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pandas, issue, tomaugspurger, data, pyarrow, maartenbreddels, sign, import, pickle, commented, parquet, string, type, projects, serialize, closed, added, mroeschke, navigation, pull, requests, actions, security, enh, view, arrowstringarray, mrocklin, subset, abcdefghijklmnopqrstuvwxyz, pieces, enhancement, triage, reviewed, team, member, contributor, upstream, lenpickledumpsa, work, arrowbacked, feather, strings, extension, readpickle, topickle, arrow, functionality, github, milestone, footer,

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/vaexio/vaex/blob/caed2cf106007c6a0141a02a5dfdf823fa38799e/packages/vaex-core/vaex/arrow/convert org/jira/browse/arrow-10739 arrow-backed data string data type arrow-backed array personal information enh pandas serializes views upstream pyarrow issue comment metadata assignees tomaugspurger closed string[pyarrow] type projects fastest version/workaround import pandas pandas dataframes tomaugspurger reopened import pyarrow pyarrow side projects milestone triage issue pandas nice sharing underlying technologies milestone relationships import pickle serialize view small pieces to_pickle pickling subset issue //github github array upstream //issues workaround version pickle serialize subset pieces sign skip jump arrowstringarrays serailizing thing pd = pd series

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DiscussionForumPosting:
      context:https://schema.org
      headline:ENH: Serialize view of ArrowStringArray
      articleBody:Currently Pandas serializes views of ArrowStringArrays by serailizing the whole thing, rather than a subset. Here is an example: ```python In [1]: import pandas as pd In [2]: s = pd.Series([c * 1000 for c in "abcdefghijklmnopqrstuvwxyz"]) In [3]: s Out[3]: 0 aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa... 1 bbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbb... 2 cccccccccccccccccccccccccccccccccccccccccccccc... 3 dddddddddddddddddddddddddddddddddddddddddddddd... 4 eeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeee... 5 ffffffffffffffffffffffffffffffffffffffffffffff... 6 gggggggggggggggggggggggggggggggggggggggggggggg... 7 hhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhh... 8 iiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiii... 9 jjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjj... 10 kkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkk... 11 llllllllllllllllllllllllllllllllllllllllllllll... 12 mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm... 13 nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn... 14 oooooooooooooooooooooooooooooooooooooooooooooo... 15 pppppppppppppppppppppppppppppppppppppppppppppp... 16 qqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqq... 17 rrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrr... 18 ssssssssssssssssssssssssssssssssssssssssssssss... 19 tttttttttttttttttttttttttttttttttttttttttttttt... 20 uuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuu... 21 vvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvv... 22 wwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwww... 23 xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx... 24 yyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyy... 25 zzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzz... dtype: object In [4]: import pickle In [5]: len(pickle.dumps(s)) Out[5]: 26758 In [6]: len(pickle.dumps(s.astype("string[pyarrow]"))) Out[6]: 26891 In [7]: len(pickle.dumps(s.head(5))) Out[7]: 5632 In [8]: len(pickle.dumps(s.astype("string[pyarrow]").head(5))) Out[8]: 26891 ``` This negatively affects dask dataframe operations that cut up pandas dataframes into small pieces, moves them around to different computers, and then pieces them back together again.
      author:
         url:https://github.com/mrocklin
         type:Person
         name:mrocklin
      datePublished:2021-07-19T00:32:53.000Z
      interactionStatistic:
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      url:https://github.com/42600/pandas/issues/42600
      context:https://schema.org
      headline:ENH: Serialize view of ArrowStringArray
      articleBody:Currently Pandas serializes views of ArrowStringArrays by serailizing the whole thing, rather than a subset. Here is an example: ```python In [1]: import pandas as pd In [2]: s = pd.Series([c * 1000 for c in "abcdefghijklmnopqrstuvwxyz"]) In [3]: s Out[3]: 0 aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa... 1 bbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbb... 2 cccccccccccccccccccccccccccccccccccccccccccccc... 3 dddddddddddddddddddddddddddddddddddddddddddddd... 4 eeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeee... 5 ffffffffffffffffffffffffffffffffffffffffffffff... 6 gggggggggggggggggggggggggggggggggggggggggggggg... 7 hhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhh... 8 iiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiii... 9 jjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjj... 10 kkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkk... 11 llllllllllllllllllllllllllllllllllllllllllllll... 12 mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm... 13 nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn... 14 oooooooooooooooooooooooooooooooooooooooooooooo... 15 pppppppppppppppppppppppppppppppppppppppppppppp... 16 qqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqq... 17 rrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrr... 18 ssssssssssssssssssssssssssssssssssssssssssssss... 19 tttttttttttttttttttttttttttttttttttttttttttttt... 20 uuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuu... 21 vvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvv... 22 wwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwww... 23 xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx... 24 yyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyy... 25 zzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzz... dtype: object In [4]: import pickle In [5]: len(pickle.dumps(s)) Out[5]: 26758 In [6]: len(pickle.dumps(s.astype("string[pyarrow]"))) Out[6]: 26891 In [7]: len(pickle.dumps(s.head(5))) Out[7]: 5632 In [8]: len(pickle.dumps(s.astype("string[pyarrow]").head(5))) Out[8]: 26891 ``` This negatively affects dask dataframe operations that cut up pandas dataframes into small pieces, moves them around to different computers, and then pieces them back together again.
      author:
         url:https://github.com/mrocklin
         type:Person
         name:mrocklin
      datePublished:2021-07-19T00:32:53.000Z
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      url:https://github.com/42600/pandas/issues/42600
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      url:https://github.com/mrocklin
      name:mrocklin
      url:https://github.com/mrocklin
      name:mrocklin
InteractionCounter:
      interactionType:https://schema.org/CommentAction
      userInteractionCount:4
      interactionType:https://schema.org/CommentAction
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