def table(ax,
data: FrameOrSeriesUnion,
rowLabels=None,
colLabels=None,
**kwargs) -> Table:
if isinstance(data, ABCSeries):
data = data.to_frame()
elif isinstance(data, ABCDataFrame):
pass
else:
raise ValueError("Input data must be DataFrame or Series")
if rowLabels is None:
rowLabels = data.index
if colLabels is None:
colLabels = data.columns
cellText = data.values
table = matplotlib.table.table(ax,
cellText=cellText,
rowLabels=rowLabels,
colLabels=colLabels,
**kwargs)
return table
def reindex_weights_to_indices(
weights: FrameOrSeriesUnion,
indices: pd.DataFrame,
axis: Axis = 0,
) -> pd.DataFrame:
"""Reshapes and reindexes weights to indices, if they do not
already have the same shape and share the same index frequency.
"""
axis = _handle_axis(axis)
# Convert to a DataFrame is weight is a Series, transpose if needed
if isinstance(weights, pd.Series):
weights = weights.to_frame()
if axis == 0:
weights = weights.T
if not weights.axes[axis].equals(indices.axes[axis]):
return reindex_and_fill(weights, indices, 'ffill', axis)
else:
return weights
def __init__(
self,
data: FrameOrSeriesUnion,
uuid: str | None = None,
uuid_len: int = 5,
table_styles: CSSStyles | None = None,
table_attributes: str | None = None,
caption: str | None = None,
cell_ids: bool = True,
):
# 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")
if not data.index.is_unique or not data.columns.is_unique:
raise ValueError("style is not supported for non-unique indices.")
self.data: DataFrame = data
self.index: Index = data.index
self.columns: Index = data.columns
if not isinstance(uuid_len, int) or not uuid_len >= 0:
raise TypeError(
"``uuid_len`` must be an integer in range [0, 32].")
self.uuid_len = min(32, uuid_len)
self.uuid = (uuid or uuid4().hex[:self.uuid_len]) + "_"
self.table_styles = table_styles
self.table_attributes = table_attributes
self.caption = caption
self.cell_ids = cell_ids
# add rendering variables
self.hidden_index: bool = False
self.hidden_columns: Sequence[int] = []
self.ctx: 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
def_precision = get_option("display.precision")
self._display_funcs: DefaultDict[ # maps (row, col) -> formatting function
tuple[int, int], Callable[[Any], str]] = defaultdict(
lambda: partial(_default_formatter, precision=def_precision))