<Outdated> Float column fix for categorical data during precession calculation #1096
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taylorfturner
suggested changes
Feb 21, 2024
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PR will also need to go into dev branch and not main per contribution docs here.
| @@ -305,7 +305,10 @@ def _get_float_precision( | |||
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| # length of sampled cells after all punctuation removed | |||
| len_per_float = ( | |||
| df_series_clean.sample(sample_size).replace(to_replace=r, value="").map(len) | |||
| df_series_clean.sample(sample_size) | |||
| .astype(object) | |||
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Is not having this causing a particular issue? It's not clear to me right now why the addition? Thanks!
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Hey @taylorfturner - thank you for the comments. Signed SLA / will fork off dev in the future.
I'm planning to close this PR. I had originally intended this to be a fix for this issue. However, I believe this PR solved the underlying issue.
SchadtJ
changed the title
SchadtJ
changed the title
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This PR can be ignored. Underlying problem was fixed in this PR
In the float column precession calculation, categorical data with trailing zeros were causing issues, because the values were being trimmed with regex and not recognized as labels anymore.