``` python
import polars as pl
import polars.selectors as cs
from great_tables import GT, md
def create_bar(prop_fill: float, max_width: int, height: int) -> str:
"""Create divs to represent prop_fill as a bar."""
width = round(max_width * prop_fill, 2)
px_width = f"{width}px"
return f"""\
\
"""
df = pl.read_csv("./sports_earnings.csv")
res = (
df.with_columns(
(pl.col("Off-the-Field Earnings") / pl.col("Total Earnings")).alias("raw_perc"),
(pl.col("Sport").str.to_lowercase() + ".png").alias("icon"),
)
.head(9)
.with_columns(
pl.col("raw_perc")
.map_elements(lambda x: create_bar(x, max_width=75, height=20))
.alias("Off-the-Field Earnings Perc")
)
.select("Rank", "Name", "icon", "Sport", "Total Earnings", "Off-the-Field Earnings", "Off-the-Field Earnings Perc")
)
```
``` python
(
GT(res, rowname_col="Rank")
.tab_header("Highest Paid Athletes in 2023")
.tab_spanner("Earnings", cs.contains("Earnings"))
#.fmt_number(cs.starts_with("Total"), scale_by = 1/1_000_000, decimals=1)
.cols_label(**{
"Total Earnings": "Total $M",
"Off-the-Field Earnings": "Off field $M",
"Off-the-Field Earnings Perc": "Off field %"
})
.fmt_number(["Total Earnings", "Off-the-Field Earnings"], scale_by = 1/1_000_000, decimals=1)
.fmt_image("icon", path="./")
.tab_source_note(
md(
'
'
"Original table: [@LisaHornung_](https://twitter.com/LisaHornung_/status/1752981867769266231)"
" | Sports icons: [Firza Alamsyah](https://thenounproject.com/browse/collection-icon/sports-96427)"
" | Data: Forbes"
"
"
"
"
)
)
)
```