doc_content stringlengths 1 386k | doc_id stringlengths 5 188 |
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pandas.Index.append Index.append(other)[source]
Append a collection of Index options together. Parameters
other:Index or list/tuple of indices
Returns
Index | pandas.reference.api.pandas.index.append |
pandas.Index.argmax Index.argmax(axis=None, skipna=True, *args, **kwargs)[source]
Return int position of the largest value in the Series. If the maximum is achieved in multiple locations, the first row position is returned. Parameters
axis:{None}
Dummy argument for consistency with Series.
skipna:bool, defa... | pandas.reference.api.pandas.index.argmax |
pandas.Index.argmin Index.argmin(axis=None, skipna=True, *args, **kwargs)[source]
Return int position of the smallest value in the Series. If the minimum is achieved in multiple locations, the first row position is returned. Parameters
axis:{None}
Dummy argument for consistency with Series.
skipna:bool, def... | pandas.reference.api.pandas.index.argmin |
pandas.Index.argsort Index.argsort(*args, **kwargs)[source]
Return the integer indices that would sort the index. Parameters
*args
Passed to numpy.ndarray.argsort. **kwargs
Passed to numpy.ndarray.argsort. Returns
np.ndarray[np.intp]
Integer indices that would sort the index if used as an indexer. ... | pandas.reference.api.pandas.index.argsort |
pandas.Index.array Index.array
The ExtensionArray of the data backing this Series or Index. Returns
ExtensionArray
An ExtensionArray of the values stored within. For extension types, this is the actual array. For NumPy native types, this is a thin (no copy) wrapper around numpy.ndarray. .array differs .values w... | pandas.reference.api.pandas.index.array |
pandas.Index.asi8 propertyIndex.asi8
Integer representation of the values. Returns
ndarray
An ndarray with int64 dtype. | pandas.reference.api.pandas.index.asi8 |
pandas.Index.asof finalIndex.asof(label)[source]
Return the label from the index, or, if not present, the previous one. Assuming that the index is sorted, return the passed index label if it is in the index, or return the previous index label if the passed one is not in the index. Parameters
label:object
The ... | pandas.reference.api.pandas.index.asof |
pandas.Index.asof_locs Index.asof_locs(where, mask)[source]
Return the locations (indices) of labels in the index. As in the asof function, if the label (a particular entry in where) is not in the index, the latest index label up to the passed label is chosen and its index returned. If all of the labels in the inde... | pandas.reference.api.pandas.index.asof_locs |
pandas.Index.astype Index.astype(dtype, copy=True)[source]
Create an Index with values cast to dtypes. The class of a new Index is determined by dtype. When conversion is impossible, a TypeError exception is raised. Parameters
dtype:numpy dtype or pandas type
Note that any signed integer dtype is treated as '... | pandas.reference.api.pandas.index.astype |
pandas.Index.copy Index.copy(name=None, deep=False, dtype=None, names=None)[source]
Make a copy of this object. Name and dtype sets those attributes on the new object. Parameters
name:Label, optional
Set name for new object.
