millisecond vs. second, etc.
In general I would just advice to not truncate the values early on. Numbers can always be formatted to be human readable. But decimal point values may carry information for machine learning and analysis
about units: a more robust way than putting the unit in the field name would be adding a data structure just for units like in the notebook I shared earlier.
In python that could look something like
@dataclass
class SIUnitDataMixin:
sign: str
unit: int
dimension: str
class SIUnit(SIUnitDataMixin, Enum):
AMPERE = ("A", "ampere", "electric current")
AMPERE_HOUR = ("Ah", "ampere-hour", "electric capacity")
CELCIUS = ("c", "celcius", "temperature")
VOLT = ("V", "volt", "electric potential")
MILLISECOND = ("ms", "millisecond", "time")
def to_dict(self):
return {
"sign": self.sign,
"name": self.unit,
"dimension": self.dimension
}
Example
SIUnit.AMPERE_HOUR.to_dict()
{'sign': 'Ah', 'name': 'ampere-hour', 'dimension': 'electric capacity'}
Depending on the database or type of files one uses for storing the data a measurement could either
point to a table of SI units in a relational database:
or have the unit embedded a la
{
...,
"measurements" : [
{
"value": 42.42,
"unit": {sign: "A", "unit": "ampere", "dimension": "electric current"}
},
{
"value": 3.14,
"unit": {sign: "A", "unit": "ampere", "dimension": "electric current"}
},
].
...
}
