Old engine for Continuous Time Bayesian Networks. Superseded by reCTBN. 🐍
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742 lines
25 KiB
742 lines
25 KiB
"""
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Utilities for conversion to writer-agnostic Excel representation.
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"""
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from functools import reduce
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import itertools
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import re
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from typing import Callable, Dict, Optional, Sequence, Union
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import warnings
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import numpy as np
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from pandas._typing import Label
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from pandas.core.dtypes import missing
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from pandas.core.dtypes.common import is_float, is_scalar
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from pandas.core.dtypes.generic import ABCIndex
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from pandas import DataFrame, Index, MultiIndex, PeriodIndex
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import pandas.core.common as com
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from pandas.io.common import stringify_path
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from pandas.io.formats.css import CSSResolver, CSSWarning
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from pandas.io.formats.format import get_level_lengths
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from pandas.io.formats.printing import pprint_thing
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class ExcelCell:
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__fields__ = ("row", "col", "val", "style", "mergestart", "mergeend")
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__slots__ = __fields__
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def __init__(
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self, row: int, col: int, val, style=None, mergestart=None, mergeend=None
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):
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self.row = row
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self.col = col
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self.val = val
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self.style = style
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self.mergestart = mergestart
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self.mergeend = mergeend
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class CSSToExcelConverter:
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"""
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A callable for converting CSS declarations to ExcelWriter styles
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Supports parts of CSS 2.2, with minimal CSS 3.0 support (e.g. text-shadow),
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focusing on font styling, backgrounds, borders and alignment.
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Operates by first computing CSS styles in a fairly generic
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way (see :meth:`compute_css`) then determining Excel style
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properties from CSS properties (see :meth:`build_xlstyle`).
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Parameters
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----------
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inherited : str, optional
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CSS declarations understood to be the containing scope for the
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CSS processed by :meth:`__call__`.
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"""
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# NB: Most of the methods here could be classmethods, as only __init__
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# and __call__ make use of instance attributes. We leave them as
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# instancemethods so that users can easily experiment with extensions
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# without monkey-patching.
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def __init__(self, inherited: Optional[str] = None):
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if inherited is not None:
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inherited = self.compute_css(inherited)
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self.inherited = inherited
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compute_css = CSSResolver()
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def __call__(self, declarations_str: str) -> Dict[str, Dict[str, str]]:
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"""
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Convert CSS declarations to ExcelWriter style.
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Parameters
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----------
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declarations_str : str
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List of CSS declarations.
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e.g. "font-weight: bold; background: blue"
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Returns
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-------
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xlstyle : dict
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A style as interpreted by ExcelWriter when found in
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ExcelCell.style.
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"""
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# TODO: memoize?
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properties = self.compute_css(declarations_str, self.inherited)
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return self.build_xlstyle(properties)
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def build_xlstyle(self, props: Dict[str, str]) -> Dict[str, Dict[str, str]]:
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out = {
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"alignment": self.build_alignment(props),
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"border": self.build_border(props),
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"fill": self.build_fill(props),
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"font": self.build_font(props),
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"number_format": self.build_number_format(props),
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}
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# TODO: handle cell width and height: needs support in pandas.io.excel
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def remove_none(d: Dict[str, str]) -> None:
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"""Remove key where value is None, through nested dicts"""
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for k, v in list(d.items()):
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if v is None:
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del d[k]
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elif isinstance(v, dict):
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remove_none(v)
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if not v:
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del d[k]
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remove_none(out)
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return out
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VERTICAL_MAP = {
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"top": "top",
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"text-top": "top",
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"middle": "center",
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"baseline": "bottom",
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"bottom": "bottom",
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"text-bottom": "bottom",
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# OpenXML also has 'justify', 'distributed'
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}
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def build_alignment(self, props) -> Dict[str, Optional[Union[bool, str]]]:
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# TODO: text-indent, padding-left -> alignment.indent
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return {
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"horizontal": props.get("text-align"),
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"vertical": self.VERTICAL_MAP.get(props.get("vertical-align")),
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"wrap_text": (
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None
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if props.get("white-space") is None
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else props["white-space"] not in ("nowrap", "pre", "pre-line")
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),
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}
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def build_border(self, props: Dict) -> Dict[str, Dict[str, str]]:
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return {
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side: {
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"style": self._border_style(
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props.get(f"border-{side}-style"),
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props.get(f"border-{side}-width"),
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),
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"color": self.color_to_excel(props.get(f"border-{side}-color")),
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}
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for side in ["top", "right", "bottom", "left"]
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}
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def _border_style(self, style: Optional[str], width):