deep:bool, default False
dtype:numpy dtype or pandas type, optional
Set dtype f... | pandas.reference.api.pandas.index.copy |
pandas.Index.delete Index.delete(loc)[source]
Make new Index with passed location(-s) deleted. Parameters
loc:int or list of int
Location of item(-s) which will be deleted. Use a list of locations to delete more than one value at the same time. Returns
Index
Will be same type as self, except for RangeIn... | pandas.reference.api.pandas.index.delete |
pandas.Index.difference finalIndex.difference(other, sort=None)[source]
Return a new Index with elements of index not in other. This is the set difference of two Index objects. Parameters
other:Index or array-like
sort:False or None, default None
Whether to sort the resulting index. By default, the values a... | pandas.reference.api.pandas.index.difference |
pandas.Index.drop Index.drop(labels, errors='raise')[source]
Make new Index with passed list of labels deleted. Parameters
labels:array-like or scalar
errors:{‘ignore’, ‘raise’}, default ‘raise’
If ‘ignore’, suppress error and existing labels are dropped. Returns
dropped:Index
Will be same type as s... | pandas.reference.api.pandas.index.drop |
pandas.Index.drop_duplicates Index.drop_duplicates(keep='first')[source]
Return Index with duplicate values removed. Parameters
keep:{‘first’, ‘last’, False}, default ‘first’
‘first’ : Drop duplicates except for the first occurrence. ‘last’ : Drop duplicates except for the last occurrence. False : Drop all d... | pandas.reference.api.pandas.index.drop_duplicates |
pandas.Index.droplevel finalIndex.droplevel(level=0)[source]
Return index with requested level(s) removed. If resulting index has only 1 level left, the result will be of Index type, not MultiIndex. Parameters
level:int, str, or list-like, default 0
If a string is given, must be the name of a level If list-li... | pandas.reference.api.pandas.index.droplevel |
pandas.Index.dropna Index.dropna(how='any')[source]
Return Index without NA/NaN values. Parameters
how:{‘any’, ‘all’}, default ‘any’
If the Index is a MultiIndex, drop the value when any or all levels are NaN. Returns
Index | pandas.reference.api.pandas.index.dropna |
pandas.Index.dtype Index.dtype
Return the dtype object of the underlying data. | pandas.reference.api.pandas.index.dtype |
pandas.Index.duplicated Index.duplicated(keep='first')[source]
Indicate duplicate index values. Duplicated values are indicated as True values in the resulting array. Either all duplicates, all except the first, or all except the last occurrence of duplicates can be indicated. Parameters
keep:{‘first’, ‘last’, ... | pandas.reference.api.pandas.index.duplicated |
pandas.Index.empty propertyIndex.empty | pandas.reference.api.pandas.index.empty |
pandas.Index.equals Index.equals(other)[source]
Determine if two Index object are equal. The things that are being compared are: The elements inside the Index object. The order of the elements inside the Index object. Parameters
other:Any
The other object to compare against. Returns
bool
True if “othe... | pandas.reference.api.pandas.index.equals |
pandas.Index.factorize Index.factorize(sort=False, na_sentinel=- 1)[source]
Encode the object as an enumerated type or categorical variable. This method is useful for obtaining a numeric representation of an array when all that matters is identifying distinct values. factorize is available as both a top-level funct... | pandas.reference.api.pandas.index.factorize |
pandas.Index.fillna Index.fillna(value=None, downcast=None)[source]
Fill NA/NaN values with the specified value. Parameters
value:scalar
Scalar value to use to fill holes (e.g. 0). This value cannot be a list-likes.
downcast:dict, default is None
A dict of item->dtype of what to downcast if possible, or t... | pandas.reference.api.pandas.index.fillna |
pandas.Index.format Index.format(name=False, formatter=None, na_rep='NaN')[source]
Render a string representation of the Index. | pandas.reference.api.pandas.index.format |
pandas.Index.get_indexer finalIndex.get_indexer(target, method=None, limit=None, tolerance=None)[source]
Compute indexer and mask for new index given the current index. The indexer should be then used as an input to ndarray.take to align the current data to the new index. Parameters
target:Index
method:{None,... | pandas.reference.api.pandas.index.get_indexer |
pandas.Index.get_indexer_for finalIndex.get_indexer_for(target)[source]
Guaranteed return of an indexer even when non-unique. This dispatches to get_indexer or get_indexer_non_unique as appropriate. Returns
np.ndarray[np.intp]
List of indices. Examples
>>> idx = pd.Index([np.nan, 'var1', np.nan])
>>> idx.g... | pandas.reference.api.pandas.index.get_indexer_for |
pandas.Index.get_indexer_non_unique Index.get_indexer_non_unique(target)[source]
Compute indexer and mask for new index given the current index. The indexer should be then used as an input to ndarray.take to align the current data to the new index. Parameters
