from __future__ import annotations
|
|
from collections import defaultdict
|
from functools import partial
|
import re
|
from typing import (
|
Any,
|
Callable,
|
DefaultDict,
|
Dict,
|
List,
|
Optional,
|
Sequence,
|
Tuple,
|
TypedDict,
|
Union,
|
)
|
from uuid import uuid4
|
|
import numpy as np
|
|
from pandas._config import get_option
|
|
from pandas._libs import lib
|
from pandas._typing import (
|
Axis,
|
Level,
|
)
|
from pandas.compat._optional import import_optional_dependency
|
|
from pandas.core.dtypes.common import (
|
is_complex,
|
is_float,
|
is_integer,
|
)
|
from pandas.core.dtypes.generic import ABCSeries
|
|
from pandas import (
|
DataFrame,
|
Index,
|
IndexSlice,
|
MultiIndex,
|
Series,
|
isna,
|
)
|
from pandas.api.types import is_list_like
|
import pandas.core.common as com
|
|
jinja2 = import_optional_dependency("jinja2", extra="DataFrame.style requires jinja2.")
|
from markupsafe import escape as escape_html # markupsafe is jinja2 dependency
|
|
BaseFormatter = Union[str, Callable]
|
ExtFormatter = Union[BaseFormatter, Dict[Any, Optional[BaseFormatter]]]
|
CSSPair = Tuple[str, Union[str, float]]
|
CSSList = List[CSSPair]
|
CSSProperties = Union[str, CSSList]
|
|
|
class CSSDict(TypedDict):
|
selector: str
|
props: CSSProperties
|
|
|
CSSStyles = List[CSSDict]
|
Subset = Union[slice, Sequence, Index]
|
|
|
class StylerRenderer:
|
"""
|
Base class to process rendering a Styler with a specified jinja2 template.
|
"""
|
|
loader = jinja2.PackageLoader("pandas", "io/formats/templates")
|
env = jinja2.Environment(loader=loader, trim_blocks=True)
|
template_html = env.get_template("html.tpl")
|
template_html_table = env.get_template("html_table.tpl")
|
template_html_style = env.get_template("html_style.tpl")
|
template_latex = env.get_template("latex.tpl")
|
template_string = env.get_template("string.tpl")
|
|
def __init__(
|
self,
|
data: DataFrame | Series,
|
uuid: str | None = None,
|
uuid_len: int = 5,
|
table_styles: CSSStyles | None = None,
|
table_attributes: str | None = None,
|
caption: str | tuple | list | None = None,
|
cell_ids: bool = True,
|
precision: int | None = None,
|
) -> None:
|
# validate ordered args
|
if isinstance(data, Series):
|
data = data.to_frame()
|
if not isinstance(data, DataFrame):
|
raise TypeError("``data`` must be a Series or DataFrame")
|
self.data: DataFrame = data
|
self.index: Index = data.index
|
self.columns: Index = data.columns
|
if not isinstance(uuid_len, int) or uuid_len < 0:
|
raise TypeError("``uuid_len`` must be an integer in range [0, 32].")
|
self.uuid = uuid or uuid4().hex[: min(32, uuid_len)]
|
self.uuid_len = len(self.uuid)
|
self.table_styles = table_styles
|
self.table_attributes = table_attributes
|
self.caption = caption
|
self.cell_ids = cell_ids
|
self.css = {
|
"row_heading": "row_heading",
|
"col_heading": "col_heading",
|
"index_name": "index_name",
|
"col": "col",
|
"row": "row",
|
"col_trim": "col_trim",
|
"row_trim": "row_trim",
|
"level": "level",
|
"data": "data",
|
"blank": "blank",
|
"foot": "foot",
|
}
|
self.concatenated: list[StylerRenderer] = []
|
# add rendering variables
|
self.hide_index_names: bool = False
|
self.hide_column_names: bool = False
|
self.hide_index_: list = [False] * self.index.nlevels
|
self.hide_columns_: list = [False] * self.columns.nlevels
|
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.ctx_index: DefaultDict[tuple[int, int], CSSList] = defaultdict(list)
|
self.ctx_columns: DefaultDict[tuple[int, int], CSSList] = defaultdict(list)
|
self.cell_context: DefaultDict[tuple[int, int], str] = defaultdict(str)
|
self._todo: list[tuple[Callable, tuple, dict]] = []
|
self.tooltips: Tooltips | None = None
|
precision = (
|
get_option("styler.format.precision") if precision is None else precision
|
)
|
self._display_funcs: DefaultDict[ # maps (row, col) -> format func
|
tuple[int, int], Callable[[Any], str]
|
] = defaultdict(lambda: partial(_default_formatter, precision=precision))
|
self._display_funcs_index: DefaultDict[ # maps (row, level) -> format func
|
tuple[int, int], Callable[[Any], str]
|
] = defaultdict(lambda: partial(_default_formatter, precision=precision))
|
self._display_funcs_columns: DefaultDict[ # maps (level, col) -> format func
|
tuple[int, int], Callable[[Any], str]
|
] = defaultdict(lambda: partial(_default_formatter, precision=precision))
|
|
def _render(
|
self,
|
sparse_index: bool,
|
sparse_columns: bool,
|
max_rows: int | None = None,
|
max_cols: int | None = None,
|
blank: str = "",
|
):
|
"""
|
Computes and applies styles and then generates the general render dicts.
|
|
Also extends the `ctx` and `ctx_index` attributes with those of concatenated
|
stylers for use within `_translate_latex`
|
"""
|
self._compute()
|
dxs = []
|
ctx_len = len(self.index)
|
for i, concatenated in enumerate(self.concatenated):
|
concatenated.hide_index_ = self.hide_index_
|
concatenated.hidden_columns = self.hidden_columns
|
foot = f"{self.css['foot']}{i}"
|
concatenated.css = {
|
**self.css,
|
"data": f"{foot}_data",
|
"row_heading": f"{foot}_row_heading",
|
"row": f"{foot}_row",
|
"foot": f"{foot}_foot",
|
}
|
dx = concatenated._render(
|
sparse_index, sparse_columns, max_rows, max_cols, blank
|
)
|
dxs.append(dx)
|
|
for (r, c), v in concatenated.ctx.items():
|
self.ctx[(r + ctx_len, c)] = v
|
for (r, c), v in concatenated.ctx_index.items():
|
self.ctx_index[(r + ctx_len, c)] = v
|
|
ctx_len += len(concatenated.index)
|
|
d = self._translate(
|
sparse_index, sparse_columns, max_rows, max_cols, blank, dxs
|
)
|
return d
|
|
def _render_html(
|
self,
|
sparse_index: bool,
|
sparse_columns: bool,
|
max_rows: int | None = None,
|
max_cols: int | None = None,
|
**kwargs,
|
) -> str:
|
"""
|
Renders the ``Styler`` including all applied styles to HTML.
|
Generates a dict with necessary kwargs passed to jinja2 template.
|
"""
|
d = self._render(sparse_index, sparse_columns, max_rows, max_cols, " ")
|
d.update(kwargs)
|
return self.template_html.render(
|
**d,
|
html_table_tpl=self.template_html_table,
|
html_style_tpl=self.template_html_style,
|
)
|
|
def _render_latex(
|
self, sparse_index: bool, sparse_columns: bool, clines: str | None, **kwargs
|
) -> str:
|
"""
|
Render a Styler in latex format
|
"""
|
d = self._render(sparse_index, sparse_columns, None, None)
|
self._translate_latex(d, clines=clines)
|
self.template_latex.globals["parse_wrap"] = _parse_latex_table_wrapping
|
self.template_latex.globals["parse_table"] = _parse_latex_table_styles
|
self.template_latex.globals["parse_cell"] = _parse_latex_cell_styles
|
self.template_latex.globals["parse_header"] = _parse_latex_header_span
|
d.update(kwargs)
|
return self.template_latex.render(**d)
|
|
def _render_string(
|
self,
|
sparse_index: bool,
|
sparse_columns: bool,
|
max_rows: int | None = None,
|
max_cols: int | None = None,
|
**kwargs,
|
) -> str:
|
"""
|
Render a Styler in string format
|
"""
|
d = self._render(sparse_index, sparse_columns, max_rows, max_cols)
|
d.update(kwargs)
|
return self.template_string.render(**d)
|
|
def _compute(self):
|
"""
|
Execute the style functions built up in `self._todo`.
|
|
Relies on the conventions that all style functions go through
|
.apply or .applymap. The append styles to apply as tuples of
|
|
(application method, *args, **kwargs)
|
"""
|
self.ctx.clear()
|
self.ctx_index.clear()
|
self.ctx_columns.clear()
|
r = self
|
for func, args, kwargs in self._todo:
|
r = func(self)(*args, **kwargs)
|
return r
|
|
def _translate(
|
self,
|
sparse_index: bool,
|
sparse_cols: bool,
|
max_rows: int | None = None,
|
max_cols: int | None = None,
|
blank: str = " ",
|
dxs: list[dict] | None = None,
|
):
|
"""
|
Process Styler data and settings into a dict for template rendering.
|
|
Convert data and settings from ``Styler`` attributes such as ``self.data``,
|
``self.tooltips`` including applying any methods in ``self._todo``.
|
|
Parameters
|
----------
|
sparse_index : bool
|
Whether to sparsify the index or print all hierarchical index elements.
|
Upstream defaults are typically to `pandas.options.styler.sparse.index`.
|
sparse_cols : bool
|
Whether to sparsify the columns or print all hierarchical column elements.
|
Upstream defaults are typically to `pandas.options.styler.sparse.columns`.
|
max_rows, max_cols : int, optional
|
Specific max rows and cols. max_elements always take precedence in render.
|
blank : str
|
Entry to top-left blank cells.
|
dxs : list[dict]
|
The render dicts of the concatenated Stylers.
