFrame(d)
After plotting, get all extracts in a dataframe with rows like:

        "/Path/to/hloop/data, label, avg_val, xcoords, ycoords, indices"

        If you want the actual extracts just grab them from 
        GridPlot.extract_instances, which is a dict keyed by fpaths and with
        lists of extacts as values.
        
After plotting, get all extracts in a dataframe with rows like:
"/Path/to/hloop/data, label, avg_val, xcoords, ycoords, indices"

If you want the actual extracts just grab them from
GridPlot.extract_instances, which is a dict keyed by fpaths and with
lists of extacts as values.
After plotting get all extracts in a dataframe with rows like : " / Path / to / hloop / data label avg_val xcoords ycoords indices " If you want the actual extracts just grab them from GridPlot . extract_instances which is a dict keyed by fpaths and with lists of extacts as values .
def extracts_as_df(self):
        from pandas import DataFrame
        d = defaultdict(list)
        for fpath, extracts in self.extract_instances.items():
            for e in extracts:
                d['fpath'].append(fpath)
                d['label'].append(e.label)
                d['avg_val'].append(e.avg_val)
                d['xcoords'].append(e.xcoords)
                d['ycoords'].append(e.ycoords)
                d['indices'].append(e.indices)
        return DataFrame(d)
def extracts_as_df ( self ) : from pandas import DataFrame d = defaultdict ( list ) for fpath , extracts in self . extract_instances . items ( ) : for e in extracts : d [ 'fpath' ] . append ( fpath ) d [ 'label' ] . append ( e . label ) d [ 'avg_val' ] . append ( e . avg_val ) d [ 'xcoords' ] . append ( e . xcoords ) d [ 'ycoords' ] . append ( e . ycoords ) d [ 'indices' ] . append ( e . indices ) return DataFrame ( d )
After plotting, get all extracts in a dataframe with rows like:
"/Path/to/hloop/data, label, avg_val, xcoords, ycoords, indices"
After plotting get all extracts in a dataframe with rows like : " / Path / to / hloop / data label avg_val xcoords ycoords indices "
"""After plotting, get all extracts in a dataframe with rows like:

        "/Path/to/hloop/data, label, avg_val, xcoords, ycoords, indices"

        If you want the actual extracts just grab them from 
        GridPlot.extract_instances, which is a dict keyed by fpaths and with
        lists of extacts as values.
        """
self