@@ -58,27 +58,6 @@ library, making their behavior more consistent with the handling of
5858NumPy arrays. We'll do this by cleaning up pandas' internals and
5959adding new methods to the extension array interface.
6060
61- ### String data type
62-
63- Currently, pandas stores text data in an ` object ` -dtype NumPy array.
64- The current implementation has two primary drawbacks: First, ` object `
65- -dtype is not specific to strings: any Python object can be stored in an
66- ` object ` -dtype array, not just strings. Second: this is not efficient.
67- The NumPy memory model isn't especially well-suited to variable width
68- text data.
69-
70- To solve the first issue, we propose a new extension type for string
71- data. This will initially be opt-in, with users explicitly requesting
72- ` dtype="string" ` . The array backing this string dtype may initially be
73- the current implementation: an ` object ` -dtype NumPy array of Python
74- strings.
75-
76- To solve the second issue (performance), we'll explore alternative
77- in-memory array libraries (for example, Apache Arrow). As part of the
78- work, we may need to implement certain operations expected by pandas
79- users (for example the algorithm used in, ` Series.str.upper ` ). That work
80- may be done outside of pandas.
81-
8261### Apache Arrow interoperability
8362
8463[ Apache Arrow] ( https://arrow.apache.org ) is a cross-language development
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