neuroscout/populate/transform.py
def dummy(ee_df):
        """ Returns a dummy feature of 1s for each stimulus
            Args:
                ee_df - ExtractedEvents in pandas df format
        """
        dummy = ee_df.groupby('stimulus_id').apply(lambda x: 1).reset_index()
        return dummy.rename(columns={0: 'value'}).to_dict('index').values()
 Returns a dummy feature of 1s for each stimulus
            Args:
                ee_df - ExtractedEvents in pandas df format
        
Returns a dummy feature of 1s for each stimulus
Args:
ee_df - ExtractedEvents in pandas df format
Returns a dummy feature of 1s for each stimulus Args : ee_df - ExtractedEvents in pandas df format
def dummy(ee_df):
        dummy = ee_df.groupby('stimulus_id').apply(lambda x: 1).reset_index()
        return dummy.rename(columns={0: 'value'}).to_dict('index').values()
def dummy ( ee_df ) : dummy = ee_df . groupby ( 'stimulus_id' ) . apply ( lambda x : 1 ) . reset_index ( ) return dummy . rename ( columns = { 0 : 'value' } ) . to_dict ( 'index' ) . values ( )
Returns a dummy feature of 1s for each stimulus
Args:
ee_df - ExtractedEvents in pandas df format
Returns a dummy feature of 1s for each stimulus Args : ee_df - ExtractedEvents in pandas df format
""" Returns a dummy feature of 1s for each stimulus
            Args:
                ee_df - ExtractedEvents in pandas df format
        """
ee_df