Open starzar opened 1 week ago
@starzar , with Polars DataFrames, it’s often best to use Polars expressions for operations. There’s an example showing how to do this with a single column, but for multiple columns, we may need to loop through each to perform the desired operations. For instance:
import polars as pl
from great_tables import GT, loc, style
df = pl.DataFrame(
{
"A": [10, -5, 20, -15],
"B": [30.32234, 25.234234, -10.234234, 15.23423],
}
)
df_gt = GT(df)
for col in df.columns:
df_gt = df_gt.tab_style(
style=style.fill(
(pl.when(pl.col(col) > 0).then(pl.lit("green")).otherwise(pl.lit("red")))
),
locations=loc.body(columns=col),
)
df_gt.show()
html_output = df_gt.as_raw_html()
html_path = "secondTerminal.html"
with open(html_path, "w") as file:
file.write(html_output)
For required packages, if you’re using Jupyter Notebook/Lab, be sure to install great_tables[extra]
, ipykernel
, and polars
.
Thanks for the polars example @jrycw !
@starzar RE the .show()
method, can you post what import great_tables; great_tables.__version__
gives? And the full import error stacktrace, if you can produce? I'm trying to figure out what might cause that..
Prework
Question
How to iterate over multiple columns for common formatting on cells eg. converting all float values to int's, showing positive/negative numbers with green/red colors (Polars)?
fmt example for iterating over multiple columns does not work in this case .
Also GT.show() import raises an import error .How to resolve this?
ERROR:
CODE: