Grouped Tables

Group a table by a column for per-group aggregation with df_summarize.

df_group_by (T, col_name) — Function

Group a table by a column, returning a grouped table. The grouped table can then be passed to df_summarize to compute per-group statistics.

Examples

(%i1) T : df_table(["region", "revenue"],
                    [df_string_column(["N","S","N","S"]),
                     ndarray([10.0, 20.0, 30.0, 40.0])])$
(%i2) G : df_group_by(T, "region")$
(%i3) df_summarize(G, "total", lambda([revenue], np_sum(revenue)));
(%o3)              df_table: 2 rows x 2 cols

The result table has the group-key column plus one column per summary function.

See also: df_summarize, df_describe, df_grouped_table_p

df_grouped_table_p (x) — Function

Predicate: return true if x is a grouped table handle, false otherwise.

Examples

(%i1) T : df_table(["region", "revenue"],
                    [df_string_column(["N","S"]), ndarray([10.0, 20.0])])$
(%i2) G : df_group_by(T, "region")$
(%i3) df_grouped_table_p(G);
(%o3)                         true
(%i4) df_grouped_table_p(T);
(%o4)                        false

See also: df_group_by, df_table_p