|
|
Returns
|
-------
|
d : dict
|
The following structure: {uuid, table_styles, caption, head, body,
|
cellstyle, table_attributes}
|
"""
|
if dxs is None:
|
dxs = []
|
self.css["blank_value"] = blank
|
|
# construct render dict
|
d = {
|
"uuid": self.uuid,
|
"table_styles": format_table_styles(self.table_styles or []),
|
"caption": self.caption,
|
}
|
|
max_elements = get_option("styler.render.max_elements")
|
max_rows = max_rows if max_rows else get_option("styler.render.max_rows")
|
max_cols = max_cols if max_cols else get_option("styler.render.max_columns")
|
max_rows, max_cols = _get_trimming_maximums(
|
len(self.data.index),
|
len(self.data.columns),
|
max_elements,
|
max_rows,
|
max_cols,
|
)
|
|
self.cellstyle_map_columns: DefaultDict[
|
tuple[CSSPair, ...], list[str]
|
] = defaultdict(list)
|
head = self._translate_header(sparse_cols, max_cols)
|
d.update({"head": head})
|
|
# for sparsifying a MultiIndex and for use with latex clines
|
idx_lengths = _get_level_lengths(
|
self.index, sparse_index, max_rows, self.hidden_rows
|
)
|
d.update({"index_lengths": idx_lengths})
|
|
self.cellstyle_map: DefaultDict[tuple[CSSPair, ...], list[str]] = defaultdict(
|
list
|
)
|
self.cellstyle_map_index: DefaultDict[
|
tuple[CSSPair, ...], list[str]
|
] = defaultdict(list)
|
body: list = self._translate_body(idx_lengths, max_rows, max_cols)
|
d.update({"body": body})
|
|
ctx_maps = {
|
"cellstyle": "cellstyle_map",
|
"cellstyle_index": "cellstyle_map_index",
|
"cellstyle_columns": "cellstyle_map_columns",
|
} # add the cell_ids styles map to the render dictionary in right format
|
for k, attr in ctx_maps.items():
|
map = [
|
{"props": list(props), "selectors": selectors}
|
for props, selectors in getattr(self, attr).items()
|
]
|
d.update({k: map})
|
|
for dx in dxs: # self.concatenated is not empty
|
d["body"].extend(dx["body"]) # type: ignore[union-attr]
|
d["cellstyle"].extend(dx["cellstyle"]) # type: ignore[union-attr]
|
d["cellstyle_index"].extend( # type: ignore[union-attr]
|
dx["cellstyle_index"]
|
)
|
|
table_attr = self.table_attributes
|
if not get_option("styler.html.mathjax"):
|
table_attr = table_attr or ""
|
if 'class="' in table_attr:
|
table_attr = table_attr.replace('class="', 'class="tex2jax_ignore ')
|
else:
|
table_attr += ' class="tex2jax_ignore"'
|
d.update({"table_attributes": table_attr})
|
|
if self.tooltips:
|
d = self.tooltips._translate(self, d)
|
|
return d
|
|
def _translate_header(self, sparsify_cols: bool, max_cols: int):
|
"""
|
Build each <tr> within table <head> as a list
|
|
Using the structure:
|
+----------------------------+---------------+---------------------------+
|
| index_blanks ... | column_name_0 | column_headers (level_0) |
|
1) | .. | .. | .. |
|
| index_blanks ... | column_name_n | column_headers (level_n) |
|
+----------------------------+---------------+---------------------------+
|
2) | index_names (level_0 to level_n) ... | column_blanks ... |
|
+----------------------------+---------------+---------------------------+
|
|
Parameters
|
----------
|
sparsify_cols : bool
|
Whether column_headers section will add colspan attributes (>1) to elements.
|
max_cols : int
|
Maximum number of columns to render. If exceeded will contain `...` filler.
|
|
Returns
|
-------
|
head : list
|
The associated HTML elements needed for template rendering.
|
"""
|
# for sparsifying a MultiIndex
|
col_lengths = _get_level_lengths(
|
self.columns, sparsify_cols, max_cols, self.hidden_columns
|
)
|
|
clabels = self.data.columns.tolist()
|
if self.data.columns.nlevels == 1:
|
clabels = [[x] for x in clabels]
|
clabels = list(zip(*clabels))
|
|
head = []
|
# 1) column headers
|
for r, hide in enumerate(self.hide_columns_):
|
if hide or not clabels:
|
continue
|
|
header_row = self._generate_col_header_row(
|
(r, clabels), max_cols, col_lengths
|
)
|
head.append(header_row)
|
|
# 2) index names
|
if (
|
self.data.index.names
|
and com.any_not_none(*self.data.index.names)
|
and not all(self.hide_index_)
|
and not self.hide_index_names
|
):
|
index_names_row = self._generate_index_names_row(
|
clabels, max_cols, col_lengths
|
)
|
head.append(index_names_row)
|
|
return head
|
|
def _generate_col_header_row(self, iter: tuple, max_cols: int, col_lengths: dict):
|
"""
|
Generate the row containing column headers:
|
|
+----------------------------+---------------+---------------------------+
|
| index_blanks ... | column_name_i | column_headers (level_i) |
|
+----------------------------+---------------+---------------------------+
|
|
Parameters
|
----------
|
iter : tuple
|
Looping variables from outer scope
|
max_cols : int
|
Permissible number of columns
|
col_lengths :
|
c
|
|
Returns
|
-------
|
list of elements
|
"""
|
|
r, clabels = iter
|
|
# number of index blanks is governed by number of hidden index levels
|
index_blanks = [
|
_element("th", self.css["blank"], self.css["blank_value"], True)
|
] * (self.index.nlevels - sum(self.hide_index_) - 1)
|
|
name = self.data.columns.names[r]
|
column_name = [
|
_element(
|
"th",
|
(
|
f"{self.css['blank']} {self.css['level']}{r}"
|
if name is None
|
else f"{self.css['index_name']} {self.css['level']}{r}"
|
),
|
name
|
if (name is not None and not self.hide_column_names)
|
else self.css["blank_value"],
|
not all(self.hide_index_),
|
)
|
]
|
|
column_headers: list = []
|
visible_col_count: int = 0
|
for c, value in enumerate(clabels[r]):
|
header_element_visible = _is_visible(c, r, col_lengths)
|
if header_element_visible:
|
visible_col_count += col_lengths.get((r, c), 0)
|
if self._check_trim(
|
visible_col_count,
|
max_cols,
|
column_headers,
|
"th",
|
f"{self.css['col_heading']} {self.css['level']}{r} "
|
f"{self.css['col_trim']}",
|
):
|
break
|
|
header_element = _element(
|
"th",
|
(
|
f"{self.css['col_heading']} {self.css['level']}{r} "
|
f"{self.css['col']}{c}"
|
),
|
value,
|
header_element_visible,
|
display_value=self._display_funcs_columns[(r, c)](value),
|
attributes=(
|
f'colspan="{col_lengths.get((r, c), 0)}"'
|
if col_lengths.get((r, c), 0) > 1
|
else ""
|
),
|
)
|
|
if self.cell_ids:
|
header_element["id"] = f"{self.css['level']}{r}_{self.css['col']}{c}"
|
if (
|
header_element_visible
|
and (r, c) in self.ctx_columns
|
and self.ctx_columns[r, c]
|
):
|
header_element["id"] = f"{self.css['level']}{r}_{self.css['col']}{c}"
|
self.cellstyle_map_columns[tuple(self.ctx_columns[r, c])].append(
|
f"{self.css['level']}{r}_{self.css['col']}{c}"
|
)
|
|
column_headers.append(header_element)
|
|
return index_blanks + column_name + column_headers
|
|
def _generate_index_names_row(self, iter: tuple, max_cols: int, col_lengths: dict):
|
"""
|
Generate the row containing index names
|
|
+----------------------------+---------------+---------------------------+
|
| index_names (level_0 to level_n) ... | column_blanks ... |
|
+----------------------------+---------------+---------------------------+
|
|
Parameters
|
----------
|
iter : tuple
|
Looping variables from outer scope
|
max_cols : int
|
Permissible number of columns
|
|
Returns
|
-------
|
list of elements
|
"""
|
|
clabels = iter
|
|
index_names = [
|
_element(
|
"th",
|
f"{self.css['index_name']} {self.css['level']}{c}",
|
self.css["blank_value"] if name is None else name,
|
not self.hide_index_[c],
|
)
|
for c, name in enumerate(self.data.index.names)
|
]
|
|
column_blanks: list = []
|
visible_col_count: int = 0
|
if clabels:
|
last_level = self.columns.nlevels - 1 # use last level since never sparsed
|
for c, value in enumerate(clabels[last_level]):
|
header_element_visible = _is_visible(c, last_level, col_lengths)
|
if header_element_visible:
|
visible_col_count += 1
|
if self._check_trim(
|
visible_col_count,
|
max_cols,
|
column_blanks,
|
"th",
|
f"{self.css['blank']} {self.css['col']}{c} {self.css['col_trim']}",
|
self.css["blank_value"],
|
):
|
break
|
|
column_blanks.append(
|
_element(
|
"th",
|
f"{self.css['blank']} {self.css['col']}{c}",
|
self.css["blank_value"],
|
c not in self.hidden_columns,
|
)
|
)
|
|
return index_names + column_blanks
|
|
def _translate_body(self, idx_lengths: dict, max_rows: int, max_cols: int):
|
"""
|
Build each <tr> within table <body> as a list
|
|
Use the following structure:
|
+--------------------------------------------+---------------------------+
|
| index_header_0 ... index_header_n | data_by_column ... |
|
+--------------------------------------------+---------------------------+
|
|
Also add elements to the cellstyle_map for more efficient grouped elements in
|
<style></style> block
|
|
Parameters
|
----------
|
sparsify_index : bool
|
Whether index_headers section will add rowspan attributes (>1) to elements.
|
|
Returns
|
-------
|
body : list
|
The associated HTML elements needed for template rendering.
