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 (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 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.
junpenglao, Dpananos, guti1, dhvalden and asishm
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