Skip to content

Commit

Permalink
Backport PR #41266: API: make hide_columns and hide_index have a …
Browse files Browse the repository at this point in the history 
…consistent signature and function in `Styler` (#42041)

Co-authored-by: attack68 <24256554+attack68@users.noreply.github.com>
  • Loading branch information
@meeseeksmachine @attack68
meeseeksmachine and attack68 committed Jun 16, 2021
1 parent 05cfa0d commit 7488d8e
Show file tree
Hide file tree
Showing 3 changed files with 235 additions and 68 deletions.
173 changes: 154 additions & 19 deletions pandas/io/formats/style.py
View file
Expand Up @@ -31,7 +31,10 @@
from pandas.util._decorators import doc

import pandas as pd
from pandas import RangeIndex
from pandas import (
IndexSlice,
RangeIndex,
)
from pandas.api.types import is_list_like
from pandas.core import generic
import pandas.core.common as com
Expand Down Expand Up @@ -726,7 +729,7 @@ def to_latex(
self.data.columns = RangeIndex(stop=len(self.data.columns))
numeric_cols = self.data._get_numeric_data().columns.to_list()
self.data.columns = _original_columns
column_format = "" if self.hidden_index else "l" * self.data.index.nlevels
column_format = "" if self.hide_index_ else "l" * self.data.index.nlevels
for ci, _ in enumerate(self.data.columns):
if ci not in self.hidden_columns:
column_format += (
Expand Down Expand Up @@ -971,7 +974,7 @@ def _copy(self, deepcopy: bool = False) -> Styler:
)

styler.uuid = self.uuid
styler.hidden_index = self.hidden_index
styler.hide_index_ = self.hide_index_

if deepcopy:
styler.ctx = copy.deepcopy(self.ctx)
Expand Down Expand Up @@ -1010,7 +1013,7 @@ def clear(self) -> None:
self.cell_context.clear()
self._todo.clear()

self.hidden_index = False
self.hide_index_ = False
self.hidden_columns = []
# self.format and self.table_styles may be dependent on user
# input in self.__init__()
Expand Down Expand Up @@ -1141,7 +1144,7 @@ def _applymap(
) -> Styler:
func = partial(func, **kwargs) # applymap doesn't take kwargs?
if subset is None:
subset = pd.IndexSlice[:]
subset = IndexSlice[:]
subset = non_reducing_slice(subset)
result = self.data.loc[subset].applymap(func)
self._update_ctx(result)
Expand Down Expand Up @@ -1556,37 +1559,169 @@ def set_na_rep(self, na_rep: str) -> StylerRenderer:
self.na_rep = na_rep
return self.format(na_rep=na_rep, precision=self.precision)

def hide_index(self) -> Styler:
def hide_index(self, subset: Subset | None = None) -> Styler:
"""
Hide any indices from rendering.
Hide the entire index, or specific keys in the index from rendering.
This method has dual functionality:
- if ``subset`` is ``None`` then the entire index will be hidden whilst
displaying all data-rows.
- if a ``subset`` is given then those specific rows will be hidden whilst the
index itself remains visible.
.. versionchanged:: 1.3.0
Parameters
----------
subset : label, array-like, IndexSlice, optional
A valid 1d input or single key along the index axis within
`DataFrame.loc[<subset>, :]`, to limit ``data`` to *before* applying
the function.
Returns
-------
self : Styler
See Also
--------
Styler.hide_columns: Hide the entire column headers row, or specific columns.
Examples
--------
Simple application hiding specific rows:
>>> df = pd.DataFrame([[1,2], [3,4], [5,6]], index=["a", "b", "c"])
>>> df.style.hide_index(["a", "b"])
0 1
c 5 6
Hide the index and retain the data values:
>>> midx = pd.MultiIndex.from_product([["x", "y"], ["a", "b", "c"]])
>>> df = pd.DataFrame(np.random.randn(6,6), index=midx, columns=midx)
>>> df.style.format("{:.1f}").hide_index()
x y
a b c a b c
0.1 0.0 0.4 1.3 0.6 -1.4
0.7 1.0 1.3 1.5 -0.0 -0.2
1.4 -0.8 1.6 -0.2 -0.4 -0.3
0.4 1.0 -0.2 -0.8 -1.2 1.1
-0.6 1.2 1.8 1.9 0.3 0.3
0.8 0.5 -0.3 1.2 2.2 -0.8
Hide specific rows but retain the index:
>>> df.style.format("{:.1f}").hide_index(subset=(slice(None), ["a", "c"]))
x y
a b c a b c
x b 0.7 1.0 1.3 1.5 -0.0 -0.2
y b -0.6 1.2 1.8 1.9 0.3 0.3
Hide specific rows and the index:
>>> df.style.format("{:.1f}").hide_index(subset=(slice(None), ["a", "c"]))
... .hide_index()
x y
a b c a b c
0.7 1.0 1.3 1.5 -0.0 -0.2
-0.6 1.2 1.8 1.9 0.3 0.3
"""
self.hidden_index = True
if subset is None:
self.hide_index_ = True
else:
subset_ = IndexSlice[subset, :] # new var so mypy reads not Optional
subset = non_reducing_slice(subset_)
hide = self.data.loc[subset]
hrows = self.index.get_indexer_for(hide.index)
# error: Incompatible types in assignment (expression has type
# "ndarray", variable has type "Sequence[int]")
self.hidden_rows = hrows # type: ignore[assignment]
return self

