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Programmation Python
Les fondamentaux
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Module « pandas »
Classe « MultiIndex »
Informations générales
Héritage
builtins.object
DirNamesMixin
PandasObject
builtins.object
OpsMixin
IndexOpsMixin
Index
MultiIndex
Définition
class MultiIndex(Index):
help(MultiIndex)
A multi-level, or hierarchical, index object for pandas objects.
Parameters
----------
levels : sequence of arrays
The unique labels for each level.
codes : sequence of arrays
Integers for each level designating which label at each location.
sortorder : optional int
Level of sortedness (must be lexicographically sorted by that
level).
names : optional sequence of objects
Names for each of the index levels. (name is accepted for compat).
copy : bool, default False
Copy the meta-data.
verify_integrity : bool, default True
Check that the levels/codes are consistent and valid.
Attributes
----------
names
levels
codes
nlevels
levshape
dtypes
Methods
-------
from_arrays
from_tuples
from_product
from_frame
set_levels
set_codes
to_frame
to_flat_index
sortlevel
droplevel
swaplevel
reorder_levels
remove_unused_levels
get_level_values
get_indexer
get_loc
get_locs
get_loc_level
drop
See Also
--------
MultiIndex.from_arrays : Convert list of arrays to MultiIndex.
MultiIndex.from_product : Create a MultiIndex from the cartesian product
of iterables.
MultiIndex.from_tuples : Convert list of tuples to a MultiIndex.
MultiIndex.from_frame : Make a MultiIndex from a DataFrame.
Index : The base pandas Index type.
Notes
-----
See the `user guide
<https://pandas.pydata.org/pandas-docs/stable/user_guide/advanced.html>`__
for more.
Examples
--------
A new ``MultiIndex`` is typically constructed using one of the helper
methods :meth:`MultiIndex.from_arrays`, :meth:`MultiIndex.from_product`
and :meth:`MultiIndex.from_tuples`. For example (using ``.from_arrays``):
>>> arrays = [[1, 1, 2, 2], ['red', 'blue', 'red', 'blue']]
>>> pd.MultiIndex.from_arrays(arrays, names=('number', 'color'))
MultiIndex([(1, 'red'),
(1, 'blue'),
(2, 'red'),
(2, 'blue')],
names=['number', 'color'])
See further examples for how to construct a MultiIndex in the doc strings
of the mentioned helper methods.
Constructeur(s)
__new__(cls, levels=None, codes=None, sortorder=None, names=None, dtype=None, copy: 'bool' = False, name=None, verify_integrity: 'bool' = True) -> 'Self' |
|
__init__(self, /, *args, **kwargs) |
Initialize self. See help(type(self)) for accurate signature. [extrait de __init__.__doc__] |
Liste des attributs statiques
dtype | <pandas._libs.properties.CachedProperty object at 0x0000020D9B4F8E40> |
dtypes | <pandas._libs.properties.CachedProperty object at 0x0000020D9B4F8A80> |
hasnans | <pandas._libs.properties.CachedProperty object at 0x0000020D9B488B40> |
inferred_type | <pandas._libs.properties.CachedProperty object at 0x0000020D9B4F8FC0> |
is_monotonic_decreasing | <pandas._libs.properties.CachedProperty object at 0x0000020D9B4F9040> |
is_monotonic_increasing | <pandas._libs.properties.CachedProperty object at 0x0000020D9B4F9000> |
is_unique | <pandas._libs.properties.CachedProperty object at 0x0000020D9B4886C0> |
levels | <pandas._libs.properties.CachedProperty object at 0x0000020D9B4F8AC0> |
nbytes | <pandas._libs.properties.CachedProperty object at 0x0000020D9B4F8EC0> |
Attributs statiques hérités de la classe Index
array
Liste des propriétés
array | |
codes | |
empty | |
has_duplicates | |
levshape | |
name | |
names | |
ndim | |
nlevels | |
shape | |
size | |
T | |
values | |
Propriétés héritées de la classe Index
is_monotonic_decreasing, is_monotonic_increasing, nbytes
Propriétés héritées de la classe IndexOpsMixin
dtype, is_unique
Opérateurs hérités de la classe Index
__iadd__, __invert__, __neg__, __pos__, __setitem__
Opérateurs hérités de la classe OpsMixin
__add__, __and__, __eq__, __floordiv__, __ge__, __gt__, __le__, __lt__, __mod__, __mul__, __ne__, __or__, __pow__, __radd__, __rand__, __rfloordiv__, __rmod__, __rmul__, __ror__, __rpow__, __rsub__, __rtruediv__, __rxor__, __sub__, __truediv__, __xor__
Liste des méthodes
Toutes les méthodes
Méthodes d'instance
Méthodes statiques
Méthodes dépréciées
__array__(self, dtype=None, copy=None) -> 'np.ndarray' |
the array interface, return my values [extrait de __array__.__doc__] |
__len__(self) -> 'int' |
|
