def summarize_df(dframe, dataset, groups=[]): """Calculate summary statistics.""" return { col: {SUMMARY: series_to_jsondict(summarize_series(dataset.is_dimension(col), data))} for col, data in dframe.iteritems() if summarizable(dframe, col, groups, dataset) }
def summarize_df(dframe, groups=[], dataset=None): """Calculate summary statistics.""" dtypes = dframe.dtypes return { col: {SUMMARY: series_to_jsondict(summarize_series(dtypes[col], data))} for col, data in dframe.iteritems() if summarizable(dframe, col, groups, dataset) }
def _check_dframe_is_subset(self, dframe1, dframe2): dframe2_rows = [self._reduce_precision(row) for row in BambooFrame(dframe2).to_jsondict()] for row in dframe1.iterrows(): dframe1_row = self._reduce_precision(series_to_jsondict(row[1])) self.assertTrue(dframe1_row in dframe2_rows, 'dframe1_row: %s\n\ndframe2_rows: %s' % ( dframe1_row, dframe2_rows))
def summarize_df(dframe, dataset, groups=[]): """Calculate summary statistics.""" return { col: { SUMMARY: series_to_jsondict( summarize_series(dataset.is_dimension(col), data)) } for col, data in dframe.iteritems() if summarizable(dframe, col, groups, dataset) }
def to_jsondict(self): """Return DataFrame as a list of dicts for each row.""" return [series_to_jsondict(series) for _, series in self.iterrows()]
def summarize_with_groups(dframe, groups, dataset): """Calculate summary statistics for group.""" return series_to_jsondict(dframe.groupby(groups).apply(summarize_df, dataset, groups))
def summarize_with_groups(dframe, groups, dataset): """Calculate summary statistics for group.""" return series_to_jsondict( dframe.groupby(groups).apply(summarize_df, dataset, groups))