|
"""
|
rlabels = self.data.index.tolist()
|
if not isinstance(self.data.index, MultiIndex):
|
rlabels = [[x] for x in rlabels]
|
|
body: list = []
|
visible_row_count: int = 0
|
for r, row_tup in [
|
z for z in enumerate(self.data.itertuples()) if z[0] not in self.hidden_rows
|
]:
|
visible_row_count += 1
|
if self._check_trim(
|
visible_row_count,
|
max_rows,
|
body,
|
"row",
|
):
|
break
|
|
body_row = self._generate_body_row(
|
(r, row_tup, rlabels), max_cols, idx_lengths
|
)
|
body.append(body_row)
|
return body
|
|
def _check_trim(
|
self,
|
count: int,
|
max: int,
|
obj: list,
|
element: str,
|
css: str | None = None,
|
value: str = "...",
|
) -> bool:
|
"""
|
Indicates whether to break render loops and append a trimming indicator
|
|
Parameters
|
----------
|
count : int
|
The loop count of previous visible items.
|
max : int
|
The allowable rendered items in the loop.
|
obj : list
|
The current render collection of the rendered items.
|
element : str
|
The type of element to append in the case a trimming indicator is needed.
|
css : str, optional
|
The css to add to the trimming indicator element.
|
value : str, optional
|
The value of the elements display if necessary.
|
|
Returns
|
-------
|
result : bool
|
Whether a trimming element was required and appended.
|
"""
|
if count > max:
|
if element == "row":
|
obj.append(self._generate_trimmed_row(max))
|
else:
|
obj.append(_element(element, css, value, True, attributes=""))
|
return True
|
return False
|
|
def _generate_trimmed_row(self, max_cols: int) -> list:
|
"""
|
When a render has too many rows we generate a trimming row containing "..."
|
|
Parameters
|
----------
|
max_cols : int
|
Number of permissible columns
|
|
Returns
|
-------
|
list of elements
|
"""
|
index_headers = [
|
_element(
|
"th",
|
(
|
f"{self.css['row_heading']} {self.css['level']}{c} "
|
f"{self.css['row_trim']}"
|
),
|
"...",
|
not self.hide_index_[c],
|
attributes="",
|
)
|
for c in range(self.data.index.nlevels)
|
]
|
|
data: list = []
|
visible_col_count: int = 0
|
for c, _ in enumerate(self.columns):
|
data_element_visible = c not in self.hidden_columns
|
if data_element_visible:
|
visible_col_count += 1
|
if self._check_trim(
|
visible_col_count,
|
max_cols,
|
data,
|
"td",
|
f"{self.css['data']} {self.css['row_trim']} {self.css['col_trim']}",
|
):
|
break
|
|
data.append(
|
_element(
|
"td",
|
f"{self.css['data']} {self.css['col']}{c} {self.css['row_trim']}",
|
"...",
|
data_element_visible,
|
attributes="",
|
)
|
)
|
|
return index_headers + data
|
|
def _generate_body_row(
|
self,
|
iter: tuple,
|
max_cols: int,
|
idx_lengths: dict,
|
):
|
"""
|
Generate a regular row for the body section of appropriate format.
|
|
+--------------------------------------------+---------------------------+
|
| index_header_0 ... index_header_n | data_by_column ... |
|
+--------------------------------------------+---------------------------+
|
|
Parameters
|
----------
|
iter : tuple
|
Iterable from outer scope: row number, row data tuple, row index labels.
|
max_cols : int
|
Number of permissible columns.
|
idx_lengths : dict
|
A map of the sparsification structure of the index
|
|
Returns
|
-------
|
list of elements
|
"""
|
r, row_tup, rlabels = iter
|
|
index_headers = []
|
for c, value in enumerate(rlabels[r]):
|
header_element_visible = (
|
_is_visible(r, c, idx_lengths) and not self.hide_index_[c]
|
)
|
header_element = _element(
|
"th",
|
(
|
f"{self.css['row_heading']} {self.css['level']}{c} "
|
f"{self.css['row']}{r}"
|
),
|
value,
|
header_element_visible,
|
display_value=self._display_funcs_index[(r, c)](value),
|
attributes=(
|
f'rowspan="{idx_lengths.get((c, r), 0)}"'
|
if idx_lengths.get((c, r), 0) > 1
|
else ""
|
),
|
)
|
|
if self.cell_ids:
|
header_element[
|
"id"
|
] = f"{self.css['level']}{c}_{self.css['row']}{r}" # id is given
|
if (
|
header_element_visible
|
and (r, c) in self.ctx_index
|
and self.ctx_index[r, c]
|
):
|
# always add id if a style is specified
|
header_element["id"] = f"{self.css['level']}{c}_{self.css['row']}{r}"
|
self.cellstyle_map_index[tuple(self.ctx_index[r, c])].append(
|
f"{self.css['level']}{c}_{self.css['row']}{r}"
|
)
|
|
index_headers.append(header_element)
|
|
data: list = []
|
visible_col_count: int = 0
|
for c, value in enumerate(row_tup[1:]):
|
data_element_visible = (
|
c not in self.hidden_columns and r not in self.hidden_rows
|
)
|
if data_element_visible:
|
visible_col_count += 1
|
if self._check_trim(
|
visible_col_count,
|
max_cols,
|
data,
|
"td",
|
f"{self.css['data']} {self.css['row']}{r} {self.css['col_trim']}",
|
):
|
break
|
|
# add custom classes from cell context
|
cls = ""
|
if (r, c) in self.cell_context:
|
cls = " " + self.cell_context[r, c]
|
|
data_element = _element(
|
"td",
|
(
|
f"{self.css['data']} {self.css['row']}{r} "
|
f"{self.css['col']}{c}{cls}"
|
),
|
value,
|
data_element_visible,
|
attributes="",
|
display_value=self._display_funcs[(r, c)](value),
|
)
|
|
if self.cell_ids:
|
data_element["id"] = f"{self.css['row']}{r}_{self.css['col']}{c}"
|
if data_element_visible and (r, c) in self.ctx and self.ctx[r, c]:
|
# always add id if needed due to specified style
|
data_element["id"] = f"{self.css['row']}{r}_{self.css['col']}{c}"
|
self.cellstyle_map[tuple(self.ctx[r, c])].append(
|
f"{self.css['row']}{r}_{self.css['col']}{c}"
|
)
|
|
data.append(data_element)
|
|
return index_headers + data
|
|
def _translate_latex(self, d: dict, clines: str | None) -> None:
|
r"""
|
Post-process the default render dict for the LaTeX template format.
|
|
Processing items included are:
|
- Remove hidden columns from the non-headers part of the body.
|
- Place cellstyles directly in td cells rather than use cellstyle_map.
|
- Remove hidden indexes or reinsert missing th elements if part of multiindex
|
or multirow sparsification (so that \multirow and \multicol work correctly).
|
"""
|
index_levels = self.index.nlevels
|
visible_index_level_n = index_levels - sum(self.hide_index_)
|
d["head"] = [
|
[
|
{**col, "cellstyle": self.ctx_columns[r, c - visible_index_level_n]}
|
for c, col in enumerate(row)
|
if col["is_visible"]
|
]
|
for r, row in enumerate(d["head"])
|
]
|
|
def _concatenated_visible_rows(obj, n, row_indices):
|
"""
|
Extract all visible row indices recursively from concatenated stylers.
|
"""
|
row_indices.extend(
|
[r + n for r in range(len(obj.index)) if r not in obj.hidden_rows]
|
)
|
n += len(obj.index)
|
for concatenated in obj.concatenated:
|
n = _concatenated_visible_rows(concatenated, n, row_indices)
|
return n
|
|
def concatenated_visible_rows(obj):
|
row_indices: list[int] = []
|
_concatenated_visible_rows(obj, 0, row_indices)
|
# TODO try to consolidate the concat visible rows
|
# methods to a single function / recursion for simplicity
|
return row_indices
|
|
body = []
|
for r, row in zip(concatenated_visible_rows(self), d["body"]):
|
# note: cannot enumerate d["body"] because rows were dropped if hidden
|
# during _translate_body so must zip to acquire the true r-index associated
|
# with the ctx obj which contains the cell styles.
|
if all(self.hide_index_):
|
row_body_headers = []
|
else:
|
row_body_headers = [
|
{
|
**col,
|
"display_value": col["display_value"]
|
if col["is_visible"]
|
else "",
|
"cellstyle": self.ctx_index[r, c],
|
}
|
for c, col in enumerate(row[:index_levels])
|
if (col["type"] == "th" and not self.hide_index_[c])
|
]
|
|
row_body_cells = [
|
{**col, "cellstyle": self.ctx[r, c]}
|
for c, col in enumerate(row[index_levels:])
|
if (col["is_visible"] and col["type"] == "td")
|
]
|
|
body.append(row_body_headers + row_body_cells)
|
d["body"] = body
|
|
# clines are determined from info on index_lengths and hidden_rows and input
|
# to a dict defining which row clines should be added in the template.
|
if clines not in [
|
None,
|
"all;data",
|
"all;index",
|
"skip-last;data",
|
"skip-last;index",
|
]:
|
raise ValueError(
|
f"`clines` value of {clines} is invalid. Should either be None or one "
|
f"of 'all;data', 'all;index', 'skip-last;data', 'skip-last;index'."
|
)
|
if clines is not None:
|
data_len = len(row_body_cells) if "data" in clines and d["body"] else 0
|
|
d["clines"] = defaultdict(list)
|
visible_row_indexes: list[int] = [
|
r for r in range(len(self.data.index)) if r not in self.hidden_rows
|
]
|
visible_index_levels: list[int] = [
|
i for i in range(index_levels) if not self.hide_index_[i]
|
]
|
for rn, r in enumerate(visible_row_indexes):
|
for lvln, lvl in enumerate(visible_index_levels):
|
if lvl == index_levels - 1 and "skip-last" in clines:
|
continue
|
idx_len = d["index_lengths"].get((lvl, r), None)
|
if idx_len is not None: # i.e. not a sparsified entry
|
d["clines"][rn + idx_len].append(
|
f"\\cline{{{lvln+1}-{len(visible_index_levels)+data_len}}}"
|
)
|
|
def format(
|
self,
|
formatter: ExtFormatter | None = None,
|
subset: Subset | None = None,
|
na_rep: str | None = None,
|
precision: int | None = None,
|
decimal: str = ".",
|
thousands: str | None = None,
|
escape: str | None = None,
|
hyperlinks: str | None = None,
|
) -> StylerRenderer:
|
r"""
|
Format the text display value of cells.