target:Index
Returns
indexer:np.ndarray[np.int... | pandas.reference.api.pandas.index.get_indexer_non_unique |
pandas.Index.get_level_values Index.get_level_values(level)[source]
Return an Index of values for requested level. This is primarily useful to get an individual level of values from a MultiIndex, but is provided on Index as well for compatibility. Parameters
level:int or str
It is either the integer position ... | pandas.reference.api.pandas.index.get_level_values |
pandas.Index.get_loc Index.get_loc(key, method=None, tolerance=None)[source]
Get integer location, slice or boolean mask for requested label. Parameters
key:label
method:{None, ‘pad’/’ffill’, ‘backfill’/’bfill’, ‘nearest’}, optional
default: exact matches only. pad / ffill: find the PREVIOUS index value if... | pandas.reference.api.pandas.index.get_loc |
pandas.Index.get_slice_bound Index.get_slice_bound(label, side, kind=NoDefault.no_default)[source]
Calculate slice bound that corresponds to given label. Returns leftmost (one-past-the-rightmost if side=='right') position of given label. Parameters
label:object
side:{‘left’, ‘right’}
kind:{‘loc’, ‘getitem’}... | pandas.reference.api.pandas.index.get_slice_bound |
pandas.Index.get_value finalIndex.get_value(series, key)[source]
Fast lookup of value from 1-dimensional ndarray. Only use this if you know what you’re doing. Returns
scalar or Series | pandas.reference.api.pandas.index.get_value |
pandas.Index.groupby finalIndex.groupby(values)[source]
Group the index labels by a given array of values. Parameters
values:array
Values used to determine the groups. Returns
dict
{group name -> group labels} | pandas.reference.api.pandas.index.groupby |
pandas.Index.has_duplicates propertyIndex.has_duplicates
Check if the Index has duplicate values. Returns
bool
Whether or not the Index has duplicate values. Examples
>>> idx = pd.Index([1, 5, 7, 7])
>>> idx.has_duplicates
True
>>> idx = pd.Index([1, 5, 7])
>>> idx.has_duplicates
False
>>> idx = pd.I... | pandas.reference.api.pandas.index.has_duplicates |
pandas.Index.hasnans Index.hasnans
Return True if there are any NaNs. Enables various performance speedups. | pandas.reference.api.pandas.index.hasnans |
pandas.Index.holds_integer finalIndex.holds_integer()[source]
Whether the type is an integer type. | pandas.reference.api.pandas.index.holds_integer |
pandas.Index.identical finalIndex.identical(other)[source]
Similar to equals, but checks that object attributes and types are also equal. Returns
bool
If two Index objects have equal elements and same type True, otherwise False. | pandas.reference.api.pandas.index.identical |
pandas.Index.inferred_type Index.inferred_type
Return a string of the type inferred from the values. | pandas.reference.api.pandas.index.inferred_type |
pandas.Index.insert Index.insert(loc, item)[source]
Make new Index inserting new item at location. Follows Python numpy.insert semantics for negative values. Parameters
loc:int
item:object
Returns
new_index:Index | pandas.reference.api.pandas.index.insert |
pandas.Index.intersection finalIndex.intersection(other, sort=False)[source]
Form the intersection of two Index objects. This returns a new Index with elements common to the index and other. Parameters
other:Index or array-like
sort:False or None, default False
Whether to sort the resulting index. False : ... | pandas.reference.api.pandas.index.intersection |
pandas.Index.is_ finalIndex.is_(other)[source]
More flexible, faster check like is but that works through views. Note: this is not the same as Index.identical(), which checks that metadata is also the same. Parameters
other:object
Other object to compare against. Returns
bool
True if both have same unde... | pandas.reference.api.pandas.index.is_ |
pandas.Index.is_all_dates Index.is_all_dates
Whether or not the index values only consist of dates. | pandas.reference.api.pandas.index.is_all_dates |
pandas.Index.is_boolean finalIndex.is_boolean()[source]
Check if the Index only consists of booleans. Returns
bool
Whether or not the Index only consists of booleans. See also is_integer
Check if the Index only consists of integers. is_floating
Check if the Index is a floating type. is_numeric
Check ... | pandas.reference.api.pandas.index.is_boolean |
pandas.Index.is_categorical finalIndex.is_categorical()[source]
Check if the Index holds categorical data. Returns
bool
True if the Index is categorical. See also CategoricalIndex
Index for categorical data. is_boolean
Check if the Index only consists of booleans. is_integer
Check if the Index only c... | pandas.reference.api.pandas.index.is_categorical |
pandas.Index.is_floating finalIndex.is_floating()[source]
Check if the Index is a floating type. The Index may consist of only floats, NaNs, or a mix of floats, integers, or NaNs. Returns
bool
