pandas.arrays.IntegerArray

class pandas.arrays.IntegerArray(values, mask, copy=False)

Array of integer (optional missing) values.

New in version 0.24.0.

Warning

IntegerArray is currently experimental, and its API or internal implementation may change without warning.

We represent an IntegerArray with 2 numpy arrays:

• data: contains a numpy integer array of the appropriate dtype
• mask: a boolean array holding a mask on the data, True is missing

To construct an IntegerArray from generic array-like input, use pandas.array() with one of the integer dtypes (see examples).

See Nullable Integer Data Type for more.

Parameters:

values : numpy.ndarray

A 1-d integer-dtype array.

mask : numpy.ndarray

A 1-d boolean-dtype array indicating missing values.

copy : bool, default False

Whether to copy the values and mask.

Returns:

IntegerArray

Examples

Create an IntegerArray with pandas.array().

>>> int_array = pd.array([1, None, 3], dtype=pd.Int32Dtype())
>>> int_array
<IntegerArray>
[1, NaN, 3]
Length: 3, dtype: Int32

String aliases for the dtypes are also available. They are capitalized.

>>> pd.array([1, None, 3], dtype='Int32')
<IntegerArray>
[1, NaN, 3]
Length: 3, dtype: Int32

>>> pd.array([1, None, 3], dtype='UInt16')
<IntegerArray>
[1, NaN, 3]
Length: 3, dtype: UInt16

Attributes

nbytes	The number of bytes needed to store this object in memory.
ndim	Extension Arrays are only allowed to be 1-dimensional.
shape	Return a tuple of the array dimensions.

dtype

Methods

argsort([ascending, kind])	Return the indices that would sort this array.
astype(dtype[, copy])	Cast to a NumPy array or IntegerArray with ‘dtype’.
copy([deep])	Return a copy of the array.
dropna()	Return ExtensionArray without NA values
factorize([na_sentinel])	Encode the extension array as an enumerated type.
fillna([value, method, limit])	Fill NA/NaN values using the specified method.
isna()	A 1-D array indicating if each value is missing.
repeat(repeats[, axis])	Repeat elements of a ExtensionArray.
searchsorted(value[, side, sorter])	Find indices where elements should be inserted to maintain order.
shift([periods, fill_value])	Shift values by desired number.
take(indexer[, allow_fill, fill_value])	Take elements from an array.
unique()	Compute the ExtensionArray of unique values.
value_counts([dropna])	Returns a Series containing counts of each category.