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Title:
ENH: pd.get_dummies should not default to dtype np.uint8 · Issue #45848 · pandas-dev/pandas
Description:
I was caught by surprise the other day when doing some vector subtraction when using pd.get_dummies. The issue is that the default dtype is np.uint8 which means that cases where a 1 is subtracted from a 0 will result in 255. I tweeted ab...
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issue, commented, default, dtype, vec, behavior, phofl, marcogorelli, npuint, int, willkurt, member, enhancement, gotcha, type, sign, cases, signed, react, discussion, return, values, missing, bashtage, projects, pdgetdummies, surprise, result, pretty, defaulting, provide, bug, template, info, unexpected, doesnt, change, uint, bool, contributor, float, navigation, pandas, pull, requests, actions, security, enh, edited, edits,
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phofl edits member personal information enh reduce memory demands discussion requires discussion encoded categorical variable handles nan fine comment metadata assignees default type bool darwin os-release generally expected result assigned labels enhancement pretty severe 'gotcha' smallest int dtype utf-8 pandas pretty big surprise undesired default behavior type projects projects milestone core team vec1 = pd vec2 = pd issue type tracking issue pretty common int dtype subtracting vectors requested information return type behavior needed documented behavior intended behavior signed dtype dtype conversion default type default behavior vector subtraction overwhelming response bill tubbs potentially large sparse matrices signed representation unexpected result 945c9ed766a61c7d2c0a7cbb251b6edebf9cb7d5 python 0 python-bits 1~1/release_x86_64 machine x86_64 processor i386 byteorder utf-8 locale unexpected results deprecation cycle
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headline:ENH: pd.get_dummies should not default to dtype np.uint8
articleBody:I was caught by surprise the other day when doing some vector subtraction when using pd.get_dummies. The issue is that the default dtype is np.uint8 which means that cases where a 1 is subtracted from a 0 will result in 255.
I [tweeted about this surprise](https://twitter.com/willkurt/status/1490163404853686278) (with an example of this issue) and the overwhelming response was that this felt like a pretty big surprise and, in most cases, undesired default behavior. [Bill Tubbs then made a mention of this in another issue](https://github.com/pandas-dev/pandas/issues/19618#issuecomment-1030762635) where it was recommended that a new issue be created for this.
My guess is that the defaulting to np.uint8 is to reduce memory demands on what are potentially large, very sparse matrices. While I'm sure there are use cases that demand this, it seems like the risk of defaulting to np.uint8 outweigh the benefits of just choosing an signed representation.
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name:willkurt
datePublished:2022-02-06T17:39:17.000Z
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headline:ENH: pd.get_dummies should not default to dtype np.uint8
articleBody:I was caught by surprise the other day when doing some vector subtraction when using pd.get_dummies. The issue is that the default dtype is np.uint8 which means that cases where a 1 is subtracted from a 0 will result in 255.
I [tweeted about this surprise](https://twitter.com/willkurt/status/1490163404853686278) (with an example of this issue) and the overwhelming response was that this felt like a pretty big surprise and, in most cases, undesired default behavior. [Bill Tubbs then made a mention of this in another issue](https://github.com/pandas-dev/pandas/issues/19618#issuecomment-1030762635) where it was recommended that a new issue be created for this.
My guess is that the defaulting to np.uint8 is to reduce memory demands on what are potentially large, very sparse matrices. While I'm sure there are use cases that demand this, it seems like the risk of defaulting to np.uint8 outweigh the benefits of just choosing an signed representation.
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datePublished:2022-02-06T17:39:17.000Z
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