|
|
Parameters
|
----------
|
formatter : str, callable, dict or None
|
Object to define how values are displayed. See notes.
|
subset : label, array-like, IndexSlice, optional
|
A valid 2d input to `DataFrame.loc[<subset>]`, or, in the case of a 1d input
|
or single key, to `DataFrame.loc[:, <subset>]` where the columns are
|
prioritised, to limit ``data`` to *before* applying the function.
|
na_rep : str, optional
|
Representation for missing values.
|
If ``na_rep`` is None, no special formatting is applied.
|
precision : int, optional
|
Floating point precision to use for display purposes, if not determined by
|
the specified ``formatter``.
|
|
.. versionadded:: 1.3.0
|
|
decimal : str, default "."
|
Character used as decimal separator for floats, complex and integers.
|
|
.. versionadded:: 1.3.0
|
|
thousands : str, optional, default None
|
Character used as thousands separator for floats, complex and integers.
|
|
.. versionadded:: 1.3.0
|
|
escape : str, optional
|
Use 'html' to replace the characters ``&``, ``<``, ``>``, ``'``, and ``"``
|
in cell display string with HTML-safe sequences.
|
Use 'latex' to replace the characters ``&``, ``%``, ``$``, ``#``, ``_``,
|
``{``, ``}``, ``~``, ``^``, and ``\`` in the cell display string with
|
LaTeX-safe sequences.
|
Escaping is done before ``formatter``.
|
|
.. versionadded:: 1.3.0
|
|
hyperlinks : {"html", "latex"}, optional
|
Convert string patterns containing https://, http://, ftp:// or www. to
|
HTML <a> tags as clickable URL hyperlinks if "html", or LaTeX \href
|
commands if "latex".
|
|
.. versionadded:: 1.4.0
|
|
Returns
|
-------
|
Styler
|
|
See Also
|
--------
|
Styler.format_index: Format the text display value of index labels.
|
|
Notes
|
-----
|
This method assigns a formatting function, ``formatter``, to each cell in the
|
DataFrame. If ``formatter`` is ``None``, then the default formatter is used.
|
If a callable then that function should take a data value as input and return
|
a displayable representation, such as a string. If ``formatter`` is
|
given as a string this is assumed to be a valid Python format specification
|
and is wrapped to a callable as ``string.format(x)``. If a ``dict`` is given,
|
keys should correspond to column names, and values should be string or
|
callable, as above.
|
|
The default formatter currently expresses floats and complex numbers with the
|
pandas display precision unless using the ``precision`` argument here. The
|
default formatter does not adjust the representation of missing values unless
|
the ``na_rep`` argument is used.
|
|
The ``subset`` argument defines which region to apply the formatting function
|
to. If the ``formatter`` argument is given in dict form but does not include
|
all columns within the subset then these columns will have the default formatter
|
applied. Any columns in the formatter dict excluded from the subset will
|
be ignored.
|
|
When using a ``formatter`` string the dtypes must be compatible, otherwise a
|
`ValueError` will be raised.
|
|
When instantiating a Styler, default formatting can be applied be setting the
|
``pandas.options``:
|
|
- ``styler.format.formatter``: default None.
|
- ``styler.format.na_rep``: default None.
|
- ``styler.format.precision``: default 6.
|
- ``styler.format.decimal``: default ".".
|
- ``styler.format.thousands``: default None.
|
- ``styler.format.escape``: default None.
|
|
.. warning::
|
`Styler.format` is ignored when using the output format `Styler.to_excel`,
|
since Excel and Python have inherrently different formatting structures.
|
However, it is possible to use the `number-format` pseudo CSS attribute
|
to force Excel permissible formatting. See examples.
|
|
Examples
|
--------
|
Using ``na_rep`` and ``precision`` with the default ``formatter``
|
|
>>> df = pd.DataFrame([[np.nan, 1.0, 'A'], [2.0, np.nan, 3.0]])
|
>>> df.style.format(na_rep='MISS', precision=3) # doctest: +SKIP
|
0 1 2
|
0 MISS 1.000 A
|
1 2.000 MISS 3.000
|
|
Using a ``formatter`` specification on consistent column dtypes
|
|
>>> df.style.format('{:.2f}', na_rep='MISS', subset=[0,1]) # doctest: +SKIP
|
0 1 2
|
0 MISS 1.00 A
|
1 2.00 MISS 3.000000
|
|
Using the default ``formatter`` for unspecified columns
|
|
>>> df.style.format({0: '{:.2f}', 1: '£ {:.1f}'}, na_rep='MISS', precision=1)
|
... # doctest: +SKIP
|
0 1 2
|
0 MISS £ 1.0 A
|
1 2.00 MISS 3.0
|
|
Multiple ``na_rep`` or ``precision`` specifications under the default
|
``formatter``.
|
|
>>> (df.style.format(na_rep='MISS', precision=1, subset=[0])
|
... .format(na_rep='PASS', precision=2, subset=[1, 2])) # doctest: +SKIP
|
0 1 2
|
0 MISS 1.00 A
|
1 2.0 PASS 3.00
|
|
Using a callable ``formatter`` function.
|
|
>>> func = lambda s: 'STRING' if isinstance(s, str) else 'FLOAT'
|
>>> df.style.format({0: '{:.1f}', 2: func}, precision=4, na_rep='MISS')
|
... # doctest: +SKIP
|
0 1 2
|
0 MISS 1.0000 STRING
|
1 2.0 MISS FLOAT
|
|
Using a ``formatter`` with HTML ``escape`` and ``na_rep``.
|
|
>>> df = pd.DataFrame([['<div></div>', '"A&B"', None]])
|
>>> s = df.style.format(
|
... '<a href="a.com/{0}">{0}</a>', escape="html", na_rep="NA"
|
... )
|
>>> s.to_html() # doctest: +SKIP
|
...
|
<td .. ><a href="a.com/<div></div>"><div></div></a></td>
|
<td .. ><a href="a.com/"A&B"">"A&B"</a></td>
|
<td .. >NA</td>
|
...
|
|
Using a ``formatter`` with LaTeX ``escape``.
|
|
>>> df = pd.DataFrame([["123"], ["~ ^"], ["$%#"]])
|
>>> df.style.format("\\textbf{{{}}}", escape="latex").to_latex()
|
... # doctest: +SKIP
|
\begin{tabular}{ll}
|
{} & {0} \\
|
0 & \textbf{123} \\
|
1 & \textbf{\textasciitilde \space \textasciicircum } \\
|
2 & \textbf{\$\%\#} \\
|
\end{tabular}
|
|
Pandas defines a `number-format` pseudo CSS attribute instead of the `.format`
|
method to create `to_excel` permissible formatting. Note that semi-colons are
|
CSS protected characters but used as separators in Excel's format string.
|
Replace semi-colons with the section separator character (ASCII-245) when
|
defining the formatting here.
|
|
>>> df = pd.DataFrame({"A": [1, 0, -1]})
|
>>> pseudo_css = "number-format: 0§[Red](0)§-§@;"
|
>>> filename = "formatted_file.xlsx"
|
>>> df.style.applymap(lambda v: pseudo_css).to_excel(filename) # doctest: +SKIP
|
|
.. figure:: ../../_static/style/format_excel_css.png
|
"""
|
if all(
|
(
|
formatter is None,
|
subset is None,
|
precision is None,
|
decimal == ".",
|
thousands is None,
|
na_rep is None,
|
escape is None,
|
hyperlinks is None,
|
)
|
):
|
self._display_funcs.clear()
|
return self # clear the formatter / revert to default and avoid looping
|
|
subset = slice(None) if subset is None else subset
|
subset = non_reducing_slice(subset)
|
data = self.data.loc[subset]
|
|
if not isinstance(formatter, dict):
|
formatter = {col: formatter for col in data.columns}
|
|
cis = self.columns.get_indexer_for(data.columns)
|
ris = self.index.get_indexer_for(data.index)
|
for ci in cis:
|
format_func = _maybe_wrap_formatter(
|
formatter.get(self.columns[ci]),
|
na_rep=na_rep,
|
precision=precision,
|
decimal=decimal,
|
thousands=thousands,
|
escape=escape,
|
hyperlinks=hyperlinks,
|
)
|
for ri in ris:
|
self._display_funcs[(ri, ci)] = format_func
|
|
return self
|
|
def format_index(
|
self,
|
formatter: ExtFormatter | None = None,
|
axis: Axis = 0,
|
level: Level | list[Level] | None = None,
|
na_rep: str | None = None,
|
precision: int | None = None,
|
decimal: str = ".",
|
thousands: str | None = None,
|
escape: str | None = None,
|
hyperlinks: str | None = None,
|
) -> StylerRenderer:
|
r"""
|
Format the text display value of index labels or column headers.
|
|
.. versionadded:: 1.4.0
|
|
Parameters
|
----------
|
formatter : str, callable, dict or None
|
Object to define how values are displayed. See notes.
|
axis : {0, "index", 1, "columns"}
|
Whether to apply the formatter to the index or column headers.
|
level : int, str, list
|
The level(s) over which to apply the generic formatter.
|
na_rep : str, optional
|
Representation for missing values.
|
If ``na_rep`` is None, no special formatting is applied.
|
precision : int, optional
|
Floating point precision to use for display purposes, if not determined by
|
the specified ``formatter``.
|
decimal : str, default "."
|
Character used as decimal separator for floats, complex and integers.
|
thousands : str, optional, default None
|
Character used as thousands separator for floats, complex and integers.
|
escape : str, optional
|
Use 'html' to replace the characters ``&``, ``<``, ``>``, ``'``, and ``"``
|
in cell display string with HTML-safe sequences.
|
Use 'latex' to replace the characters ``&``, ``%``, ``$``, ``#``, ``_``,
|
``{``, ``}``, ``~``, ``^``, and ``\`` in the cell display string with
|
LaTeX-safe sequences.
|
Escaping is done before ``formatter``.
