Allow ints and string inputs for TIMESTAMP columns, consistent with other OmniSci client interfaces #138
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* Fixes for boolean na types, typos, na assignments in test cases (heavyai#110) * Fix na types for boolean, fix test case na types, fillna prior to boolean Thrift cast to prevent type error * Attempt to distinguish int from bigint when int column contains None, fix int64 test that was actually an in32 test, add int32 test case * Fix linting issue * Option to chunk Pandas columnar data load (heavyai#117) * Fixes for boolean na types, typos, na assignments in test cases (heavyai#110) (#3) * Fix na types for boolean, fix test case na types, fillna prior to boolean Thrift cast to prevent type error * Attempt to distinguish int from bigint when int column contains None, fix int64 test that was actually an in32 test, add int32 test case * Fix linting issue * Add option for chunking a Pandas columnar data load * Fix linting issues * Reorder options * Reorder options
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Fix bug with loading Pandas dataframe row-wise (heavyai#133)
… return int if int passed
randyzwitch
reviewed
Dec 14, 2018
added 2 commits
December 14, 2018 14:39
randyzwitch
reviewed
Dec 17, 2018
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Currently mapdql and Immerse both allow the user to insert timestamps as strings or integers. pymapd insists on having the timestamp in datetime64[ns] format which is inconsistent.
The column type of the OmniSci table is what determines that the data should be a TIMESTAMP as of recently, so we're not longer guessing on input what the user wanted, and are no longer naive about the destination data type. This allows us to make confident decisions about what the data is and what should happen to it to allow the user multiple input options without having to do the transformations prior to passing to pymapd, bringing the behavior in-line with other OmniSci client utilities.