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Implement GT.pipe()
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Implement GT.pipe()
#363
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1623719
Implement `GT.pipe()` and `GT.pipes()`
jrycw f9702db
Allow passing a list of functions to `GT.pipes()`
jrycw 7e4a167
Code review change
jrycw 3d7152d
Improve type hints for `GT.pipe()`
jrycw c4f4801
Merge branch 'main' into fix-353
machow 2dafcc7
tests: simplify .pipe test
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Original file line number | Diff line number | Diff line change |
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@@ -0,0 +1,100 @@ | ||
from __future__ import annotations | ||
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from typing import TYPE_CHECKING, Callable | ||
from typing_extensions import ParamSpec | ||
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if TYPE_CHECKING: | ||
from .gt import GT | ||
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P = ParamSpec("P") | ||
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def pipe(self: "GT", func: Callable[P, "GT"], *args: P.args, **kwargs: P.kwargs) -> "GT": | ||
""" | ||
Provide a structured way to chain a function for a GT object. | ||
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This function accepts a function that receives a GT object along with optional positional and | ||
keyword arguments, returning a GT object. This allows users to easily integrate a function | ||
into the chained API offered by **Great Tables**. | ||
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Parameters | ||
---------- | ||
func | ||
A function that receives a GT object along with optional positional and keyword arguments, | ||
returning a GT object. | ||
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*args | ||
Optional positional arguments to be passed to the function. | ||
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**kwargs | ||
Optional keyword arguments to be passed to the function. | ||
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Returns | ||
------- | ||
gt | ||
A GT object. | ||
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Examples: | ||
------ | ||
Let's use the `name`, `land_area_km2`, and `density_2021` columns of the `towny` dataset to | ||
create a table. First, we'll demonstrate using two consecutive calls to the `.tab_style()` | ||
method to highlight the maximum value of the `land_area_km2` column with `"lightgray"` and the | ||
maximum value of the `density_2021` column with `"lightblue"`. | ||
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```{python} | ||
import polars as pl | ||
from great_tables import GT, loc, style | ||
from great_tables.data import towny | ||
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towny_mini = pl.from_pandas(towny).head(10) | ||
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( | ||
GT( | ||
towny_mini[["name", "land_area_km2", "density_2021"]], | ||
rowname_col="name", | ||
) | ||
.tab_style( | ||
style=style.fill(color="lightgray"), | ||
locations=loc.body( | ||
columns="land_area_km2", | ||
rows=pl.col("land_area_km2").eq(pl.col("land_area_km2").max()), | ||
), | ||
) | ||
.tab_style( | ||
style=style.fill(color="lightblue"), | ||
locations=loc.body( | ||
columns="density_2021", | ||
rows=pl.col("density_2021").eq(pl.col("density_2021").max()), | ||
), | ||
) | ||
) | ||
``` | ||
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Next, we'll demonstrate how to achieve the same result using the `.pipe()` method to | ||
programmatically style each column. | ||
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```{python} | ||
columns = ["land_area_km2", "density_2021"] | ||
colors = ["lightgray", "lightblue"] | ||
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def tbl_style(gtbl: GT, columns: list[str], colors: list[str]) -> GT: | ||
for column, color in zip(columns, colors): | ||
gtbl = gtbl.tab_style( | ||
style=style.fill(color=color), | ||
locations=loc.body(columns=column, rows=pl.col(column).eq(pl.col(column).max())), | ||
) | ||
return gtbl | ||
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( | ||
GT( | ||
towny_mini[["name", "land_area_km2", "density_2021"]], | ||
rowname_col="name", | ||
).pipe(tbl_style, columns, colors) | ||
) | ||
``` | ||
""" | ||
return func(self, *args, **kwargs) |
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Original file line number | Diff line number | Diff line change |
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@@ -0,0 +1,17 @@ | ||
import polars as pl | ||
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from great_tables import GT | ||
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def test_pipe(): | ||
columns = ["x", "y"] | ||
label = "a spanner" | ||
df = pl.DataFrame({"x": [1, 2, 3], "y": [3, 2, 1]}) | ||
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def tab_spanner2(gt, label, columns): | ||
return gt.tab_spanner(label=label, columns=columns) | ||
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gt1 = GT(df).tab_spanner(label, columns=columns) | ||
gt2 = GT(df).pipe(tab_spanner2, label, columns=columns) | ||
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assert len(gt1._spanners) == len(gt2._spanners) |
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What about putting pipe in the helper functions section. @rich-iannone WDYT?
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I like it!