|
hyperlinks : {"html", "latex"}, optional
|
Convert string patterns containing https://, http://, ftp:// or www. to
|
HTML <a> tags as clickable URL hyperlinks if "html", or LaTeX \href
|
commands if "latex".
|
|
Returns
|
-------
|
Styler
|
|
See Also
|
--------
|
Styler.format: Format the text display value of data cells.
|
|
Notes
|
-----
|
This method assigns a formatting function, ``formatter``, to each level label
|
in the DataFrame's index or column headers. If ``formatter`` is ``None``,
|
then the default formatter is used.
|
If a callable then that function should take a label value as input and return
|
a displayable representation, such as a string. If ``formatter`` is
|
given as a string this is assumed to be a valid Python format specification
|
and is wrapped to a callable as ``string.format(x)``. If a ``dict`` is given,
|
keys should correspond to MultiIndex level numbers or names, and values should
|
be string or callable, as above.
|
|
The default formatter currently expresses floats and complex numbers with the
|
pandas display precision unless using the ``precision`` argument here. The
|
default formatter does not adjust the representation of missing values unless
|
the ``na_rep`` argument is used.
|
|
The ``level`` argument defines which levels of a MultiIndex to apply the
|
method to. If the ``formatter`` argument is given in dict form but does
|
not include all levels within the level argument then these unspecified levels
|
will have the default formatter applied. Any levels in the formatter dict
|
specifically excluded from the level argument will be ignored.
|
|
When using a ``formatter`` string the dtypes must be compatible, otherwise a
|
`ValueError` will be raised.
|
|
.. warning::
|
`Styler.format_index` is ignored when using the output format
|
`Styler.to_excel`, since Excel and Python have inherrently different
|
formatting structures.
|
However, it is possible to use the `number-format` pseudo CSS attribute
|
to force Excel permissible formatting. See documentation for `Styler.format`.
|
|
Examples
|
--------
|
Using ``na_rep`` and ``precision`` with the default ``formatter``
|
|
>>> df = pd.DataFrame([[1, 2, 3]], columns=[2.0, np.nan, 4.0])
|
>>> df.style.format_index(axis=1, na_rep='MISS', precision=3) # doctest: +SKIP
|
2.000 MISS 4.000
|
0 1 2 3
|
|
Using a ``formatter`` specification on consistent dtypes in a level
|
|
>>> df.style.format_index('{:.2f}', axis=1, na_rep='MISS') # doctest: +SKIP
|
2.00 MISS 4.00
|
0 1 2 3
|
|
Using the default ``formatter`` for unspecified levels
|
|
>>> df = pd.DataFrame([[1, 2, 3]],
|
... columns=pd.MultiIndex.from_arrays([["a", "a", "b"],[2, np.nan, 4]]))
|
>>> df.style.format_index({0: lambda v: upper(v)}, axis=1, precision=1)
|
... # doctest: +SKIP
|
A B
|
2.0 nan 4.0
|
0 1 2 3
|
|
Using a callable ``formatter`` function.
|
|
>>> func = lambda s: 'STRING' if isinstance(s, str) else 'FLOAT'
|
>>> df.style.format_index(func, axis=1, na_rep='MISS')
|
... # doctest: +SKIP
|
STRING STRING
|
FLOAT MISS FLOAT
|
0 1 2 3
|
|
Using a ``formatter`` with HTML ``escape`` and ``na_rep``.
|
|
>>> df = pd.DataFrame([[1, 2, 3]], columns=['"A"', 'A&B', None])
|
>>> s = df.style.format_index('$ {0}', axis=1, escape="html", na_rep="NA")
|
... # doctest: +SKIP
|
<th .. >$ "A"</th>
|
<th .. >$ A&B</th>
|
<th .. >NA</td>
|
...
|
|
Using a ``formatter`` with LaTeX ``escape``.
|
|
>>> df = pd.DataFrame([[1, 2, 3]], columns=["123", "~", "$%#"])
|
>>> df.style.format_index("\\textbf{{{}}}", escape="latex", axis=1).to_latex()
|
... # doctest: +SKIP
|
\begin{tabular}{lrrr}
|
{} & {\textbf{123}} & {\textbf{\textasciitilde }} & {\textbf{\$\%\#}} \\
|
0 & 1 & 2 & 3 \\
|
\end{tabular}
|
"""
|
axis = self.data._get_axis_number(axis)
|
if axis == 0:
|
display_funcs_, obj = self._display_funcs_index, self.index
|
else:
|
display_funcs_, obj = self._display_funcs_columns, self.columns
|
levels_ = refactor_levels(level, obj)
|
|
if all(
|
(
|
formatter is None,
|
level is None,
|
precision is None,
|
decimal == ".",
|
thousands is None,
|
na_rep is None,
|
escape is None,
|
hyperlinks is None,
|
)
|
):
|
display_funcs_.clear()
|
return self # clear the formatter / revert to default and avoid looping
|
|
if not isinstance(formatter, dict):
|
formatter = {level: formatter for level in levels_}
|
else:
|
formatter = {
|
obj._get_level_number(level): formatter_
|
for level, formatter_ in formatter.items()
|
}
|
|
for lvl in levels_:
|
format_func = _maybe_wrap_formatter(
|
formatter.get(lvl),
|
na_rep=na_rep,
|
precision=precision,
|
decimal=decimal,
|
thousands=thousands,
|
escape=escape,
|
hyperlinks=hyperlinks,
|
)
|
|
for idx in [(i, lvl) if axis == 0 else (lvl, i) for i in range(len(obj))]:
|
display_funcs_[idx] = format_func
|
|
return self
|
|
def relabel_index(
|
self,
|
labels: Sequence | Index,
|
axis: Axis = 0,
|
level: Level | list[Level] | None = None,
|
) -> StylerRenderer:
|
r"""
|
Relabel the index, or column header, keys to display a set of specified values.
|
|
.. versionadded:: 1.5.0
|
|
Parameters
|
----------
|
labels : list-like or Index
|
New labels to display. Must have same length as the underlying values not
|
hidden.
|
axis : {"index", 0, "columns", 1}
|
Apply to the index or columns.
|
level : int, str, list, optional
|
The level(s) over which to apply the new labels. If `None` will apply
|
to all levels of an Index or MultiIndex which are not hidden.
|
|
Returns
|
-------
|
Styler
|
|
See Also
|
--------
|
Styler.format_index: Format the text display value of index or column headers.
|
Styler.hide: Hide the index, column headers, or specified data from display.
|
|
Notes
|
-----
|
As part of Styler, this method allows the display of an index to be
|
completely user-specified without affecting the underlying DataFrame data,
|
index, or column headers. This means that the flexibility of indexing is
|
maintained whilst the final display is customisable.
|
|
Since Styler is designed to be progressively constructed with method chaining,
|
this method is adapted to react to the **currently specified hidden elements**.
|
This is useful because it means one does not have to specify all the new
|
labels if the majority of an index, or column headers, have already been hidden.
|
The following produce equivalent display (note the length of ``labels`` in
|
each case).
|
|
.. code-block:: python
|
|
# relabel first, then hide
|
df = pd.DataFrame({"col": ["a", "b", "c"]})
|
df.style.relabel_index(["A", "B", "C"]).hide([0,1])
|
# hide first, then relabel
|
df = pd.DataFrame({"col": ["a", "b", "c"]})
|
df.style.hide([0,1]).relabel_index(["C"])
|
|
This method should be used, rather than :meth:`Styler.format_index`, in one of
|
the following cases (see examples):
|
|
- A specified set of labels are required which are not a function of the
|
underlying index keys.
|
- The function of the underlying index keys requires a counter variable,
|
such as those available upon enumeration.
|
|
Examples
|
--------
|
Basic use
|
|
>>> df = pd.DataFrame({"col": ["a", "b", "c"]})
|
>>> df.style.relabel_index(["A", "B", "C"]) # doctest: +SKIP
|
col
|
A a
|
B b
|
C c
|
|
Chaining with pre-hidden elements
|
|
>>> df.style.hide([0,1]).relabel_index(["C"]) # doctest: +SKIP
|
col
|
C c
|
|
Using a MultiIndex
|
|
>>> midx = pd.MultiIndex.from_product([[0, 1], [0, 1], [0, 1]])
|
>>> df = pd.DataFrame({"col": list(range(8))}, index=midx)
|
>>> styler = df.style # doctest: +SKIP
|
col
|
0 0 0 0
|
1 1
|
1 0 2
|
1 3
|
1 0 0 4
|
1 5
|
1 0 6
|
1 7
|
>>> styler.hide((midx.get_level_values(0)==0)|(midx.get_level_values(1)==0))
|
... # doctest: +SKIP
|
>>> styler.hide(level=[0,1]) # doctest: +SKIP
|
>>> styler.relabel_index(["binary6", "binary7"]) # doctest: +SKIP
|
col
|
binary6 6
|
binary7 7
|
|
We can also achieve the above by indexing first and then re-labeling
|
|
>>> styler = df.loc[[(1,1,0), (1,1,1)]].style
|
>>> styler.hide(level=[0,1]).relabel_index(["binary6", "binary7"])
|
... # doctest: +SKIP
|
col
|
binary6 6
|
binary7 7
|
|
Defining a formatting function which uses an enumeration counter. Also note
|
that the value of the index key is passed in the case of string labels so it
|
can also be inserted into the label, using curly brackets (or double curly
|
brackets if the string if pre-formatted),
|
|
>>> df = pd.DataFrame({"samples": np.random.rand(10)})
|
>>> styler = df.loc[np.random.randint(0,10,3)].style
|
>>> styler.relabel_index([f"sample{i+1} ({{}})" for i in range(3)])
|
... # doctest: +SKIP
|
samples
|
sample1 (5) 0.315811
|
sample2 (0) 0.495941
|
sample3 (2) 0.067946
|
"""
|
axis = self.data._get_axis_number(axis)
|
if axis == 0:
|
display_funcs_, obj = self._display_funcs_index, self.index
|
hidden_labels, hidden_lvls = self.hidden_rows, self.hide_index_
|
else:
|
display_funcs_, obj = self._display_funcs_columns, self.columns
|
hidden_labels, hidden_lvls = self.hidden_columns, self.hide_columns_
|
visible_len = len(obj) - len(set(hidden_labels))
|
if len(labels) != visible_len:
|
raise ValueError(
|
"``labels`` must be of length equal to the number of "
|
f"visible labels along ``axis`` ({visible_len})."
