import pandas as pd
from great_tables import GT, md
import gt_extras as gte
df = pd.DataFrame(
{
"Category": ["Points", "Rebounds", "Assists", "Blocks", "Steals"],
"Hart": [1051, 737, 453, 27, 119],
"Brunson": [1690, 187, 475, 8, 60],
"Bridges": [1444, 259, 306, 43, 75],
}
)
hart_header = gte.img_header(
label="Josh Hart",
img_url="https://a.espncdn.com/combiner/i?img=/i/headshots/nba/players/full/3062679.png",
)
brunson_header = gte.img_header(
label="Jalen Brunson",
img_url="https://a.espncdn.com/combiner/i?img=/i/headshots/nba/players/full/3934672.png",
)
bridges_header = gte.img_header(
label="Mikal Bridges",
img_url="https://a.espncdn.com/combiner/i?img=/i/headshots/nba/players/full/3147657.png",
)
(
GT(df, rowname_col="Category")
.tab_source_note(md("Images and data courtesy of [ESPN](https://www.espn.com)"))
.cols_label(
{
"Hart": hart_header,
"Brunson": brunson_header,
"Bridges": bridges_header,
}
)
)
Josh Hart
|
Jalen Brunson
|
Mikal Bridges
|
|
|---|---|---|---|
| Points | 1051 | 1690 | 1444 |
| Rebounds | 737 | 187 | 259 |
| Assists | 453 | 475 | 306 |
| Blocks | 27 | 8 | 43 |
| Steals | 119 | 60 | 75 |
| Images and data courtesy of ESPN | |||