pandas.Index

class pandas.Index

Immutable ndarray implementing an ordered, sliceable set. The basic object storing axis labels for all pandas objects

Parameters :

data : array-like (1-dimensional)

dtype : NumPy dtype (default: object)

copy : bool

Make a copy of input ndarray

name : object

Name to be stored in the index

tupleize_cols : bool (default: True)

When True, attempt to create a MultiIndex if possible

Notes

An Index instance can only contain hashable objects

Attributes

T	Same as self.transpose(), except that self is returned if self.ndim < 2.
base	Base object if memory is from some other object.
ctypes	An object to simplify the interaction of the array with the ctypes module.
data	Python buffer object pointing to the start of the array’s data.
flags
flat	A 1-D iterator over the array.
imag	The imaginary part of the array.
is_monotonic
itemsize	Length of one array element in bytes.
names
nbytes	Total bytes consumed by the elements of the array.
ndim	Number of array dimensions.
nlevels
real	The real part of the array.
shape	Tuple of array dimensions.
size	Number of elements in the array.
strides	Tuple of bytes to step in each dimension when traversing an array.
values

asi8
dtype
inferred_type
is_all_dates
is_unique
name

Methods

all([axis, out])	Returns True if all elements evaluate to True.
any([axis, out])	Returns True if any of the elements of a evaluate to True.
append(other)	Append a collection of Index options together
argmax([axis, out])	Return indices of the maximum values along the given axis.
argmin([axis, out])	Return indices of the minimum values along the given axis of a.
argpartition(kth[, axis, kind, order])	Returns the indices that would partition this array.
argsort(*args, **kwargs)	See docstring for ndarray.argsort
asof(label)	For a sorted index, return the most recent label up to and including the passed label.
asof_locs(where, mask)	where : array of timestamps
astype(dtype)
byteswap(inplace)	Swap the bytes of the array elements
choose(choices[, out, mode])	Use an index array to construct a new array from a set of choices.
clip(a_min, a_max[, out])	Return an array whose values are limited to [a_min, a_max].
compress(condition[, axis, out])	Return selected slices of this array along given axis.
conj()	Complex-conjugate all elements.
conjugate()	Return the complex conjugate, element-wise.
copy([names, name, dtype, deep])	Make a copy of this object.
cumprod([axis, dtype, out])	Return the cumulative product of the elements along the given axis.
cumsum([axis, dtype, out])	Return the cumulative sum of the elements along the given axis.
delete(loc)	Make new Index with passed location(-s) deleted
diagonal([offset, axis1, axis2])	Return specified diagonals.
diff(other)	Compute sorted set difference of two Index objects
dot(b[, out])	Dot product of two arrays.
drop(labels)	Make new Index with passed list of labels deleted
dump(file)	Dump a pickle of the array to the specified file.
dumps()	Returns the pickle of the array as a string.
equals(other)	Determines if two Index objects contain the same elements.
factorize([sort, na_sentinel])	Encode the object as an enumerated type or categorical variable
fill(*args, **kwargs)	This method will not function because object is immutable.
flatten([order])	Return a copy of the array collapsed into one dimension.
format([name, formatter])	Render a string representation of the Index
get_duplicates()
get_indexer(target[, method, limit])	Compute indexer and mask for new index given the current index.
get_indexer_for(target, **kwargs)	guaranteed return of an indexer even when non-unique
get_indexer_non_unique(target, **kwargs)	return an indexer suitable for taking from a non unique index
get_level_values(level)	Return vector of label values for requested level, equal to the length
get_loc(key)	Get integer location for requested label
get_value(series, key)	Fast lookup of value from 1-dimensional ndarray.
get_values()
getfield(dtype[, offset])	Returns a field of the given array as a certain type.
groupby(to_groupby)
holds_integer()
identical(other)	Similar to equals, but check that other comparable attributes are
insert(loc, item)	Make new Index inserting new item at location. Follows