def hide_columns(self, subset: Subset) -> Styler:
def hide_columns(self, subset: Subset | None = None) -> Styler:
"""
Hide columns from rendering.
Hide the column headers or specific keys in the columns from rendering.
This method has dual functionality:
- if ``subset`` is ``None`` then the entire column headers row will be hidden
whilst the data-values remain visible.
- if a ``subset`` is given then those specific columns, including the
data-values will be hidden, whilst the column headers row remains visible.
.. versionchanged:: 1.3.0
Parameters
----------
subset : label, array-like, IndexSlice
A valid 1d input or single key along the appropriate axis within
`DataFrame.loc[]`, to limit ``data`` to *before* applying the function.
subset : label, array-like, IndexSlice, optional
A valid 1d input or single key along the columns axis within
`DataFrame.loc[:, <subset>]`, to limit ``data`` to *before* applying
the function.
Returns
-------
self : Styler
See Also
--------
Styler.hide_index: Hide the entire index, or specific keys in the index.
Examples
--------
Simple application hiding specific columns:
>>> df = pd.DataFrame([[1, 2, 3], [4, 5, 6]], columns=["a", "b", "c"])
>>> df.style.hide_columns(["a", "b"])
c
0 3
1 6
Hide column headers and retain the data values:
>>> midx = pd.MultiIndex.from_product([["x", "y"], ["a", "b", "c"]])
>>> df = pd.DataFrame(np.random.randn(6,6), index=midx, columns=midx)
>>> df.style.format("{:.1f}").hide_columns()
x d 0.1 0.0 0.4 1.3 0.6 -1.4
e 0.7 1.0 1.3 1.5 -0.0 -0.2
f 1.4 -0.8 1.6 -0.2 -0.4 -0.3
y d 0.4 1.0 -0.2 -0.8 -1.2 1.1
e -0.6 1.2 1.8 1.9 0.3 0.3
f 0.8 0.5 -0.3 1.2 2.2 -0.8
Hide specific columns but retain the column headers:
>>> df.style.format("{:.1f}").hide_columns(subset=(slice(None), ["a", "c"]))
x y
b b
x a 0.0 0.6
b 1.0 -0.0
c -0.8 -0.4
y a 1.0 -1.2
b 1.2 0.3
c 0.5 2.2
Hide specific columns and the column headers:
>>> df.style.format("{:.1f}").hide_columns(subset=(slice(None), ["a", "c"]))
... .hide_columns()
x a 0.0 0.6
b 1.0 -0.0
c -0.8 -0.4
y a 1.0 -1.2
b 1.2 0.3
c 0.5 2.2
"""
subset = non_reducing_slice(subset)
hidden_df = self.data.loc[subset]
hcols = self.columns.get_indexer_for(hidden_df.columns)
# error: Incompatible types in assignment (expression has type
# "ndarray", variable has type "Sequence[int]")
self.hidden_columns = hcols # type: ignore[assignment]
if subset is None:
self.hide_columns_ = True
else:
subset_ = IndexSlice[:, subset] # new var so mypy reads not Optional
subset = non_reducing_slice(subset_)
hide = self.data.loc[subset]
hcols = self.columns.get_indexer_for(hide.columns)
# error: Incompatible types in assignment (expression has type
# "ndarray", variable has type "Sequence[int]")
self.hidden_columns = hcols # type: ignore[assignment]
return self

# -----------------------------------------------------------------------
Expand Down
97 changes: 54 additions & 43 deletions pandas/io/formats/style_render.py
View file
Expand Up @@ -98,7 +98,9 @@ def __init__(
self.cell_ids = cell_ids

