Module « pandas »
Classe « MultiIndex »
Informations générales
Héritage
builtins.object
DirNamesMixin
PandasObject
builtins.object
OpsMixin
IndexOpsMixin
Index
MultiIndex
Définition
class MultiIndex(Index):
Description [extrait de MultiIndex.__doc__]
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.
.. versionadded:: 0.24.0
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
Methods
-------
from_arrays
from_tuples
from_product
from_frame
set_levels
set_codes
to_frame
to_flat_index
is_lexsorted
sortlevel
droplevel
swaplevel
reorder_levels
remove_unused_levels
get_locs
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)
Liste des attributs statiques
dtype | <pandas._libs.properties.CachedProperty object at 0x7f504b717780> |
hasnans | <pandas._libs.properties.CachedProperty object at 0x7f504bd34d40> |
inferred_type | <pandas._libs.properties.CachedProperty object at 0x7f504b717a40> |
is_all_dates | <pandas._libs.properties.CachedProperty object at 0x7f504bd34c40> |
is_monotonic_decreasing | <pandas._libs.properties.CachedProperty object at 0x7f504b717b80> |
is_monotonic_increasing | <pandas._libs.properties.CachedProperty object at 0x7f504b717b00> |
is_unique | <pandas._libs.properties.CachedProperty object at 0x7f504bd34880> |
levels | <pandas._libs.properties.CachedProperty object at 0x7f504b7175c0> |
lexsort_depth | <pandas._libs.properties.CachedProperty object at 0x7f504b717cc0> |
nbytes | <pandas._libs.properties.CachedProperty object at 0x7f504b7178c0> |
Attributs statiques hérités de la classe Index
array
Liste des propriétés
array | |
asi8 | |
codes | |
empty | |
has_duplicates | |
is_monotonic | |
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
__and__, __iadd__, __inv__, __neg__, __or__, __pos__, __setitem__, __xor__
Opérateurs hérités de la classe OpsMixin
__add__, __eq__, __floordiv__, __ge__, __gt__, __le__, __lt__, __mod__, __mul__, __ne__, __pow__, __radd__, __rand__, __rfloordiv__, __rmod__, __rmul__, __ror__, __rpow__, __rsub__, __rtruediv__, __rxor__, __sub__, __truediv__
Liste des méthodes
Toutes les méthodes
Méthodes d'instance
Méthodes statiques
Méthodes dépréciées
__array__(self, dtype=None) -> numpy.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, **kwargs) -> numpy.ndarray |
|
astype(self, dtype, copy=True) |
|
copy(self, names=None, dtype=None, levels=None, codes=None, deep=False, name=None) |
|
delete(self, loc) |
|
difference(self, other, sort=None) |
|
drop(self, codes, level=None, errors='raise') |
|
dropna(self, how='any') |
|
duplicated(self, keep='first') |
|
equal_levels(self, other) -> bool |
|
equals(self, other: object) -> bool |
|
fillna(self, value=None, downcast=None) |
|
format(self, name: Optional[bool] = None, formatter: Optional[Callable] = None, na_rep: Optional[str] = None, names: bool = False, space: int = 2, sparsify=None, adjoin: bool = True) -> List |
|
from_arrays(arrays, sortorder=None, names=<object object at 0x7f5051439e10>) -> 'MultiIndex' |
|
from_frame(df, sortorder=None, names=None) |
|
from_product(iterables, sortorder=None, names=<object object at 0x7f5051439e10>) |
|
from_tuples(tuples, sortorder: Optional[int] = None, names: Optional[Sequence[Optional[Hashable]]] = None) |
|
get_indexer(self, target, method=None, limit=None, tolerance=None) |
|
get_level_values(self, level) |
|
get_loc(self, key, method=None) |
|
get_loc_level(self, key, level=0, drop_level: bool = True) |
|
get_locs(self, seq) |
|
get_slice_bound(self, label: Union[Hashable, Sequence[Hashable]], side: str, kind: str) -> int |
|
insert(self, loc: int, item) |
|
intersection(self, other, sort=False) |
|
is_lexsorted(self) -> bool |
|
isin(self, values, level=None) |
|
memory_usage(self, deep: bool = False) -> int |
|
reindex(self, target, method=None, level=None, limit=None, tolerance=None) |
|
remove_unused_levels(self) |
|
reorder_levels(self, order) |
|
repeat(self, repeats, axis=None) |
|
set_codes(self, codes, level=None, inplace=None, verify_integrity=True) |
|
set_levels(self, levels, level=None, inplace=None, verify_integrity=True) |
|
slice_locs(self, start=None, end=None, step=None, kind=None) |
|
sortlevel(self, level=0, ascending=True, sort_remaining=True) |
|
swaplevel(self, i=-2, j=-1) |
|
symmetric_difference(self, other, result_name=None, sort=None) |
|
take(self, indices, axis=0, allow_fill=True, fill_value=None, **kwargs) |
|
to_flat_index(self) |
|
to_frame(self, index=True, name=None) |
|
truncate(self, before=None, after=None) |
|
union(self, other, sort=None) |
|
unique(self, level=None) |
|
view(self, cls=None) |
this is defined as a copy with the same identity [extrait de view.__doc__] |
where(self, cond, other=None) |
|
Méthodes héritées de la classe Index
__abs__, __array_wrap__, __bool__, __copy__, __deepcopy__, __hash__, __init_subclass__, __nonzero__, __repr__, __subclasshook__, all, any, asof, asof_locs, drop_duplicates, droplevel, get_indexer_for, get_indexer_non_unique, get_value, groupby, holds_integer, identical, is_, is_boolean, is_categorical, is_floating, is_integer, is_interval, is_mixed, is_numeric, is_object, is_type_compatible, isna, isnull, join, map, notna, notnull, putmask, ravel, rename, set_names, set_value, shift, slice_indexer, sort, sort_values, to_native_types, to_series
Méthodes héritées de la classe PandasObject
__sizeof__
Méthodes héritées de la classe DirNamesMixin
__dir__
Méthodes héritées de la classe IndexOpsMixin
__iter__, argmax, argmin, factorize, item, max, min, 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__,
__reduce_ex__,
__setattr__,
__str__
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