intersection(other)	Form the intersection of two Index objects. Sortedness of the result is
is_(other)	More flexible, faster check like is but that works through views
is_floating()
is_integer()
is_lexsorted_for_tuple(tup)
is_mixed()
is_numeric()
is_type_compatible(typ)
isin(values)	Compute boolean array of whether each index value is found in the
item(*args)	Copy an element of an array to a standard Python scalar and return it.
itemset(*args, **kwargs)	This method will not function because object is immutable.
join(other[, how, level, return_indexers])	Internal API method. Compute join_index and indexers to conform data
map(mapper)
max()	The maximum value of the object
mean([axis, dtype, out])	Returns the average of the array elements along given axis.
min()	The minimum value of the object
newbyteorder([new_order])	Return the array with the same data viewed with a different byte order.
nonzero()	Return the indices of the elements that are non-zero.
nunique([dropna])	Return number of unique elements in the object.
order([return_indexer, ascending])	Return sorted copy of Index
partition(kth[, axis, kind, order])	Rearranges the elements in the array in such a way that value of the element in kth position is in the position it would be in a sorted array.
prod([axis, dtype, out])	Return the product of the array elements over the given axis
ptp([axis, out])	Peak to peak (maximum - minimum) value along a given axis.
put(*args, **kwargs)	This method will not function because object is immutable.
ravel([order])	Return a flattened array.
reindex(target[, method, level, limit, ...])	For Index, simply returns the new index and the results of
rename(name[, inplace])	Set new names on index.
repeat(repeats[, axis])	Repeat elements of an array.
reshape(shape[, order])	Returns an array containing the same data with a new shape.
resize(new_shape[, refcheck])	Change shape and size of array in-place.
round([decimals, out])	Return a with each element rounded to the given number of decimals.
searchsorted(v[, side, sorter])	Find indices where elements of v should be inserted in a to maintain order.
set_names(names[, inplace])	Set new names on index.
set_value(arr, key, value)	Fast lookup of value from 1-dimensional ndarray.
setfield(val, dtype[, offset])	Put a value into a specified place in a field defined by a data-type.
setflags([write, align, uic])	Set array flags WRITEABLE, ALIGNED, and UPDATEIFCOPY, respectively.
shift([periods, freq])	Shift Index containing datetime objects by input number of periods and
slice_indexer([start, end, step])	For an ordered Index, compute the slice indexer for input labels and
slice_locs([start, end])	For an ordered Index, compute the slice locations for input labels
sort(*args, **kwargs)
squeeze([axis])	Remove single-dimensional entries from the shape of a.
std([axis, dtype, out, ddof])	Returns the standard deviation of the array elements along given axis.
sum([axis, dtype, out])	Return the sum of the array elements over the given axis.
summary([name])
swapaxes(axis1, axis2)	Return a view of the array with axis1 and axis2 interchanged.
sym_diff(other[, result_name])	Compute the sorted symmetric difference of two Index objects.
take(indexer[, axis])	Analogous to ndarray.take
to_datetime([dayfirst])	For an Index containing strings or datetime.datetime objects, attempt
to_native_types([slicer])	slice and dice then format
to_series([keep_tz])	Create a Series with both index and values equal to the index keys
tofile(fid[, sep, format])	Write array to a file as text or binary (default).
tolist()	Overridden version of ndarray.tolist
tostring([order])	Construct a Python string containing the raw data bytes in the array.
trace([offset, axis1, axis2, dtype, out])	Return the sum along diagonals of the array.
transpose(*axes)	Returns a view of the array with axes transposed.
union(other)	Form the union of two Index objects and sorts if possible
unique()	Return array of unique values in the object.
value_counts([normalize, sort, ascending, ...])	Returns object containing counts of unique values.
var([axis, dtype, out, ddof])	Returns the variance of the array elements, along given axis.
view(*args, **kwargs)