Whether or not the Index only consists of only consists of floats, NaNs, or a mix of floats, integers, or NaNs. Se... | pandas.reference.api.pandas.index.is_floating |
pandas.Index.is_integer finalIndex.is_integer()[source]
Check if the Index only consists of integers. Returns
bool
Whether or not the Index only consists of integers. See also is_boolean
Check if the Index only consists of booleans. is_floating
Check if the Index is a floating type. is_numeric
Check ... | pandas.reference.api.pandas.index.is_integer |
pandas.Index.is_interval finalIndex.is_interval()[source]
Check if the Index holds Interval objects. Returns
bool
Whether or not the Index holds Interval objects. See also IntervalIndex
Index for Interval objects. is_boolean
Check if the Index only consists of booleans. is_integer
Check if the Index ... | pandas.reference.api.pandas.index.is_interval |
pandas.Index.is_mixed finalIndex.is_mixed()[source]
Check if the Index holds data with mixed data types. Returns
bool
Whether or not the Index holds data with mixed data types. See also is_boolean
Check if the Index only consists of booleans. is_integer
Check if the Index only consists of integers. is... | pandas.reference.api.pandas.index.is_mixed |
pandas.Index.is_monotonic propertyIndex.is_monotonic
Alias for is_monotonic_increasing. | pandas.reference.api.pandas.index.is_monotonic |
pandas.Index.is_monotonic_decreasing propertyIndex.is_monotonic_decreasing
Return if the index is monotonic decreasing (only equal or decreasing) values. Examples
>>> Index([3, 2, 1]).is_monotonic_decreasing
True
>>> Index([3, 2, 2]).is_monotonic_decreasing
True
>>> Index([3, 1, 2]).is_monotonic_decreasing
False | pandas.reference.api.pandas.index.is_monotonic_decreasing |
pandas.Index.is_monotonic_increasing propertyIndex.is_monotonic_increasing
Return if the index is monotonic increasing (only equal or increasing) values. Examples
>>> Index([1, 2, 3]).is_monotonic_increasing
True
>>> Index([1, 2, 2]).is_monotonic_increasing
True
>>> Index([1, 3, 2]).is_monotonic_increasing
False | pandas.reference.api.pandas.index.is_monotonic_increasing |
pandas.Index.is_numeric finalIndex.is_numeric()[source]
Check if the Index only consists of numeric data. Returns
bool
Whether or not the Index only consists of numeric data. See also is_boolean
Check if the Index only consists of booleans. is_integer
Check if the Index only consists of integers. is_f... | pandas.reference.api.pandas.index.is_numeric |
pandas.Index.is_object finalIndex.is_object()[source]
Check if the Index is of the object dtype. Returns
bool
Whether or not the Index is of the object dtype. See also is_boolean
Check if the Index only consists of booleans. is_integer
Check if the Index only consists of integers. is_floating
Check i... | pandas.reference.api.pandas.index.is_object |
pandas.Index.is_type_compatible Index.is_type_compatible(kind)[source]
Whether the index type is compatible with the provided type. | pandas.reference.api.pandas.index.is_type_compatible |
pandas.Index.is_unique Index.is_unique
Return if the index has unique values. | pandas.reference.api.pandas.index.is_unique |
pandas.Index.isin Index.isin(values, level=None)[source]
Return a boolean array where the index values are in values. Compute boolean array of whether each index value is found in the passed set of values. The length of the returned boolean array matches the length of the index. Parameters
values:set or list-li... | pandas.reference.api.pandas.index.isin |
pandas.Index.isna finalIndex.isna()[source]
Detect missing values. Return a boolean same-sized object indicating if the values are NA. NA values, such as None, numpy.NaN or pd.NaT, get mapped to True values. Everything else get mapped to False values. Characters such as empty strings ‘’ or numpy.inf are not conside... | pandas.reference.api.pandas.index.isna |
pandas.Index.isnull Index.isnull()[source]
Detect missing values. Return a boolean same-sized object indicating if the values are NA. NA values, such as None, numpy.NaN or pd.NaT, get mapped to True values. Everything else get mapped to False values. Characters such as empty strings ‘’ or numpy.inf are not consider... | pandas.reference.api.pandas.index.isnull |
pandas.Index.item Index.item()[source]
Return the first element of the underlying data as a Python scalar. Returns
scalar
The first element of %(klass)s. Raises
ValueError
If the data is not length-1. | pandas.reference.api.pandas.index.item |
pandas.Index.join finalIndex.join(other, how='left', level=None, return_indexers=False, sort=False)[source]
Compute join_index and indexers to conform data structures to the new index. Parameters
other:Index
how:{‘left’, ‘right’, ‘inner’, ‘outer’}
level:int or level name, default None
return_indexers:bool... | pandas.reference.api.pandas.index.join |
pandas.Index.map Index.map(mapper, na_action=None)[source]
Map values using an input mapping or function. Parameters
mapper:function, dict, or Series
Mapping correspondence.
