keras-pandas
View on PyPI — Reverse Dependencies (0)
3.1.0 | keras_pandas-3.1.0-py2.py3-none-any.whl |
Wheel Details
Project: | keras-pandas |
Version: | 3.1.0 |
Filename: | keras_pandas-3.1.0-py2.py3-none-any.whl |
Download: | [link] |
Size: | 40138 |
MD5: | f6d3141f36d9798ebd5606d742fcc52b |
SHA256: | b89765152b7e26c5d365d33222c6fd6a0da4cf1ef77ebb7fa0310291b84495ce |
Uploaded: | 2018-12-15 00:29:05 +0000 |
dist-info
METADATA · WHEEL · RECORD · top_level.txt
METADATA
WHEEL
Wheel-Version: | 1.0 |
Generator: | bdist_wheel (0.31.1) |
Root-Is-Purelib: | true |
Tag: | py2-none-any |
Tag: | py3-none-any |
RECORD
Path | Digest | Size |
---|---|---|
examples/__init__.py | sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU | 0 |
examples/example_interface.py | sha256=QUYFsQc1zRdfHsi0TkL6t_E-V9lDjQCpoKlsl4-psl8 | 2406 |
examples/instanbul_predict_ise.py | sha256=fjZPKlLN9ftk5Tj6XF05dt5Te8a6KEfJmpdi56mJ1Pk | 2682 |
examples/lending_club_predict_dti.py | sha256=hvW4Igdj-zqkvCLNwpSfDimcWDTK0ksA62T8osgKeBQ | 2898 |
examples/lending_club_predict_loan_status.py | sha256=asfc5EsqMVliK1ZI8-p_WJlceb1tNQ3iMOAW-NXgQNo | 2921 |
examples/titianic_predict_survived.py | sha256=45O4Dgwe9VvJIslg4tYh14eFFNljIUIBt0G1hrwZf_Y | 2528 |
keras_pandas/Automater.py | sha256=CETlG9vo4B2NnMEZKMpsUU7zGDyWjpytlzb0uJ1qTss | 16660 |
keras_pandas/__init__.py | sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU | 0 |
keras_pandas/lib.py | sha256=0TJxeBUiB8kwoXy7HD_TBIxo2cxzqZb9ro_Pj5dh2go | 10591 |
keras_pandas/transformations.py | sha256=KeEbMfEzkshATssOZL9ova7u3Ej3ONjJHytJvbC9MIM | 15232 |
keras_pandas/data_types/Abstract.py | sha256=K2AiOmyhE-jVfGaO8w7HQGI9v_AFHcfwABIUllJHs9s | 2748 |
keras_pandas/data_types/Boolean.py | sha256=0nmvOYjggmMhGczC3orW7zjUKdjxIRGcwQFmHm-nrf4 | 3587 |
keras_pandas/data_types/Categorical.py | sha256=-ql935Ouo-0EQr_tZRYg4sR_dBqk-qSpAow_c35ge4Y | 5313 |
keras_pandas/data_types/Numerical.py | sha256=gEp6Fin17RKPjuD_T_TT77vnFqdfcJTll8VbQ_lcts0 | 4363 |
keras_pandas/data_types/Text.py | sha256=nxMiGQ2spWCg2f2aIm38hX-p9flBt09lnVurCQlLyJw | 5544 |
keras_pandas/data_types/TimeSeries.py | sha256=i99VufPC3PYp2Rshu1YFaUHosZsas53FUB35KjKQz9o | 4363 |
keras_pandas/data_types/__init__.py | sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU | 0 |
keras_pandas-3.1.0.dist-info/METADATA | sha256=q4_zfWjdY6WSrpMtho1NHzEqlvUPC38f5eg0Xhhvm4U | 13238 |
keras_pandas-3.1.0.dist-info/RECORD | — | — |
keras_pandas-3.1.0.dist-info/WHEEL | sha256=gduuPyBvFJQSQ0zdyxF7k0zynDXbIbvg5ZBHoXum5uk | 110 |
keras_pandas-3.1.0.dist-info/top_level.txt | sha256=v8h60FNStkR-fGYzUKZMy6JL7aRvHhlZOhPGEIrIaNU | 28 |
tests/__init__.py | sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU | 0 |
tests/testAbstractDatatype.py | sha256=EM3Hnz_cs0loGSnGHS7trGkLfONkzSupL_AKyj4HjVo | 1075 |
tests/testAutomater.py | sha256=A1uKiglGDxH5NlWOdx9O2nA_3i75Jp9j1yiHaNIpfeo | 6802 |
tests/testBoolean.py | sha256=rEZo0pxOit8IxnVsEhjuJilttl8Xs2uywAVZ7Sv3UkE | 1341 |
tests/testCategorical.py | sha256=JjzknW1tz7slDX4Y7ZleimXjY4leomkPjasnqm1_N9Q | 1280 |
tests/testDatatypeTemplate.py | sha256=CXEmUbUwj7Hmu0Cf4IFUZtcQoM_NmhYvUBCyG6jiktU | 531 |
tests/testExamples.py | sha256=f36L0FiriyJCWhwhlQG5VW3E2bUdHmRITAA3IG5SeaI | 560 |
tests/testLib.py | sha256=GHuoZxtS7RuyjZSJoXDZhGL1xG2PHsMdysSscl13QoU | 644 |
tests/testNumerical.py | sha256=d3BDGqTPrXBHsB73ooGuDT8Qe4J1arGHHX2oVygmWro | 1269 |
tests/testText.py | sha256=tqM5JZNYVf0CJRgLo7GPEoHiyagAnWvXjyktCjZRicg | 1251 |
tests/testTimeSeries.py | sha256=40rb4D6cRp6U8QL87rMVytAKjnNhnoROGCxp8r-QkIk | 1459 |
tests/testbase.py | sha256=Bxmk_lipyz5rnFIJZPLzWtrZlwnJjou1pIRUMf8nVFs | 366 |
top_level.txt
examples
keras_pandas
tests