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# convert styles and widths to openxml, one of:
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# 'dashDot'
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# 'dashDotDot'
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# 'dashed'
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# 'dotted'
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# 'double'
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# 'hair'
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# 'medium'
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# 'mediumDashDot'
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# 'mediumDashDotDot'
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# 'mediumDashed'
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# 'slantDashDot'
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# 'thick'
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# 'thin'
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if width is None and style is None:
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return None
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if style == "none" or style == "hidden":
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return None
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if width is None:
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width = "2pt"
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width = float(width[:-2])
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if width < 1e-5:
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return None
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elif width < 1.3:
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width_name = "thin"
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elif width < 2.8:
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width_name = "medium"
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else:
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width_name = "thick"
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if style in (None, "groove", "ridge", "inset", "outset"):
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# not handled
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style = "solid"
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if style == "double":
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return "double"
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if style == "solid":
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return width_name
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if style == "dotted":
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if width_name in ("hair", "thin"):
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return "dotted"
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return "mediumDashDotDot"
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if style == "dashed":
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if width_name in ("hair", "thin"):
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return "dashed"
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return "mediumDashed"
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def build_fill(self, props: Dict[str, str]):
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# TODO: perhaps allow for special properties
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# -excel-pattern-bgcolor and -excel-pattern-type
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fill_color = props.get("background-color")
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if fill_color not in (None, "transparent", "none"):
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return {"fgColor": self.color_to_excel(fill_color), "patternType": "solid"}
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BOLD_MAP = {
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"bold": True,
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"bolder": True,
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"600": True,
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"700": True,
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"800": True,
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"900": True,
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"normal": False,
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"lighter": False,
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"100": False,
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"200": False,
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"300": False,
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"400": False,
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"500": False,
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}
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ITALIC_MAP = {"normal": False, "italic": True, "oblique": True}
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def build_font(self, props) -> Dict[str, Optional[Union[bool, int, str]]]:
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size = props.get("font-size")
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if size is not None:
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assert size.endswith("pt")
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size = float(size[:-2])
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font_names_tmp = re.findall(
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r"""(?x)
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(
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"(?:[^"]|\\")+"
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'(?:[^']|\\')+'
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[^'",]+
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)(?=,|\s*$)
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""",
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props.get("font-family", ""),
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)
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font_names = []
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for name in font_names_tmp:
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if name[:1] == '"':
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name = name[1:-1].replace('\\"', '"')
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elif name[:1] == "'":
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name = name[1:-1].replace("\\'", "'")
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else:
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name = name.strip()
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if name:
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font_names.append(name)
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family = None
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for name in font_names:
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if name == "serif":
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family = 1 # roman
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break
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elif name == "sans-serif":
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family = 2 # swiss
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break
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elif name == "cursive":
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family = 4 # script
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break
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elif name == "fantasy":
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family = 5 # decorative
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break
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decoration = props.get("text-decoration")
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if decoration is not None:
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decoration = decoration.split()
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else:
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decoration = ()
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return {
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"name": font_names[0] if font_names else None,
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"family": family,
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"size": size,
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"bold": self.BOLD_MAP.get(props.get("font-weight")),
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"italic": self.ITALIC_MAP.get(props.get("font-style")),
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"underline": ("single" if "underline" in decoration else None),
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"strike": ("line-through" in decoration) or None,
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"color": self.color_to_excel(props.get("color")),
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# shadow if nonzero digit before shadow color
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"shadow": (
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bool(re.search("^[^#(]*[1-9]", props["text-shadow"]))
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if "text-shadow" in props
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else None
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),
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# FIXME: dont leave commented-out
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# 'vertAlign':,
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# 'charset': ,
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# 'scheme': ,
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# 'outline': ,
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# 'condense': ,
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}
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NAMED_COLORS = {
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"maroon": "800000",
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"brown": "A52A2A",
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"red": "FF0000",
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"pink": "FFC0CB",
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"orange": "FFA500",
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"yellow": "FFFF00",
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"olive": "808000",
