Add a table stub, to emphasize row and group information.
GT.tab_stub(
rowname_col=None,
groupname_col=None,
)
Parameters
rowname_col: str | list[str] | None = None-
The column to use for row names. By default, no row names added. A list of columns creates a hierarchical stub: the last column holds the row names, and the columns before it are outer levels (outermost first), with repeated values merged across adjacent rows.
groupname_col: str | None = None-
The column to use for group names. By default no group names added.
Returns
GT-
The GT object is returned. This is the same object that the method is called on so that we can facilitate method chaining.
Examples
By default, all data is together in the body of the table.
from great_tables import GT, exibble
GT(exibble)
| num |
char |
fctr |
date |
time |
datetime |
currency |
row |
group |
| 0.1111 |
apricot |
one |
2015-01-15 |
13:35 |
2018-01-01 02:22 |
49.95 |
row_1 |
grp_a |
| 2.222 |
banana |
two |
2015-02-15 |
14:40 |
2018-02-02 14:33 |
17.95 |
row_2 |
grp_a |
| 33.33 |
coconut |
three |
2015-03-15 |
15:45 |
2018-03-03 03:44 |
1.39 |
row_3 |
grp_a |
| 444.4 |
durian |
four |
2015-04-15 |
16:50 |
2018-04-04 15:55 |
65100.0 |
row_4 |
grp_a |
| 5550.0 |
None |
five |
2015-05-15 |
17:55 |
2018-05-05 04:00 |
1325.81 |
row_5 |
grp_b |
| None |
fig |
six |
2015-06-15 |
None |
2018-06-06 16:11 |
13.255 |
row_6 |
grp_b |
| 777000.0 |
grapefruit |
seven |
None |
19:10 |
2018-07-07 05:22 |
None |
row_7 |
grp_b |
| 8880000.0 |
honeydew |
eight |
2015-08-15 |
20:20 |
None |
0.44 |
row_8 |
grp_b |
The table stub separates row names with a vertical line, and puts group names on their own line.
GT(exibble).tab_stub(rowname_col="row", groupname_col="group")
|
num |
char |
fctr |
date |
time |
datetime |
currency |
| grp_a |
| row_1 |
0.1111 |
apricot |
one |
2015-01-15 |
13:35 |
2018-01-01 02:22 |
49.95 |
| row_2 |
2.222 |
banana |
two |
2015-02-15 |
14:40 |
2018-02-02 14:33 |
17.95 |
| row_3 |
33.33 |
coconut |
three |
2015-03-15 |
15:45 |
2018-03-03 03:44 |
1.39 |
| row_4 |
444.4 |
durian |
four |
2015-04-15 |
16:50 |
2018-04-04 15:55 |
65100.0 |
| grp_b |
| row_5 |
5550.0 |
None |
five |
2015-05-15 |
17:55 |
2018-05-05 04:00 |
1325.81 |
| row_6 |
None |
fig |
six |
2015-06-15 |
None |
2018-06-06 16:11 |
13.255 |
| row_7 |
777000.0 |
grapefruit |
seven |
None |
19:10 |
2018-07-07 05:22 |
None |
| row_8 |
8880000.0 |
honeydew |
eight |
2015-08-15 |
20:20 |
None |
0.44 |
Passing a list of columns to rowname_col= creates a hierarchical stub. Here, the rows are labeled by "group" and then "row", and the repeated group values are merged.
GT(exibble[["group", "row", "num", "char"]]).tab_stub(rowname_col=["group", "row"])
|
num |
char |
| grp_a |
row_1 |
0.1111 |
apricot |
| row_2 |
2.222 |
banana |
| row_3 |
33.33 |
coconut |
| row_4 |
444.4 |
durian |
| grp_b |
row_5 |
5550.0 |
None |
| row_6 |
None |
fig |
| row_7 |
777000.0 |
grapefruit |
| row_8 |
8880000.0 |
honeydew |