na_action:{None, ‘ignore’}
If ‘ignore’, propagate NA values, without passing them to the mapping correspondence. Returns
appli... | pandas.reference.api.pandas.index.map |
pandas.Index.max Index.max(axis=None, skipna=True, *args, **kwargs)[source]
Return the maximum value of the Index. Parameters
axis:int, optional
For compatibility with NumPy. Only 0 or None are allowed.
skipna:bool, default True
Exclude NA/null values when showing the result. *args, **kwargs
Additional ... | pandas.reference.api.pandas.index.max |
pandas.Index.memory_usage Index.memory_usage(deep=False)[source]
Memory usage of the values. Parameters
deep:bool, default False
Introspect the data deeply, interrogate object dtypes for system-level memory consumption. Returns
bytes used
See also numpy.ndarray.nbytes
Total bytes consumed by the el... | pandas.reference.api.pandas.index.memory_usage |
pandas.Index.min Index.min(axis=None, skipna=True, *args, **kwargs)[source]
Return the minimum value of the Index. Parameters
axis:{None}
Dummy argument for consistency with Series.
skipna:bool, default True
Exclude NA/null values when showing the result. *args, **kwargs
Additional arguments and keyword... | pandas.reference.api.pandas.index.min |
pandas.Index.name propertyIndex.name
Return Index or MultiIndex name. | pandas.reference.api.pandas.index.name |
pandas.Index.names propertyIndex.names | pandas.reference.api.pandas.index.names |
pandas.Index.nbytes propertyIndex.nbytes
Return the number of bytes in the underlying data. | pandas.reference.api.pandas.index.nbytes |
pandas.Index.ndim propertyIndex.ndim
Number of dimensions of the underlying data, by definition 1. | pandas.reference.api.pandas.index.ndim |
pandas.Index.nlevels propertyIndex.nlevels
Number of levels. | pandas.reference.api.pandas.index.nlevels |
pandas.Index.notna finalIndex.notna()[source]
Detect existing (non-missing) values. Return a boolean same-sized object indicating if the values are not NA. Non-missing values get mapped to True. Characters such as empty strings '' or numpy.inf are not considered NA values (unless you set pandas.options.mode.use_inf... | pandas.reference.api.pandas.index.notna |
pandas.Index.notnull Index.notnull()[source]
Detect existing (non-missing) values. Return a boolean same-sized object indicating if the values are not NA. Non-missing values get mapped to True. Characters such as empty strings '' or numpy.inf are not considered NA values (unless you set pandas.options.mode.use_inf_... | pandas.reference.api.pandas.index.notnull |
pandas.Index.nunique Index.nunique(dropna=True)[source]
Return number of unique elements in the object. Excludes NA values by default. Parameters
dropna:bool, default True
Don’t include NaN in the count. Returns
int
See also DataFrame.nunique
Method nunique for DataFrame. Series.count
Count non-N... | pandas.reference.api.pandas.index.nunique |
pandas.Index.putmask finalIndex.putmask(mask, value)[source]
Return a new Index of the values set with the mask. Returns
Index
See also numpy.ndarray.putmask
Changes elements of an array based on conditional and input values. | pandas.reference.api.pandas.index.putmask |
pandas.Index.ravel finalIndex.ravel(order='C')[source]
Return an ndarray of the flattened values of the underlying data. Returns
numpy.ndarray
Flattened array. See also numpy.ndarray.ravel
Return a flattened array. | pandas.reference.api.pandas.index.ravel |
pandas.Index.reindex Index.reindex(target, method=None, level=None, limit=None, tolerance=None)[source]
Create index with target’s values. Parameters
target:an iterable
method:{None, ‘pad’/’ffill’, ‘backfill’/’bfill’, ‘nearest’}, optional
default: exact matches only. pad / ffill: find the PREVIOUS index va... | pandas.reference.api.pandas.index.reindex |
pandas.Index.rename Index.rename(name, inplace=False)[source]
Alter Index or MultiIndex name. Able to set new names without level. Defaults to returning new index. Length of names must match number of levels in MultiIndex. Parameters
name:label or list of labels
Name(s) to set.
