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.
Parameters:
data: array-like (1-dimensional)
An array-like structure containing the data for the index. This could be a Python list, a NumPy array, or a pandas Series.
dtype: str, numpy.dtype, or ExtensionDtype, optional
Data type for the output Index. If not specified, this will be inferred from data. See the user guide for more usages.
copy: bool, default None
Whether to copy input data, only relevant for array, Series, and Index inputs (for other input, e.g. a list, a new array is created anyway). Defaults to True for array input and False for Index/Series. Set to False to avoid copying array input at your own risk (if you know the input data won’t be modified elsewhere). Set to True to force copying Series/Index input up front.
name: object
Name to be stored in the index.
tupleize_cols: bool (default: True)
When True, attempt to create a MultiIndex if possible.
See also:
RangeIndex
Index implementing a monotonic integer range.
CategoricalIndex
Index of Categorical s.
MultiIndex
A multi-level, or hierarchical Index.
IntervalIndex
An Index of Interval s.
DatetimeIndex
Index of datetime64 data.
TimedeltaIndex
Index of timedelta64 data.
PeriodIndex
Index of Period data.
Notes:
An Index instance can only contain hashable objects. An Index instance can not hold numpy float16 dtype.