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Using the 'date' field for datetime64+timezone columns

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Ashton Sidhu 2022-01-04 23:03:49 -05:00 committed by GitHub
parent 3db93cd789
commit 64daa07a65
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GPG Key ID: 4AEE18F83AFDEB23
2 changed files with 6 additions and 1 deletions
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5
eland/field_mappings.py
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@ -34,6 +34,7 @@ import numpy as np
import pandas as pd # type: ignore
from pandas.core.dtypes.common import ( # type: ignore
is_bool_dtype,
is_datetime64_any_dtype,
is_datetime_or_timedelta_dtype,
is_float_dtype,
is_integer_dtype,
@ -487,7 +488,7 @@ class FieldMappings:
int64 int int_, int8, int16, int32, int64, uint8, uint16, uint32, uint64 Integer numbers
float64 float float_, float16, float32, float64 Floating point numbers
bool bool bool_ True/False values
datetime64 NA datetime64[ns] Date and time values
datetime64 NA datetime64[ns] datetime64[ns, TIMEZONE] Date and time values
timedelta[ns] NA NA Differences between two datetimes
category NA NA Finite list of text values
```
@ -505,6 +506,8 @@ class FieldMappings:
es_dtype = "keyword"
elif is_datetime_or_timedelta_dtype(pd_dtype):
es_dtype = "date"
elif is_datetime64_any_dtype(pd_dtype):
es_dtype = "date"
else:
warnings.warn(
f"No mapping for pd_dtype: [{pd_dtype}], using default mapping"

2
tests/dataframe/test_utils_pytest.py
View File

@ -37,6 +37,7 @@ class TestDataFrameUtils(TestData):
"E": [1.0, 2.0, 3.0],
"F": False,
"G": [1, 2, 3],
"H": pd.Timestamp("20190102", tz="UTC"),
},
index=["0", "1", "2"],
)
@ -51,6 +52,7 @@ class TestDataFrameUtils(TestData):
"E": {"type": "double"},
"F": {"type": "boolean"},
"G": {"type": "long"},
"H": {"type": "date"},
}
}
}