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"green": "008000",
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"purple": "800080",
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"fuchsia": "FF00FF",
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"lime": "00FF00",
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"teal": "008080",
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"aqua": "00FFFF",
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"blue": "0000FF",
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"navy": "000080",
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"black": "000000",
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"gray": "808080",
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"grey": "808080",
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"silver": "C0C0C0",
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"white": "FFFFFF",
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}
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def color_to_excel(self, val: Optional[str]):
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if val is None:
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return None
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if val.startswith("#") and len(val) == 7:
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return val[1:].upper()
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if val.startswith("#") and len(val) == 4:
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return (val[1] * 2 + val[2] * 2 + val[3] * 2).upper()
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try:
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return self.NAMED_COLORS[val]
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except KeyError:
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warnings.warn(f"Unhandled color format: {repr(val)}", CSSWarning)
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def build_number_format(self, props: Dict) -> Dict[str, Optional[str]]:
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return {"format_code": props.get("number-format")}
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|
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class ExcelFormatter:
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"""
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Class for formatting a DataFrame to a list of ExcelCells,
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Parameters
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----------
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df : DataFrame or Styler
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na_rep: na representation
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float_format : string, default None
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Format string for floating point numbers
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cols : sequence, optional
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Columns to write
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header : boolean or list of string, default True
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Write out column names. If a list of string is given it is
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assumed to be aliases for the column names
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index : boolean, default True
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output row names (index)
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index_label : string or sequence, default None
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Column label for index column(s) if desired. If None is given, and
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`header` and `index` are True, then the index names are used. A
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sequence should be given if the DataFrame uses MultiIndex.
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merge_cells : boolean, default False
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Format MultiIndex and Hierarchical Rows as merged cells.
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inf_rep : string, default `'inf'`
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representation for np.inf values (which aren't representable in Excel)
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A `'-'` sign will be added in front of -inf.
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style_converter : callable, optional
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This translates Styler styles (CSS) into ExcelWriter styles.
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Defaults to ``CSSToExcelConverter()``.
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It should have signature css_declarations string -> excel style.
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This is only called for body cells.
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"""
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max_rows = 2 ** 20
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max_cols = 2 ** 14
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def __init__(
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self,
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df,
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na_rep: str = "",
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float_format: Optional[str] = None,
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cols: Optional[Sequence[Label]] = None,
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header: Union[Sequence[Label], bool] = True,
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index: bool = True,
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index_label: Optional[Union[Label, Sequence[Label]]] = None,
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merge_cells: bool = False,
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inf_rep: str = "inf",
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style_converter: Optional[Callable] = None,
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):
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self.rowcounter = 0
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self.na_rep = na_rep
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if not isinstance(df, DataFrame):
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self.styler = df
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df = df.data
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if style_converter is None:
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style_converter = CSSToExcelConverter()
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self.style_converter = style_converter
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else:
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self.styler = None
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self.df = df
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if cols is not None:
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# all missing, raise
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if not len(Index(cols) & df.columns):
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raise KeyError("passes columns are not ALL present dataframe")
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if len(Index(cols) & df.columns) != len(cols):
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# Deprecated in GH#17295, enforced in 1.0.0
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raise KeyError("Not all names specified in 'columns' are found")
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self.df = df.reindex(columns=cols)
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self.columns = self.df.columns
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self.float_format = float_format
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self.index = index
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self.index_label = index_label
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self.header = header
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self.merge_cells = merge_cells
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self.inf_rep = inf_rep
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|
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@property
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def header_style(self):
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return {
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"font": {"bold": True},
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"borders": {
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"top": "thin",
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"right": "thin",
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"bottom": "thin",
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"left": "thin",
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},
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"alignment": {"horizontal": "center", "vertical": "top"},
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}
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def _format_value(self, val):
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if is_scalar(val) and missing.isna(val):
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val = self.na_rep
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elif is_float(val):
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if missing.isposinf_scalar(val):
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val = self.inf_rep
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elif missing.isneginf_scalar(val):
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val = f"-{self.inf_rep}"
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elif self.float_format is not None:
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val = float(self.float_format % val)
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if getattr(val, "tzinfo", None) is not None:
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raise ValueError(
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"Excel does not support datetimes with "
|
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"timezones. Please ensure that datetimes "
|
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"are timezone unaware before writing to Excel."