|
)
|
|
if level is None:
|
level = [i for i in range(obj.nlevels) if not hidden_lvls[i]]
|
levels_ = refactor_levels(level, obj)
|
|
def alias_(x, value):
|
if isinstance(value, str):
|
return value.format(x)
|
return value
|
|
for ai, i in enumerate([i for i in range(len(obj)) if i not in hidden_labels]):
|
if len(levels_) == 1:
|
idx = (i, levels_[0]) if axis == 0 else (levels_[0], i)
|
display_funcs_[idx] = partial(alias_, value=labels[ai])
|
else:
|
for aj, lvl in enumerate(levels_):
|
idx = (i, lvl) if axis == 0 else (lvl, i)
|
display_funcs_[idx] = partial(alias_, value=labels[ai][aj])
|
|
return self
|
|
|
def _element(
|
html_element: str,
|
html_class: str | None,
|
value: Any,
|
is_visible: bool,
|
**kwargs,
|
) -> dict:
|
"""
|
Template to return container with information for a <td></td> or <th></th> element.
|
"""
|
if "display_value" not in kwargs:
|
kwargs["display_value"] = value
|
return {
|
"type": html_element,
|
"value": value,
|
"class": html_class,
|
"is_visible": is_visible,
|
**kwargs,
|
}
|
|
|
def _get_trimming_maximums(
|
rn,
|
cn,
|
max_elements,
|
max_rows=None,
|
max_cols=None,
|
scaling_factor: float = 0.8,
|
) -> tuple[int, int]:
|
"""
|
Recursively reduce the number of rows and columns to satisfy max elements.
|
|
Parameters
|
----------
|
rn, cn : int
|
The number of input rows / columns
|
max_elements : int
|
The number of allowable elements
|
max_rows, max_cols : int, optional
|
Directly specify an initial maximum rows or columns before compression.
|
scaling_factor : float
|
Factor at which to reduce the number of rows / columns to fit.
|
|
Returns
|
-------
|
rn, cn : tuple
|
New rn and cn values that satisfy the max_elements constraint
|
"""
|
|
def scale_down(rn, cn):
|
if cn >= rn:
|
return rn, int(cn * scaling_factor)
|
else:
|
return int(rn * scaling_factor), cn
|
|
if max_rows:
|
rn = max_rows if rn > max_rows else rn
|
if max_cols:
|
cn = max_cols if cn > max_cols else cn
|
|
while rn * cn > max_elements:
|
rn, cn = scale_down(rn, cn)
|
|
return rn, cn
|
|
|
def _get_level_lengths(
|
index: Index,
|
sparsify: bool,
|
max_index: int,
|
hidden_elements: Sequence[int] | None = None,
|
):
|
"""
|
Given an index, find the level length for each element.
|
|
Parameters
|
----------
|
index : Index
|
Index or columns to determine lengths of each element
|
sparsify : bool
|
Whether to hide or show each distinct element in a MultiIndex
|
max_index : int
|
The maximum number of elements to analyse along the index due to trimming
|
hidden_elements : sequence of int
|
Index positions of elements hidden from display in the index affecting
|
length
|
|
Returns
|
-------
|
Dict :
|
Result is a dictionary of (level, initial_position): span
|
"""
|
if isinstance(index, MultiIndex):
|
levels = index.format(sparsify=lib.no_default, adjoin=False)
|
else:
|
levels = index.format()
|
|
if hidden_elements is None:
|
hidden_elements = []
|
|
lengths = {}
|
if not isinstance(index, MultiIndex):
|
for i, value in enumerate(levels):
|
if i not in hidden_elements:
|
lengths[(0, i)] = 1
|
return lengths
|
|
for i, lvl in enumerate(levels):
|
visible_row_count = 0 # used to break loop due to display trimming
|
for j, row in enumerate(lvl):
|
if visible_row_count > max_index:
|
break
|
if not sparsify:
|
# then lengths will always equal 1 since no aggregation.
|
if j not in hidden_elements:
|
lengths[(i, j)] = 1
|
visible_row_count += 1
|
elif (row is not lib.no_default) and (j not in hidden_elements):
|
# this element has not been sparsified so must be the start of section
|
last_label = j
|
lengths[(i, last_label)] = 1
|
visible_row_count += 1
|
elif row is not lib.no_default:
|
# even if the above is hidden, keep track of it in case length > 1 and
|
# later elements are visible
|
last_label = j
|
lengths[(i, last_label)] = 0
|
elif j not in hidden_elements:
|
# then element must be part of sparsified section and is visible
|
visible_row_count += 1
|
if visible_row_count > max_index:
|
break # do not add a length since the render trim limit reached
|
if lengths[(i, last_label)] == 0:
|
# if previous iteration was first-of-section 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
|
}
|
|
return non_zero_lengths
|
|
|
def _is_visible(idx_row, idx_col, lengths) -> bool:
|
"""
|
Index -> {(idx_row, idx_col): bool}).
|
"""
|
return (idx_col, idx_row) in lengths
|
|
|
def format_table_styles(styles: CSSStyles) -> CSSStyles:
|
"""
|
looks for multiple CSS selectors and separates them:
|
[{'selector': 'td, th', 'props': 'a:v;'}]
|
---> [{'selector': 'td', 'props': 'a:v;'},
|
{'selector': 'th', 'props': 'a:v;'}]
|
"""
|
return [
|
{"selector": selector, "props": css_dict["props"]}
|
for css_dict in styles
|
for selector in css_dict["selector"].split(",")
|
]
|
|
|
def _default_formatter(x: Any, precision: int, thousands: bool = False) -> Any:
|
"""
|
Format the display of a value
|
|
Parameters
|
----------
|
x : Any
|
Input variable to be formatted
|
precision : Int
|
Floating point precision used if ``x`` is float or complex.
|
thousands : bool, default False
|
Whether to group digits with thousands separated with ",".
|
|
Returns
|
-------
|
value : Any
|
Matches input type, or string if input is float or complex or int with sep.
|
"""
|
if is_float(x) or is_complex(x):
|
return f"{x:,.{precision}f}" if thousands else f"{x:.{precision}f}"
|
elif is_integer(x):
|
return f"{x:,.0f}" if thousands else f"{x:.0f}"
|
return x
|
|
|
def _wrap_decimal_thousands(
|
formatter: Callable, decimal: str, thousands: str | None
|
) -> Callable:
|
"""
|
Takes a string formatting function and wraps logic to deal with thousands and
|
decimal parameters, in the case that they are non-standard and that the input
|
is a (float, complex, int).
|
"""
|
|
def wrapper(x):
|
if is_float(x) or is_integer(x) or is_complex(x):
|
if decimal != "." and thousands is not None and thousands != ",":
|
return (
|
formatter(x)
|
.replace(",", "§_§-") # rare string to avoid "," <-> "." clash.
|
.replace(".", decimal)
|
.replace("§_§-", thousands)
|
)
|
elif decimal != "." and (thousands is None or thousands == ","):
|
return formatter(x).replace(".", decimal)
|
elif decimal == "." and thousands is not None and thousands != ",":
|
return formatter(x).replace(",", thousands)
|
return formatter(x)
|
|
return wrapper
|
|
|
def _str_escape(x, escape):
|
"""if escaping: only use on str, else return input"""
|
if isinstance(x, str):
|
if escape == "html":
|
return escape_html(x)
|
elif escape == "latex":
|
return _escape_latex(x)
|
else:
|
raise ValueError(
|
f"`escape` only permitted in {{'html', 'latex'}}, got {escape}"
|
)
|
return x
|
|
|
def _render_href(x, format):
|
"""uses regex to detect a common URL pattern and converts to href tag in format."""
|
if isinstance(x, str):
|
if format == "html":
|
href = '<a href="{0}" target="_blank">{0}</a>'
|
elif format == "latex":
|
href = r"\href{{{0}}}{{{0}}}"
|
else:
|
raise ValueError("``hyperlinks`` format can only be 'html' or 'latex'")
|
pat = r"((http|ftp)s?:\/\/|www.)[\w/\-?=%.:@]+\.[\w/\-&?=%.,':;~!@#$*()\[\]]+"
|
return re.sub(pat, lambda m: href.format(m.group(0)), x)
|
return x
|
|
|
def _maybe_wrap_formatter(
|
formatter: BaseFormatter | None = None,
|
na_rep: str | None = None,
|
precision: int | None = None,
|
decimal: str = ".",
|
thousands: str | None = None,
|
escape: str | None = None,
|
hyperlinks: str | None = None,
|
) -> Callable:
|
"""
|
Allows formatters to be expressed as str, callable or None, where None returns
|
a default formatting function. wraps with na_rep, and precision where they are
|
available.
|
"""
|
# Get initial func from input string, input callable, or from default factory
|
if isinstance(formatter, str):
|
func_0 = lambda x: formatter.format(x)
|
elif callable(formatter):
|
func_0 = formatter
|
elif formatter is None:
|
precision = (
|
get_option("styler.format.precision") if precision is None else precision
|
)
|
func_0 = partial(
|
_default_formatter, precision=precision, thousands=(thousands is not None)
|
)
|
else:
|
raise TypeError(f"'formatter' expected str or callable, got {type(formatter)}")
|
|
# Replace chars if escaping
|
if escape is not None:
|
func_1 = lambda x: func_0(_str_escape(x, escape=escape))
|
else:
|
func_1 = func_0
|
|
# Replace decimals and thousands if non-standard inputs detected
|
if decimal != "." or (thousands is not None and thousands != ","):
|
func_2 = _wrap_decimal_thousands(func_1, decimal=decimal, thousands=thousands)
|
else:
|
func_2 = func_1
|
|
# Render links
|
if hyperlinks is not None:
|
func_3 = lambda x: func_2(_render_href(x, format=hyperlinks))
|
else:
|
func_3 = func_2
|
|
# Replace missing values if na_rep
|
if na_rep is None:
|
return func_3
|
else:
|
return lambda x: na_rep if (isna(x) is True) else func_3(x)
|
|
|
def non_reducing_slice(slice_: Subset):
|
"""
|
Ensure that a slice doesn't reduce to a Series or Scalar.