inplace:bool, default False
... | pandas.reference.api.pandas.index.rename |
pandas.Index.repeat Index.repeat(repeats, axis=None)[source]
Repeat elements of a Index. Returns a new Index where each element of the current Index is repeated consecutively a given number of times. Parameters
repeats:int or array of ints
The number of repetitions for each element. This should be a non-negat... | pandas.reference.api.pandas.index.repeat |
pandas.Index.searchsorted Index.searchsorted(value, side='left', sorter=None)[source]
Find indices where elements should be inserted to maintain order. Find the indices into a sorted Index self such that, if the corresponding elements in value were inserted before the indices, the order of self would be preserved. ... | pandas.reference.api.pandas.index.searchsorted |
pandas.Index.set_names Index.set_names(names, level=None, inplace=False)[source]
Set Index or MultiIndex name. Able to set new names partially and by level. Parameters
names:label or list of label or dict-like for MultiIndex
Name(s) to set. Changed in version 1.3.0.
level:int, label or list of int or labe... | pandas.reference.api.pandas.index.set_names |
pandas.Index.set_value finalIndex.set_value(arr, key, value)[source]
Fast lookup of value from 1-dimensional ndarray. Deprecated since version 1.0. Notes Only use this if you know what you’re doing. | pandas.reference.api.pandas.index.set_value |
pandas.Index.shape propertyIndex.shape
Return a tuple of the shape of the underlying data. | pandas.reference.api.pandas.index.shape |
pandas.Index.shift Index.shift(periods=1, freq=None)[source]
Shift index by desired number of time frequency increments. This method is for shifting the values of datetime-like indexes by a specified time increment a given number of times. Parameters
periods:int, default 1
Number of periods (or increments) to... | pandas.reference.api.pandas.index.shift |
pandas.Index.size propertyIndex.size
Return the number of elements in the underlying data. | pandas.reference.api.pandas.index.size |
pandas.Index.slice_indexer Index.slice_indexer(start=None, end=None, step=None, kind=NoDefault.no_default)[source]
Compute the slice indexer for input labels and step. Index needs to be ordered and unique. Parameters
start:label, default None
If None, defaults to the beginning.
end:label, default None
If ... | pandas.reference.api.pandas.index.slice_indexer |
pandas.Index.slice_locs Index.slice_locs(start=None, end=None, step=None, kind=NoDefault.no_default)[source]
Compute slice locations for input labels. Parameters
start:label, default None
If None, defaults to the beginning.
end:label, default None
If None, defaults to the end.
step:int, defaults None
... | pandas.reference.api.pandas.index.slice_locs |
pandas.Index.sort finalIndex.sort(*args, **kwargs)[source]
Use sort_values instead. | pandas.reference.api.pandas.index.sort |
pandas.Index.sort_values Index.sort_values(return_indexer=False, ascending=True, na_position='last', key=None)[source]
Return a sorted copy of the index. Return a sorted copy of the index, and optionally return the indices that sorted the index itself. Parameters
return_indexer:bool, default False
Should the ... | pandas.reference.api.pandas.index.sort_values |
pandas.Index.sortlevel Index.sortlevel(level=None, ascending=True, sort_remaining=None)[source]
For internal compatibility with the Index API. Sort the Index. This is for compat with MultiIndex Parameters
ascending:bool, default True
False to sort in descending order level, sort_remaining are compat paramete... | pandas.reference.api.pandas.index.sortlevel |
pandas.Index.str Index.str()[source]
Vectorized string functions for Series and Index. NAs stay NA unless handled otherwise by a particular method. Patterned after Python’s string methods, with some inspiration from R’s stringr package. Examples
>>> s = pd.Series(["A_Str_Series"])
>>> s
0 A_Str_Series
dtype: ob... | pandas.reference.api.pandas.index.str |
pandas.Index.symmetric_difference Index.symmetric_difference(other, result_name=None, sort=None)[source]
Compute the symmetric difference of two Index objects. Parameters
other:Index or array-like
result_name:str
sort:False or None, default None
Whether to sort the resulting index. By default, the values ... | pandas.reference.api.pandas.index.symmetric_difference |
pandas.Index.T propertyIndex.T
Return the transpose, which is by definition self. | pandas.reference.api.pandas.index.t |
pandas.Index.take Index.take(indices, axis=0, allow_fill=True, fill_value=None, **kwargs)[source]
Return a new Index of the values selected by the indices. For internal compatibility with numpy arrays. Parameters
indices:array-like
Indices to be taken.
