A lightweight DataFrame validation library.
Project description
Pulire
A lightweight DataFrame validation library for Pandas.
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Schema
Pulire requires a Schema
which describes all columns in a given DataFrame
.
from pulire import Schema, Column, validators, formatters
Schema([
Column("temp", "Float64", [
validators.minimum(-80),
validators.maximum(65),
formatters.decimals(1)
])
])
Validate
Pulire automatically removes values which fail the validation. Let's use the meteostat
library to get some data:
from datetime import datetime
from meteostat import Hourly
df = Hourly("10637", datetime(2018, 1, 1), datetime(2018, 1, 1, 23, 59)).fetch()
print(df)
Now, we can get a valid copy of our Meteostat DataFrame
by running our schema's validate
method:
df = myschema.validate(df)
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