|
|
Any user-passed `subset` should have this called on it
|
to make sure we're always working with DataFrames.
|
"""
|
# default to column slice, like DataFrame
|
# ['A', 'B'] -> IndexSlices[:, ['A', 'B']]
|
kinds = (ABCSeries, np.ndarray, Index, list, str)
|
if isinstance(slice_, kinds):
|
slice_ = IndexSlice[:, slice_]
|
|
def pred(part) -> bool:
|
"""
|
Returns
|
-------
|
bool
|
True if slice does *not* reduce,
|
False if `part` is a tuple.
|
"""
|
# true when slice does *not* reduce, False when part is a tuple,
|
# i.e. MultiIndex slice
|
if isinstance(part, tuple):
|
# GH#39421 check for sub-slice:
|
return any((isinstance(s, slice) or is_list_like(s)) for s in part)
|
else:
|
return isinstance(part, slice) or is_list_like(part)
|
|
if not is_list_like(slice_):
|
if not isinstance(slice_, slice):
|
# a 1-d slice, like df.loc[1]
|
slice_ = [[slice_]]
|
else:
|
# slice(a, b, c)
|
slice_ = [slice_] # to tuplize later
|
else:
|
# error: Item "slice" of "Union[slice, Sequence[Any]]" has no attribute
|
# "__iter__" (not iterable) -> is specifically list_like in conditional
|
slice_ = [p if pred(p) else [p] for p in slice_] # type: ignore[union-attr]
|
return tuple(slice_)
|
|
|
def maybe_convert_css_to_tuples(style: CSSProperties) -> CSSList:
|
"""
|
Convert css-string to sequence of tuples format if needed.
|
'color:red; border:1px solid black;' -> [('color', 'red'),
|
('border','1px solid red')]
|
"""
|
if isinstance(style, str):
|
s = style.split(";")
|
try:
|
return [
|
(x.split(":")[0].strip(), x.split(":")[1].strip())
|
for x in s
|
if x.strip() != ""
|
]
|
except IndexError:
|
raise ValueError(
|
"Styles supplied as string must follow CSS rule formats, "
|
f"for example 'attr: val;'. '{style}' was given."
|
)
|
return style
|
|
|
def refactor_levels(
|
level: Level | list[Level] | None,
|
obj: Index,
|
) -> list[int]:
|
"""
|
Returns a consistent levels arg for use in ``hide_index`` or ``hide_columns``.
|
|
Parameters
|
----------
|
level : int, str, list
|
Original ``level`` arg supplied to above methods.
|
obj:
|
Either ``self.index`` or ``self.columns``
|
|
Returns
|
-------
|
list : refactored arg with a list of levels to hide
|
"""
|
if level is None:
|
levels_: list[int] = list(range(obj.nlevels))
|
elif isinstance(level, int):
|
levels_ = [level]
|
elif isinstance(level, str):
|
levels_ = [obj._get_level_number(level)]
|
elif isinstance(level, list):
|
levels_ = [
|
obj._get_level_number(lev) if not isinstance(lev, int) else lev
|
for lev in level
|
]
|
else:
|
raise ValueError("`level` must be of type `int`, `str` or list of such")
|
return levels_
|
|
|
class Tooltips:
|
"""
|
An extension to ``Styler`` that allows for and manipulates tooltips on hover
|
of ``<td>`` cells in the HTML result.
|
|
Parameters
|
----------
|
css_name: str, default "pd-t"
|
Name of the CSS class that controls visualisation of tooltips.
|
css_props: list-like, default; see Notes
|
List of (attr, value) tuples defining properties of the CSS class.
|
tooltips: DataFrame, default empty
|
DataFrame of strings aligned with underlying Styler data for tooltip
|
display.
|
|
Notes
|
-----
|
The default properties for the tooltip CSS class are:
|
|
- visibility: hidden
|
- position: absolute
|
- z-index: 1
|
- background-color: black
|
- color: white
|
- transform: translate(-20px, -20px)
|
|
Hidden visibility is a key prerequisite to the hover functionality, and should
|
always be included in any manual properties specification.
|
"""
|
|
def __init__(
|
self,
|
css_props: CSSProperties = [
|
("visibility", "hidden"),
|
("position", "absolute"),
|
("z-index", 1),
|
("background-color", "black"),
|
("color", "white"),
|
("transform", "translate(-20px, -20px)"),
|
],
|
css_name: str = "pd-t",
|
tooltips: DataFrame = DataFrame(),
|
) -> None:
|
self.class_name = css_name
|
self.class_properties = css_props
|
self.tt_data = tooltips
|
self.table_styles: CSSStyles = []
|
|
@property
|
def _class_styles(self):
|
"""
|
Combine the ``_Tooltips`` CSS class name and CSS properties to the format
|
required to extend the underlying ``Styler`` `table_styles` to allow
|
tooltips to render in HTML.
|
|
Returns
|
-------
|
styles : List
|
"""
|
return [
|
{
|
"selector": f".{self.class_name}",
|
"props": maybe_convert_css_to_tuples(self.class_properties),
|
}
|
]
|
|
def _pseudo_css(self, uuid: str, name: str, row: int, col: int, text: str):
|
"""
|
For every table data-cell that has a valid tooltip (not None, NaN or
|
empty string) must create two pseudo CSS entries for the specific
|
<td> element id which are added to overall table styles:
|
an on hover visibility change and a content change
|
dependent upon the user's chosen display string.
|
|
For example:
|
[{"selector": "T__row1_col1:hover .pd-t",
|
"props": [("visibility", "visible")]},
|
{"selector": "T__row1_col1 .pd-t::after",
|
"props": [("content", "Some Valid Text String")]}]
|
|
Parameters
|
----------
|
uuid: str
|
The uuid of the Styler instance
|
name: str
|
The css-name of the class used for styling tooltips
|
row : int
|
The row index of the specified tooltip string data
|
col : int
|
The col index of the specified tooltip string data
|
text : str
|
The textual content of the tooltip to be displayed in HTML.
|
|
Returns
|
-------
|
pseudo_css : List
|
"""
|
selector_id = "#T_" + uuid + "_row" + str(row) + "_col" + str(col)
|
return [
|
{
|
"selector": selector_id + f":hover .{name}",
|
"props": [("visibility", "visible")],
|
},
|
{
|
"selector": selector_id + f" .{name}::after",
|
"props": [("content", f'"{text}"')],
|
},
|
]
|
|
def _translate(self, styler: StylerRenderer, d: dict):
|
"""
|
Mutate the render dictionary to allow for tooltips:
|
|
- Add ``<span>`` HTML element to each data cells ``display_value``. Ignores
|
headers.
|
- Add table level CSS styles to control pseudo classes.
|
|
Parameters
|
----------
|
styler_data : DataFrame
|
Underlying ``Styler`` DataFrame used for reindexing.
|
uuid : str
|
The underlying ``Styler`` uuid for CSS id.
|
d : dict
|
The dictionary prior to final render
|
|
Returns
|
-------
|
render_dict : Dict
|
"""
|
self.tt_data = self.tt_data.reindex_like(styler.data)
|
if self.tt_data.empty:
|
return d
|
|
name = self.class_name
|
mask = (self.tt_data.isna()) | (self.tt_data.eq("")) # empty string = no ttip
|
self.table_styles = [
|
style
|
for sublist in [
|
self._pseudo_css(styler.uuid, name, i, j, str(self.tt_data.iloc[i, j]))
|
for i in range(len(self.tt_data.index))
|
for j in range(len(self.tt_data.columns))
|
if not (
|
mask.iloc[i, j]
|
or i in styler.hidden_rows
|
or j in styler.hidden_columns
|
)
|
]
|
for style in sublist
|
]
|
|
if self.table_styles:
|
# add span class to every cell only if at least 1 non-empty tooltip
|
for row in d["body"]:
|
for item in row:
|
if item["type"] == "td":
|
item["display_value"] = (
|
str(item["display_value"])
|
+ f'<span class="{self.class_name}"></span>'
|
)
|
d["table_styles"].extend(self._class_styles)
|
d["table_styles"].extend(self.table_styles)
|
|
return d
|
|
|
def _parse_latex_table_wrapping(table_styles: CSSStyles, caption: str | None) -> bool:
|
"""
|
Indicate whether LaTeX {tabular} should be wrapped with a {table} environment.
|
|
Parses the `table_styles` and detects any selectors which must be included outside
|
of {tabular}, i.e. indicating that wrapping must occur, and therefore return True,
|
or if a caption exists and requires similar.
|
"""
|
IGNORED_WRAPPERS = ["toprule", "midrule", "bottomrule", "column_format"]
|
# ignored selectors are included with {tabular} so do not need wrapping
|
return (
|
table_styles is not None
|
and any(d["selector"] not in IGNORED_WRAPPERS for d in table_styles)
|
) or caption is not None
|
|
|
def _parse_latex_table_styles(table_styles: CSSStyles, selector: str) -> str | None:
|
"""
|
Return the first 'props' 'value' from ``tables_styles`` identified by ``selector``.
|
|
Examples
|
--------
|
>>> table_styles = [{'selector': 'foo', 'props': [('attr','value')]},
|
... {'selector': 'bar', 'props': [('attr', 'overwritten')]},
|
... {'selector': 'bar', 'props': [('a1', 'baz'), ('a2', 'ignore')]}]
|
>>> _parse_latex_table_styles(table_styles, selector='bar')
|
'baz'
|
|
Notes
|
-----
|
The replacement of "§" with ":" is to avoid the CSS problem where ":" has structural
|
significance and cannot be used in LaTeX labels, but is often required by them.