# add rendering variables
self.hidden_index: bool = False
self.hide_index_: bool = False # bools for hiding col/row headers
self.hide_columns_: bool = False
self.hidden_rows: Sequence[int] = [] # sequence for specific hidden rows/cols
self.hidden_columns: Sequence[int] = []
self.ctx: DefaultDict[tuple[int, int], CSSList] = defaultdict(list)
self.cell_context: DefaultDict[tuple[int, int], str] = defaultdict(str)
Expand Down Expand Up @@ -298,55 +300,56 @@ def _translate_header(

head = []
# 1) column headers
for r in range(self.data.columns.nlevels):
index_blanks = [
_element("th", blank_class, blank_value, not self.hidden_index)
] * (self.data.index.nlevels - 1)

name = self.data.columns.names[r]
column_name = [
_element(
"th",
f"{blank_class if name is None else index_name_class} level{r}",
name if name is not None else blank_value,
not self.hidden_index,
)
]

if clabels:
column_headers = [
if not self.hide_columns_:
for r in range(self.data.columns.nlevels):
index_blanks = [
_element("th", blank_class, blank_value, not self.hide_index_)
] * (self.data.index.nlevels - 1)

name = self.data.columns.names[r]
column_name = [
_element(
"th",
f"{col_heading_class} level{r} col{c}",
value,
_is_visible(c, r, col_lengths),
attributes=(
f'colspan="{col_lengths.get((r, c), 0)}"'
if col_lengths.get((r, c), 0) > 1
else ""
),
f"{blank_class if name is None else index_name_class} level{r}",
name if name is not None else blank_value,
not self.hide_index_,
)
for c, value in enumerate(clabels[r])
]

if len(self.data.columns) > max_cols:
# add an extra column with `...` value to indicate trimming
column_headers.append(
if clabels:
column_headers = [
_element(
"th",
f"{col_heading_class} level{r} {trimmed_col_class}",
"...",
True,
attributes="",
f"{col_heading_class} level{r} col{c}",
value,
_is_visible(c, r, col_lengths),
attributes=(
f'colspan="{col_lengths.get((r, c), 0)}"'
if col_lengths.get((r, c), 0) > 1
else ""
),
)
)
head.append(index_blanks + column_name + column_headers)
for c, value in enumerate(clabels[r])
]

if len(self.data.columns) > max_cols:
# add an extra column with `...` value to indicate trimming
column_headers.append(
_element(
"th",
f"{col_heading_class} level{r} {trimmed_col_class}",
"...",
True,
attributes="",
)
)
head.append(index_blanks + column_name + column_headers)

# 2) index names
if (
self.data.index.names
and com.any_not_none(*self.data.index.names)
and not self.hidden_index
and not self.hide_index_
):
index_names = [
_element(
Expand Down Expand Up @@ -412,7 +415,9 @@ def _translate_body(
The associated HTML elements needed for template rendering.
"""
# for sparsifying a MultiIndex
idx_lengths = _get_level_lengths(self.index, sparsify_index, max_rows)
idx_lengths = _get_level_lengths(
self.index, sparsify_index, max_rows, self.hidden_rows
)

rlabels = self.data.index.tolist()[:max_rows] # slice to allow trimming
if self.data.index.nlevels == 1:
Expand All @@ -426,7 +431,7 @@ def _translate_body(
"th",
f"{row_heading_class} level{c} {trimmed_row_class}",
"...",
not self.hidden_index,
not self.hide_index_,
attributes="",
)
for c in range(self.data.index.nlevels)
Expand Down Expand Up @@ -463,7 +468,7 @@ def _translate_body(
"th",
f"{row_heading_class} level{c} row{r}",
value,
(_is_visible(r, c, idx_lengths) and not self.hidden_index),
(_is_visible(r, c, idx_lengths) and not self.hide_index_),
id=f"level{c}_row{r}",
attributes=(
f'rowspan="{idx_lengths.get((c, r), 0)}"'
Expand Down Expand Up @@ -497,7 +502,7 @@ def _translate_body(
"td",
f"{data_class} row{r} col{c}{cls}",
value,
(c not in self.hidden_columns),
(c not in self.hidden_columns and r not in self.hidden_rows),
attributes="",
display_value=self._display_funcs[(r, c)](value),
)
Expand Down Expand Up @@ -528,7 +533,7 @@ def _translate_latex(self, d: dict) -> None:
d["head"] = [[col for col in row if col["is_visible"]] for row in d["head"]]
body = []
for r, row in enumerate(d["body"]):
if self.hidden_index:
if self.hide_index_:
row_body_headers = []
else:
row_body_headers = [
Expand Down Expand Up @@ -843,7 +848,13 @@ def _get_level_lengths(
last_label = j
lengths[(i, last_label)] = 0
elif j not in hidden_elements:
lengths[(i, last_label)] += 1
if lengths[(i, last_label)] == 0:
# if the previous iteration was first-of-kind but hidden then offset
last_label = j
lengths[(i, last_label)] = 1
else:
# else add to previous iteration
lengths[(i, last_label)] += 1

non_zero_lengths = {
element: length for element, length in lengths.items() if length >= 1
Expand Down

0 comments on commit 7488d8e

Please sign in to comment.