axis:int, optional
The axis over which to select valu... | pandas.reference.api.pandas.index.take |
pandas.Index.to_flat_index Index.to_flat_index()[source]
Identity method. This is implemented for compatibility with subclass implementations when chaining. Returns
pd.Index
Caller. See also MultiIndex.to_flat_index
Subclass implementation. | pandas.reference.api.pandas.index.to_flat_index |
pandas.Index.to_frame Index.to_frame(index=True, name=NoDefault.no_default)[source]
Create a DataFrame with a column containing the Index. Parameters
index:bool, default True
Set the index of the returned DataFrame as the original Index.
name:object, default None
The passed name should substitute for the ... | pandas.reference.api.pandas.index.to_frame |
pandas.Index.to_list Index.to_list()[source]
Return a list of the values. These are each a scalar type, which is a Python scalar (for str, int, float) or a pandas scalar (for Timestamp/Timedelta/Interval/Period) Returns
list
See also numpy.ndarray.tolist
Return the array as an a.ndim-levels deep nested lis... | pandas.reference.api.pandas.index.to_list |
pandas.Index.to_native_types finalIndex.to_native_types(slicer=None, **kwargs)[source]
Format specified values of self and return them. Deprecated since version 1.2.0. Parameters
slicer:int, array-like
An indexer into self that specifies which values are used in the formatting process.
kwargs:dict
Optio... | pandas.reference.api.pandas.index.to_native_types |
pandas.Index.to_numpy Index.to_numpy(dtype=None, copy=False, na_value=NoDefault.no_default, **kwargs)[source]
A NumPy ndarray representing the values in this Series or Index. Parameters
dtype:str or numpy.dtype, optional
The dtype to pass to numpy.asarray().
copy:bool, default False
Whether to ensure that... | pandas.reference.api.pandas.index.to_numpy |
pandas.Index.to_series Index.to_series(index=None, name=None)[source]
Create a Series with both index and values equal to the index keys. Useful with map for returning an indexer based on an index. Parameters
index:Index, optional
Index of resulting Series. If None, defaults to original index.
name:str, opt... | pandas.reference.api.pandas.index.to_series |
pandas.Index.tolist Index.tolist()[source]
Return a list of the values. These are each a scalar type, which is a Python scalar (for str, int, float) or a pandas scalar (for Timestamp/Timedelta/Interval/Period) Returns
list
See also numpy.ndarray.tolist
Return the array as an a.ndim-levels deep nested list ... | pandas.reference.api.pandas.index.tolist |
pandas.Index.transpose Index.transpose(*args, **kwargs)[source]
Return the transpose, which is by definition self. Returns
%(klass)s | pandas.reference.api.pandas.index.transpose |
pandas.Index.union finalIndex.union(other, sort=None)[source]
Form the union of two Index objects. If the Index objects are incompatible, both Index objects will be cast to dtype(‘object’) first.
Changed in version 0.25.0.
Parameters
other:Index or array-like
sort:bool or None, default None
Whether to... | pandas.reference.api.pandas.index.union |
pandas.Index.unique Index.unique(level=None)[source]
Return unique values in the index. Unique values are returned in order of appearance, this does NOT sort. Parameters
level:int or hashable, optional
Only return values from specified level (for MultiIndex). If int, gets the level by integer position, else b... | pandas.reference.api.pandas.index.unique |
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