Immutable sequence used for indexing and alignment.
The basic object storing axis labels for all pandas objects.
Changed in version 2.0.0: Index can hold all numpy numeric dtypes (except float16). Previously only int64/uint64/float64 dtypes were accepted.
An Index instance can only contain hashable objects. An Index instance can not hold numpy float16 dtype.
all(*args, **kwargs)
Return whether all elements are Truthy.
any(*args, **kwargs)
Return whether any element is Truthy.
append(other)
Append a collection of Index options together.
argmax([axis, skipna])
Return int position of the largest value in the Series.
argmin([axis, skipna])
Return int position of the smallest value in the Series.
argsort(*args, **kwargs)
Return the integer indices that would sort the index.
asof(label)
Return the label from the index, or, if not present, the previous one.
asof_locs(where, mask)
Return the locations (indices) of labels in the index.
astype(dtype[, copy])
Create an Index with values cast to dtypes.
copy([name, deep])
Make a copy of this object.
delete(loc)
Make new Index with passed location(-s) deleted.
diff([periods])
Computes the difference between consecutive values in the Index object.
difference(other[, sort])
Return a new Index with elements of index not in other.
drop(labels[, errors])
Make new Index with passed list of labels deleted.
drop_duplicates(*[, keep])
Return Index with duplicate values removed.
droplevel([level])
Return index with requested level(s) removed.
dropna([how])
Return Index without NA/NaN values.
duplicated([keep])
Indicate duplicate index values.
equals(other)
Determine if two Index object are equal.
factorize([sort, use_na_sentinel])
Encode the object as an enumerated type or categorical variable.
fillna(value)
Fill NA/NaN values with the specified value.
get_indexer(target[, method, limit, tolerance])
Compute indexer and mask for new index given the current index.
get_indexer_for(target)
Guaranteed return of an indexer even when non-unique.
get_indexer_non_unique(target)
Compute indexer and mask for new index given the current index.
get_level_values(level)
Return an Index of values for requested level.
get_loc(key)
Get integer location, slice or boolean mask for requested label.
get_slice_bound(label, side)
Calculate slice bound that corresponds to given label.
groupby(values)
Group the index labels by a given array of values.
identical(other)
Similar to equals, but checks that object attributes and types are also equal.
infer_objects([copy])
If we have an object dtype, try to infer a non-object dtype.
insert(loc, item)
Make new Index inserting new item at location.
intersection(other[, sort])
Form the intersection of two Index objects.
is_(other)
More flexible, faster check like is but that works through views.
isin(values[, level])
Return a boolean array where the index values are in values.
isna()
Detect missing values.
isnull()
Detect missing values.
item()
Return the first element of the underlying data as a Python scalar.
join(other, *[, how, level, ...])
Compute join_index and indexers to conform data structures to the new index.
map(mapper[, na_action])
Map values using an input mapping or function.
max([axis, skipna])
Return the maximum value of the Index.
memory_usage([deep])
Memory usage of the values.
min([axis, skipna])
Return the minimum value of the Index.
notna()
Detect existing (non-missing) values.
notnull()
Detect existing (non-missing) values.
nunique([dropna])
Return number of unique elements in the object.
putmask(mask, value)
Return a new Index of the values set with the mask.
ravel([order])
Return a view on self.
reindex(target[, method, level, limit, ...])
Create index with target's values.
rename(name, *[, inplace])
Alter Index or MultiIndex name.
repeat(repeats[, axis])
Repeat elements of a Index.
round([decimals])
Round each value in the Index to the given number of decimals.
searchsorted(value[, side, sorter])
Find indices where elements should be inserted to maintain order.
set_names(names, *[, level, inplace])
Set Index or MultiIndex name.
shift([periods, freq])
Shift index by desired number of time frequency increments.
slice_indexer([start, end, step])
Compute the slice indexer for input labels and step.
slice_locs([start, end, step])
Compute slice locations for input labels.
sort_values(*[, return_indexer, ascending, ...])
Return a sorted copy of the index.
sortlevel([level, ascending, ...])
For internal compatibility with the Index API.
symmetric_difference(other[, result_name, sort])
Compute the symmetric difference of two Index objects.
take(indices[, axis, allow_fill, fill_value])
Return a new Index of the values selected by the indices.
to_flat_index()
Identity method.
to_frame([index, name])
Create a DataFrame with a column containing the Index.
to_list()
Return a list of the values.
to_numpy([dtype, copy, na_value])
A NumPy ndarray representing the values in this Series or Index.
to_series([index, name])
Create a Series with both index and values equal to the index keys.
tolist()
Return a list of the values.
transpose(*args, **kwargs)
Return the transpose, which is by definition self.
union(other[, sort])
Form the union of two Index objects.
unique([level])
Return unique values in the index.
value_counts([normalize, sort, ascending, ...])
Return a Series containing counts of unique values.
view([cls])
Return a view of the Index with the specified dtype or a new Index instance.
where(cond[, other])
Replace values where the condition is False.
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