pandas2numpy
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| pandas2numpy | null | |
|---|---|---|
| 1 | 1 | |
| 3 | 32 | |
| - | - | |
| 1.8 | 0.0 | |
| about 3 years ago | over 2 years ago | |
| Python | Go | |
| Apache License 2.0 | MIT License |
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pandas2numpy
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Ask HN: What are some tools / libraries you built yourself?
I wrote pandas2numpy [0] it helps you turn a pandas dataframe into one (or two if you have categorical variables) numpy tensors ready to be pushed into a deep learning framework.
It can deal with continuous data, categorical data, normalisation of the data, log scale and NA.
I found it really useful to work on tabular data and, since it uses numpy, it is agnostic to the deep-learning framework used.
[0]: https://github.com/nestordemeure/pandas2numpy
null
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Ask HN: What are some tools / libraries you built yourself?
I build a logging library for Go, because I couldn't find one that logs to stdout AND stderr. If you used a logging lib on GCP for example, all log output went into the same pile of junk and it was hard to find "real" errors: https://github.com/emvi/logbuch
Then there is "null", also because I couldn't find one that got both, marshalling to JSON and be able to store null values in db: https://github.com/emvi/null
And finally, our "flagship" open-source project Pirsch, an embedded library for web analytics: https://github.com/pirsch-analytics/pirsch
What are some alternatives?
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