fix: crash on null values from access long type #5
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Changed the conversion from access long type to pandas float instead of pandas int, in order to support null values. Note that pandas just released int null support @ pandas .24, but still experimental.
verasativa
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Feb 25, 2019
behrenhoff
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May 6, 2019
| @@ -34,7 +34,8 @@ def _extract_dtype(data_type): | |||
| if data_type.startswith('double'): | |||
| return np.float_ | |||
| elif data_type.startswith('long'): | |||
| return np.int_ | |||
| # access CAN have null values on long type, @ pandas 0.24 int null suport is experimental, a float is safer for now. | |||
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float supports a smaller range than INT. This might be ok, but when dealing with IDs (which tend to use up the whole range of values), you will break code.
consider:
f = np.float_(1 << 53)
print(f)
f += 1
print(f)
(in case np.float_ is a 64 bit IEEE representation)
So this should at least be optional.
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Since pandas .24 there is a Int type (notice the caps on the I), which allows nulls ints. If you are willing to require .24+ (they are at .24.2 now), that will fix it for both cases.
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Changed the conversion from access long type to pandas float instead of pandas int, in order to support null values.
Note that pandas just released int null support @ pandas .24, but still experimental.