|
"""
|
for style in table_styles[::-1]: # in reverse for most recently applied style
|
if style["selector"] == selector:
|
return str(style["props"][0][1]).replace("§", ":")
|
return None
|
|
|
def _parse_latex_cell_styles(
|
latex_styles: CSSList, display_value: str, convert_css: bool = False
|
) -> str:
|
r"""
|
Mutate the ``display_value`` string including LaTeX commands from ``latex_styles``.
|
|
This method builds a recursive latex chain of commands based on the
|
CSSList input, nested around ``display_value``.
|
|
If a CSS style is given as ('<command>', '<options>') this is translated to
|
'\<command><options>{display_value}', and this value is treated as the
|
display value for the next iteration.
|
|
The most recent style forms the inner component, for example for styles:
|
`[('c1', 'o1'), ('c2', 'o2')]` this returns: `\c1o1{\c2o2{display_value}}`
|
|
Sometimes latex commands have to be wrapped with curly braces in different ways:
|
We create some parsing flags to identify the different behaviours:
|
|
- `--rwrap` : `\<command><options>{<display_value>}`
|
- `--wrap` : `{\<command><options> <display_value>}`
|
- `--nowrap` : `\<command><options> <display_value>`
|
- `--lwrap` : `{\<command><options>} <display_value>`
|
- `--dwrap` : `{\<command><options>}{<display_value>}`
|
|
For example for styles:
|
`[('c1', 'o1--wrap'), ('c2', 'o2')]` this returns: `{\c1o1 \c2o2{display_value}}
|
"""
|
if convert_css:
|
latex_styles = _parse_latex_css_conversion(latex_styles)
|
for command, options in latex_styles[::-1]: # in reverse for most recent style
|
formatter = {
|
"--wrap": f"{{\\{command}--to_parse {display_value}}}",
|
"--nowrap": f"\\{command}--to_parse {display_value}",
|
"--lwrap": f"{{\\{command}--to_parse}} {display_value}",
|
"--rwrap": f"\\{command}--to_parse{{{display_value}}}",
|
"--dwrap": f"{{\\{command}--to_parse}}{{{display_value}}}",
|
}
|
display_value = f"\\{command}{options} {display_value}"
|
for arg in ["--nowrap", "--wrap", "--lwrap", "--rwrap", "--dwrap"]:
|
if arg in str(options):
|
display_value = formatter[arg].replace(
|
"--to_parse", _parse_latex_options_strip(value=options, arg=arg)
|
)
|
break # only ever one purposeful entry
|
return display_value
|
|
|
def _parse_latex_header_span(
|
cell: dict[str, Any],
|
multirow_align: str,
|
multicol_align: str,
|
wrap: bool = False,
|
convert_css: bool = False,
|
) -> str:
|
r"""
|
Refactor the cell `display_value` if a 'colspan' or 'rowspan' attribute is present.
|
|
'rowspan' and 'colspan' do not occur simultaneouly. If they are detected then
|
the `display_value` is altered to a LaTeX `multirow` or `multicol` command
|
respectively, with the appropriate cell-span.
|
|
``wrap`` is used to enclose the `display_value` in braces which is needed for
|
column headers using an siunitx package.
|
|
Requires the package {multirow}, whereas multicol support is usually built in
|
to the {tabular} environment.
|
|
Examples
|
--------
|
>>> cell = {'cellstyle': '', 'display_value':'text', 'attributes': 'colspan="3"'}
|
>>> _parse_latex_header_span(cell, 't', 'c')
|
'\\multicolumn{3}{c}{text}'
|
"""
|
display_val = _parse_latex_cell_styles(
|
cell["cellstyle"], cell["display_value"], convert_css
|
)
|
if "attributes" in cell:
|
attrs = cell["attributes"]
|
if 'colspan="' in attrs:
|
colspan = attrs[attrs.find('colspan="') + 9 :] # len('colspan="') = 9
|
colspan = int(colspan[: colspan.find('"')])
|
if "naive-l" == multicol_align:
|
out = f"{{{display_val}}}" if wrap else f"{display_val}"
|
blanks = " & {}" if wrap else " &"
|
return out + blanks * (colspan - 1)
|
elif "naive-r" == multicol_align:
|
out = f"{{{display_val}}}" if wrap else f"{display_val}"
|
blanks = "{} & " if wrap else "& "
|
return blanks * (colspan - 1) + out
|
return f"\\multicolumn{{{colspan}}}{{{multicol_align}}}{{{display_val}}}"
|
elif 'rowspan="' in attrs:
|
if multirow_align == "naive":
|
return display_val
|
rowspan = attrs[attrs.find('rowspan="') + 9 :]
|
rowspan = int(rowspan[: rowspan.find('"')])
|
return f"\\multirow[{multirow_align}]{{{rowspan}}}{{*}}{{{display_val}}}"
|
if wrap:
|
return f"{{{display_val}}}"
|
else:
|
return display_val
|
|
|
def _parse_latex_options_strip(value: str | float, arg: str) -> str:
|
"""
|
Strip a css_value which may have latex wrapping arguments, css comment identifiers,
|
and whitespaces, to a valid string for latex options parsing.
|
|
For example: 'red /* --wrap */ ' --> 'red'
|
"""
|
return str(value).replace(arg, "").replace("/*", "").replace("*/", "").strip()
|
|
|
def _parse_latex_css_conversion(styles: CSSList) -> CSSList:
|
"""
|
Convert CSS (attribute,value) pairs to equivalent LaTeX (command,options) pairs.
|
|
Ignore conversion if tagged with `--latex` option, skipped if no conversion found.
|
"""
|
|
def font_weight(value, arg):
|
if value in ("bold", "bolder"):
|
return "bfseries", f"{arg}"
|
return None
|
|
def font_style(value, arg):
|
if value == "italic":
|
return "itshape", f"{arg}"
|
if value == "oblique":
|
return "slshape", f"{arg}"
|
return None
|
|
def color(value, user_arg, command, comm_arg):
|
"""
|
CSS colors have 5 formats to process:
|
|
- 6 digit hex code: "#ff23ee" --> [HTML]{FF23EE}
|
- 3 digit hex code: "#f0e" --> [HTML]{FF00EE}
|
- rgba: rgba(128, 255, 0, 0.5) --> [rgb]{0.502, 1.000, 0.000}
|
- rgb: rgb(128, 255, 0,) --> [rbg]{0.502, 1.000, 0.000}
|
- string: red --> {red}
|
|
Additionally rgb or rgba can be expressed in % which is also parsed.
|
"""
|
arg = user_arg if user_arg != "" else comm_arg
|
|
if value[0] == "#" and len(value) == 7: # color is hex code
|
return command, f"[HTML]{{{value[1:].upper()}}}{arg}"
|
if value[0] == "#" and len(value) == 4: # color is short hex code
|
val = f"{value[1].upper()*2}{value[2].upper()*2}{value[3].upper()*2}"
|
return command, f"[HTML]{{{val}}}{arg}"
|
elif value[:3] == "rgb": # color is rgb or rgba
|
r = re.findall("(?<=\\()[0-9\\s%]+(?=,)", value)[0].strip()
|
r = float(r[:-1]) / 100 if "%" in r else int(r) / 255
|
g = re.findall("(?<=,)[0-9\\s%]+(?=,)", value)[0].strip()
|
g = float(g[:-1]) / 100 if "%" in g else int(g) / 255
|
if value[3] == "a": # color is rgba
|
b = re.findall("(?<=,)[0-9\\s%]+(?=,)", value)[1].strip()
|
else: # color is rgb
|
b = re.findall("(?<=,)[0-9\\s%]+(?=\\))", value)[0].strip()
|
b = float(b[:-1]) / 100 if "%" in b else int(b) / 255
|
return command, f"[rgb]{{{r:.3f}, {g:.3f}, {b:.3f}}}{arg}"
|
else:
|
return command, f"{{{value}}}{arg}" # color is likely string-named
|
|
CONVERTED_ATTRIBUTES: dict[str, Callable] = {
|
"font-weight": font_weight,
|
"background-color": partial(color, command="cellcolor", comm_arg="--lwrap"),
|
"color": partial(color, command="color", comm_arg=""),
|
"font-style": font_style,
|
}
|
|
latex_styles: CSSList = []
|
for attribute, value in styles:
|
if isinstance(value, str) and "--latex" in value:
|
# return the style without conversion but drop '--latex'
|
latex_styles.append((attribute, value.replace("--latex", "")))
|
if attribute in CONVERTED_ATTRIBUTES:
|
arg = ""
|
for x in ["--wrap", "--nowrap", "--lwrap", "--dwrap", "--rwrap"]:
|
if x in str(value):
|
arg, value = x, _parse_latex_options_strip(value, x)
|
break
|
latex_style = CONVERTED_ATTRIBUTES[attribute](value, arg)
|
if latex_style is not None:
|
latex_styles.extend([latex_style])
|
return latex_styles
|
|
|
def _escape_latex(s):
|
r"""
|
Replace the characters ``&``, ``%``, ``$``, ``#``, ``_``, ``{``, ``}``,
|
``~``, ``^``, and ``\`` in the string with LaTeX-safe sequences.
|
|
Use this if you need to display text that might contain such characters in LaTeX.
|
|
Parameters
|
----------
|
s : str
|
Input to be escaped
|
|
Return
|
------
|
str :
|
Escaped string
|
"""
|
return (
|
s.replace("\\", "ab2§=§8yz") # rare string for final conversion: avoid \\ clash
|
.replace("ab2§=§8yz ", "ab2§=§8yz\\space ") # since \backslash gobbles spaces
|
.replace("&", "\\&")
|
.replace("%", "\\%")
|
.replace("$", "\\$")
|
.replace("#", "\\#")
|
.replace("_", "\\_")
|
.replace("{", "\\{")
|
.replace("}", "\\}")
|
.replace("~ ", "~\\space ") # since \textasciitilde gobbles spaces
|
.replace("~", "\\textasciitilde ")
|
.replace("^ ", "^\\space ") # since \textasciicircum gobbles spaces
|
.replace("^", "\\textasciicircum ")
|
.replace("ab2§=§8yz", "\\textbackslash ")
|
)
|