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)
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return val
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|
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def _format_header_mi(self):
|
|
if self.columns.nlevels > 1:
|
|
if not self.index:
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raise NotImplementedError(
|
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"Writing to Excel with MultiIndex columns and no "
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"index ('index'=False) is not yet implemented."
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)
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|
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has_aliases = isinstance(self.header, (tuple, list, np.ndarray, ABCIndex))
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|
if not (has_aliases or self.header):
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return
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|
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|
columns = self.columns
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|
level_strs = columns.format(
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|
sparsify=self.merge_cells, adjoin=False, names=False
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|
)
|
|
level_lengths = get_level_lengths(level_strs)
|
|
coloffset = 0
|
|
lnum = 0
|
|
|
|
if self.index and isinstance(self.df.index, MultiIndex):
|
|
coloffset = len(self.df.index[0]) - 1
|
|
|
|
if self.merge_cells:
|
|
# Format multi-index as a merged cells.
|
|
for lnum in range(len(level_lengths)):
|
|
name = columns.names[lnum]
|
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yield ExcelCell(lnum, coloffset, name, self.header_style)
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|
|
|
for lnum, (spans, levels, level_codes) in enumerate(
|
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zip(level_lengths, columns.levels, columns.codes)
|
|
):
|
|
values = levels.take(level_codes)
|
|
for i in spans:
|
|
if spans[i] > 1:
|
|
yield ExcelCell(
|
|
lnum,
|
|
coloffset + i + 1,
|
|
values[i],
|
|
self.header_style,
|
|
lnum,
|
|
coloffset + i + spans[i],
|
|
)
|
|
else:
|
|
yield ExcelCell(
|
|
lnum, coloffset + i + 1, values[i], self.header_style
|
|
)
|
|
else:
|
|
# Format in legacy format with dots to indicate levels.
|
|
for i, values in enumerate(zip(*level_strs)):
|
|
v = ".".join(map(pprint_thing, values))
|
|
yield ExcelCell(lnum, coloffset + i + 1, v, self.header_style)
|
|
|
|
self.rowcounter = lnum
|
|
|
|
def _format_header_regular(self):
|
|
has_aliases = isinstance(self.header, (tuple, list, np.ndarray, ABCIndex))
|
|
if has_aliases or self.header:
|
|
coloffset = 0
|
|
|
|
if self.index:
|
|
coloffset = 1
|
|
if isinstance(self.df.index, MultiIndex):
|
|
coloffset = len(self.df.index[0])
|
|
|
|
colnames = self.columns
|
|
if has_aliases:
|
|
if len(self.header) != len(self.columns):
|
|
raise ValueError(
|
|
f"Writing {len(self.columns)} cols but got {len(self.header)} "
|
|
"aliases"
|
|
)
|
|
else:
|
|
colnames = self.header
|
|
|
|
for colindex, colname in enumerate(colnames):
|
|
yield ExcelCell(
|
|
self.rowcounter, colindex + coloffset, colname, self.header_style
|
|
)
|
|
|
|
def _format_header(self):
|
|
if isinstance(self.columns, MultiIndex):
|
|
gen = self._format_header_mi()
|
|
else:
|
|
gen = self._format_header_regular()
|
|
|
|
gen2 = ()
|
|
if self.df.index.names:
|
|
row = [x if x is not None else "" for x in self.df.index.names] + [
|
|
""
|
|
] * len(self.columns)
|
|
if reduce(lambda x, y: x and y, map(lambda x: x != "", row)):
|
|
gen2 = (
|
|
ExcelCell(self.rowcounter, colindex, val, self.header_style)
|
|
for colindex, val in enumerate(row)
|
|
)
|
|
self.rowcounter += 1
|
|
return itertools.chain(gen, gen2)
|
|
|
|
def _format_body(self):
|
|
if isinstance(self.df.index, MultiIndex):
|
|
return self._format_hierarchical_rows()
|
|
else:
|
|
return self._format_regular_rows()
|
|
|
|
def _format_regular_rows(self):
|
|
has_aliases = isinstance(self.header, (tuple, list, np.ndarray, ABCIndex))
|
|
if has_aliases or self.header:
|
|
self.rowcounter += 1
|
|
|
|
# output index and index_label?
|
|
if self.index:
|
|
# check aliases
|
|
# if list only take first as this is not a MultiIndex
|
|
if self.index_label and isinstance(
|
|
self.index_label, (list, tuple, np.ndarray, Index)
|
|
):
|
|
index_label = self.index_label[0]
|
|
# if string good to go
|
|
elif self.index_label and isinstance(self.index_label, str):
|
|
index_label = self.index_label
|
|
else:
|
|
index_label = self.df.index.names[0]
|
|
|
|
if isinstance(self.columns, MultiIndex):
|
|
self.rowcounter += 1
|
|
|
|
if index_label and self.header is not False:
|
|
yield ExcelCell(self.rowcounter - 1, 0, index_label, self.header_style)
|
|
|
|
# write index_values
|
|
index_values = self.df.index
|
|
if isinstance(self.df.index, PeriodIndex):
|
|
index_values = self.df.index.to_timestamp()
|
|
|
|
for idx, idxval in enumerate(index_values):
|
|
yield ExcelCell(self.rowcounter + idx, 0, idxval, self.header_style)
|
|
|
|
coloffset = 1
|
|
else:
|
|
coloffset = 0
|
|
|
|
for cell in self._generate_body(coloffset):
|
|
yield cell
|
|
|
|
def _format_hierarchical_rows(self):
|
|
has_aliases = isinstance(self.header, (tuple, list, np.ndarray, ABCIndex))
|
|
if has_aliases or self.header:
|
|
self.rowcounter += 1
|
|
|
|
gcolidx = 0
|
|
|
|
if self.index:
|
|
index_labels = self.df.index.names
|
|
# check for aliases
|
|
if self.index_label and isinstance(
|
|
self.index_label, (list, tuple, np.ndarray, Index)
|
|
):
|
|
index_labels = self.index_label
|
|
|
|
# MultiIndex columns require an extra row
|
|
# with index names (blank if None) for
|
|
# unambiguous round-trip, unless not merging,
|
|
# in which case the names all go on one row Issue #11328
|
|
if isinstance(self.columns, MultiIndex) and self.merge_cells:
|
|
self.rowcounter += 1
|
|
|
|
# if index labels are not empty go ahead and dump
|
|
if com.any_not_none(*index_labels) and self.header is not False:
|
|
|
|
for cidx, name in enumerate(index_labels):
|
|
yield ExcelCell(self.rowcounter - 1, cidx, name, self.header_style)
|
|
|
|
if self.merge_cells:
|
|
# Format hierarchical rows as merged cells.
|
|
level_strs = self.df.index.format(
|
|
sparsify=True, adjoin=False, names=False
|
|
)
|
|
level_lengths = get_level_lengths(level_strs)
|
|
|
|
for spans, levels, level_codes in zip(
|
|
level_lengths, self.df.index.levels, self.df.index.codes
|
|
):
|
|
|
|
values = levels.take(
|
|
level_codes, allow_fill=levels._can_hold_na, fill_value=True
|
|
)
|
|
|
|
for i in spans:
|
|
if spans[i] > 1:
|
|
yield ExcelCell(
|
|
self.rowcounter + i,
|
|
gcolidx,
|
|
values[i],
|
|
self.header_style,
|
|
self.rowcounter + i + spans[i] - 1,
|
|
gcolidx,
|
|
)
|
|
else:
|
|
yield ExcelCell(
|
|
self.rowcounter + i,
|
|
gcolidx,
|
|
values[i],
|
|
self.header_style,
|
|
)
|
|
gcolidx += 1
|
|
|
|
else:
|
|
# Format hierarchical rows with non-merged values.
|
|
for indexcolvals in zip(*self.df.index):
|
|
for idx, indexcolval in enumerate(indexcolvals):
|
|
yield ExcelCell(
|
|
self.rowcounter + idx,
|
|
gcolidx,
|
|
indexcolval,
|
|
self.header_style,
|
|
)
|
|
gcolidx += 1
|
|
|
|
for cell in self._generate_body(gcolidx):
|
|
yield cell
|
|
|
|
def _generate_body(self, coloffset: int):
|
|
if self.styler is None:
|
|
styles = None
|
|
else:
|
|
styles = self.styler._compute().ctx
|
|
if not styles:
|
|
styles = None
|
|
xlstyle = None
|
|
|
|
# Write the body of the frame data series by series.
|
|
for colidx in range(len(self.columns)):
|
|
series = self.df.iloc[:, colidx]
|
|
for i, val in enumerate(series):
|
|
if styles is not None:
|
|
xlstyle = self.style_converter(";".join(styles[i, colidx]))
|
|
yield ExcelCell(self.rowcounter + i, colidx + coloffset, val, xlstyle)
|
|
|
|
def get_formatted_cells(self):
|
|
for cell in itertools.chain(self._format_header(), self._format_body()):
|
|
cell.val = self._format_value(cell.val)
|
|
yield cell
|
|
|
|
def write(
|
|
self,
|
|
writer,
|
|
sheet_name="Sheet1",
|
|
startrow=0,
|
|
startcol=0,
|
|
freeze_panes=None,
|
|
engine=None,
|
|
):
|
|
"""
|
|
writer : string or ExcelWriter object
|
|
File path or existing ExcelWriter
|
|
sheet_name : string, default 'Sheet1'
|
|
Name of sheet which will contain DataFrame
|
|
startrow :
|
|
upper left cell row to dump data frame
|
|
startcol :
|
|
upper left cell column to dump data frame
|
|
freeze_panes : tuple of integer (length 2), default None
|
|
Specifies the one-based bottommost row and rightmost column that
|
|
is to be frozen
|
|
engine : string, default None
|
|
write engine to use if writer is a path - you can also set this
|
|
via the options ``io.excel.xlsx.writer``, ``io.excel.xls.writer``,
|
|
and ``io.excel.xlsm.writer``.
|
|
"""
|
|
from pandas.io.excel import ExcelWriter
|
|
|
|
num_rows, num_cols = self.df.shape
|
|
if num_rows > self.max_rows or num_cols > self.max_cols:
|
|
raise ValueError(
|
|
f"This sheet is too large! Your sheet size is: {num_rows}, {num_cols} "
|
|
f"Max sheet size is: {self.max_rows}, {self.max_cols}"
|
|
)
|
|
|
|
if isinstance(writer, ExcelWriter):
|
|
need_save = False
|
|
else:
|
|
writer = ExcelWriter(stringify_path(writer), engine=engine)
|
|
need_save = True
|
|
|
|
formatted_cells = self.get_formatted_cells()
|
|
writer.write_cells(
|
|
formatted_cells,
|
|
sheet_name,
|
|
startrow=startrow,
|
|
startcol=startcol,
|
|
freeze_panes=freeze_panes,
|
|
)
|
|
if need_save:
|
|
writer.save()
|
|
|