coalispr.resources.numeric

Classes

NumericIndex

Immutable sequence used for indexing and alignment.

IntegerIndex

Immutable sequence used for indexing and alignment.

Int64Index

Immutable sequence used for indexing and alignment.

UInt64Index

Immutable sequence used for indexing and alignment.

Float64Index

Immutable sequence used for indexing and alignment.

Module Contents

class coalispr.resources.numeric.NumericIndex

Bases: pandas.core.indexes.base.Index

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))

  • 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 False) – Copy input data.

  • 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.

Examples

>>> pd.Index([1, 2, 3])
Index([1, 2, 3], dtype='int64')

>>> pd.Index(list('abc'))
Index(['a', 'b', 'c'], dtype='object')

>>> pd.Index([1, 2, 3], dtype="uint8")
Index([1, 2, 3], dtype='uint8')
class coalispr.resources.numeric.IntegerIndex

Bases: NumericIndex

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))

  • 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 False) – Copy input data.

  • 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.

Examples

>>> pd.Index([1, 2, 3])
Index([1, 2, 3], dtype='int64')

>>> pd.Index(list('abc'))
Index(['a', 'b', 'c'], dtype='object')

>>> pd.Index([1, 2, 3], dtype="uint8")
Index([1, 2, 3], dtype='uint8')
class coalispr.resources.numeric.Int64Index

Bases: IntegerIndex

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))

  • 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 False) – Copy input data.

  • 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.

Examples

>>> pd.Index([1, 2, 3])
Index([1, 2, 3], dtype='int64')

>>> pd.Index(list('abc'))
Index(['a', 'b', 'c'], dtype='object')

>>> pd.Index([1, 2, 3], dtype="uint8")
Index([1, 2, 3], dtype='uint8')
class coalispr.resources.numeric.UInt64Index

Bases: IntegerIndex

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))

  • 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 False) – Copy input data.

  • 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.

Examples

>>> pd.Index([1, 2, 3])
Index([1, 2, 3], dtype='int64')

>>> pd.Index(list('abc'))
Index(['a', 'b', 'c'], dtype='object')

>>> pd.Index([1, 2, 3], dtype="uint8")
Index([1, 2, 3], dtype='uint8')
class coalispr.resources.numeric.Float64Index

Bases: NumericIndex

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))

  • 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 False) – Copy input data.

  • 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.

Examples

>>> pd.Index([1, 2, 3])
Index([1, 2, 3], dtype='int64')

>>> pd.Index(list('abc'))
Index(['a', 'b', 'c'], dtype='object')

>>> pd.Index([1, 2, 3], dtype="uint8")
Index([1, 2, 3], dtype='uint8')