__reduce__(self) |
Necessary for making this object picklable [extrait de __reduce__.__doc__] |
append(self, other) |
|
argsort(self, *args, na_position: 'str' = 'last', **kwargs) -> 'npt.NDArray[np.intp]' |
|
astype(self, dtype, copy: 'bool' = True) |
|
copy(self, names=None, deep: 'bool' = False, name=None) -> 'Self' |
|
delete(self, loc) -> 'MultiIndex' |
|
drop(self, codes, level: 'Index | np.ndarray | Iterable[Hashable] | None' = None, errors: 'IgnoreRaise' = 'raise') -> 'MultiIndex' |
|
dropna(self, how: 'AnyAll' = 'any') -> 'MultiIndex' |
|
duplicated(self, keep: 'DropKeep' = 'first') -> 'npt.NDArray[np.bool_]' |
|
equal_levels(self, other: 'MultiIndex') -> 'bool' |
|
equals(self, other: 'object') -> 'bool' |
|
fillna(self, value=None, downcast=None) |
|
format(self, name: 'bool | None' = None, formatter: 'Callable | None' = None, na_rep: 'str | None' = None, names: 'bool' = False, space: 'int' = 2, sparsify=None, adjoin: 'bool' = True) -> 'list' |
|
from_arrays(arrays, sortorder: 'int | None' = None, names: 'Sequence[Hashable] | Hashable | lib.NoDefault' = <no_default>) -> 'MultiIndex' |
|
from_frame(df: 'DataFrame', sortorder: 'int | None' = None, names: 'Sequence[Hashable] | Hashable | None' = None) -> 'MultiIndex' |
|
from_product(iterables: 'Sequence[Iterable[Hashable]]', sortorder: 'int | None' = None, names: 'Sequence[Hashable] | Hashable | lib.NoDefault' = <no_default>) -> 'MultiIndex' |
|
from_tuples(tuples: 'Iterable[tuple[Hashable, ...]]', sortorder: 'int | None' = None, names: 'Sequence[Hashable] | Hashable | None' = None) -> 'MultiIndex' |
|
get_level_values(self, level) -> 'Index' |
|
get_loc(self, key) |
|
get_loc_level(self, key, level: 'IndexLabel' = 0, drop_level: 'bool' = True) |
|
get_locs(self, seq) -> 'npt.NDArray[np.intp]' |
|
get_slice_bound(self, label: 'Hashable | Sequence[Hashable]', side: "Literal['left', 'right']") -> 'int' |
|
insert(self, loc: 'int', item) -> 'MultiIndex' |
|
isin(self, values, level=None) -> 'npt.NDArray[np.bool_]' |
|
memory_usage(self, deep: 'bool' = False) -> 'int' |
|
putmask(self, mask, value: 'MultiIndex') -> 'MultiIndex' |
|
remove_unused_levels(self) -> 'MultiIndex' |
|
reorder_levels(self, order) -> 'MultiIndex' |
|
repeat(self, repeats: 'int', axis=None) -> 'MultiIndex' |
|
set_codes(self, codes, *, level=None, verify_integrity: 'bool' = True) -> 'MultiIndex' |
|
set_levels(self, levels, *, level=None, verify_integrity: 'bool' = True) -> 'MultiIndex' |
|
slice_locs(self, start=None, end=None, step=None) -> 'tuple[int, int]' |
|
sortlevel(self, level: 'IndexLabel' = 0, ascending: 'bool | list[bool]' = True, sort_remaining: 'bool' = True, na_position: 'str' = 'first') -> 'tuple[MultiIndex, npt.NDArray[np.intp]]' |
|
swaplevel(self, i=-2, j=-1) -> 'MultiIndex' |
|
take(self: 'MultiIndex', indices, axis: 'Axis' = 0, allow_fill: 'bool' = True, fill_value=None, **kwargs) -> 'MultiIndex' |
|
to_flat_index(self) -> 'Index' |
|
to_frame(self, index: 'bool' = True, name=<no_default>, allow_duplicates: 'bool' = False) -> 'DataFrame' |
|
truncate(self, before=None, after=None) -> 'MultiIndex' |
|
unique(self, level=None) |
|
view(self, cls=None) -> 'Self' |
this is defined as a copy with the same identity [extrait de view.__doc__] |
Méthodes héritées de la classe Index
__abs__, __array_ufunc__, __array_wrap__, __bool__, __copy__, __deepcopy__, __init_subclass__, __nonzero__, __repr__, __subclasshook__, all, any, argmax, argmin, asof, asof_locs, diff, difference, drop_duplicates, droplevel, get_indexer, get_indexer_for, get_indexer_non_unique, groupby, holds_integer, identical, infer_objects, intersection, is_, is_boolean, is_categorical, is_floating, is_integer, is_interval, is_numeric, is_object, isna, isnull, join, map, max, min, notna, notnull, ravel, reindex, rename, round, set_names, shift, slice_indexer, sort, sort_values, symmetric_difference, to_series, union, where
Méthodes héritées de la classe PandasObject
__sizeof__
Méthodes héritées de la classe DirNamesMixin
__dir__
Méthodes héritées de la classe IndexOpsMixin
__iter__, factorize, item, nunique, searchsorted, to_list, to_numpy, tolist, transpose, value_counts
Méthodes héritées de la classe OpsMixin
__divmod__, __rdivmod__
Méthodes héritées de la classe object
__delattr__,
__format__,
__getattribute__,
__getstate__,
__hash__,
__reduce_ex__,
__setattr__,
__str__
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