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Update air quality data #520

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Update air quality data #520

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d080725
WIP: Update air quality data to use more recent data and also
alexander-griffen Mar 28, 2024
008e85c
fixup! WIP: Update air quality data to use more recent data and also …
struan Apr 1, 2024
27fcd83
fixup! WIP: Update air quality data to use more recent data and also …
struan Apr 1, 2024
888c3bf
fixup! WIP: Update air quality data to use more recent data and also …
struan Apr 1, 2024
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45 changes: 27 additions & 18 deletions hub/management/commands/import_air_quality_data.py
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Original file line number Diff line number Diff line change
@@ -1,15 +1,16 @@
from functools import reduce

from django.conf import settings
from django.core.management.base import BaseCommand

import pandas as pd
from tqdm import tqdm

from hub.models import Area, AreaData, DataSet, DataType

from .base_importers import BaseAreaImportCommand

class Command(BaseCommand):

class Command(BaseAreaImportCommand):
help = "Import air-pollution data"

source_url = "https://uk-air.defra.gov.uk/data/modelling-data"
Expand All @@ -25,7 +26,7 @@ class Command(BaseCommand):
"data_type": "float",
"category": "place",
"source_label": "Data from Defra.",
"release_date": "2021",
"release_date": "2022",
"is_range": True,
"source": source_url,
"source_type": "csv",
Expand All @@ -42,47 +43,50 @@ class Command(BaseCommand):
"pm_10": {
"pollutant": "PM10",
"metric": "Annual mean",
"header_label": "pm102021g",
"header_label": "pm102022g",
"WHO_AQG": "15",
"comments": "Gravimetric units",
"csv_link": "https://uk-air.defra.gov.uk/datastore/pcm/mappm102021g.csv",
"csv_link": "https://uk-air.defra.gov.uk/datastore/pcm/mappm102022g.csv",
},
"pm_2_5": {
"pollutant": "PM2.5",
"metric": "Annual mean",
"header_label": "pm252021g",
"csv_link": "https://uk-air.defra.gov.uk/datastore/pcm/mappm252021g.csv",
"header_label": "pm252022g",
"WHO_AQG": "5",
"csv_link": "https://uk-air.defra.gov.uk/datastore/pcm/mappm252022g.csv",
},
"no_2": {
"pollutant": "NO2",
"metric": "Annual mean",
"header_label": "no22021",
"csv_link": "https://uk-air.defra.gov.uk/datastore/pcm/mapno22021.csv",
"header_label": "no22022",
"WHO_AQG": "10",
"csv_link": "https://uk-air.defra.gov.uk/datastore/pcm/mapno22022.csv",
},
"no_x": {
"pollutant": "NOx",
"metric": "Annual mean",
"header_label": "nox2021",
"header_label": "nox2022",
"comments": "µg m\u207B\u00B3 (NO\u2093 as NO\u2082)",
"csv_link": "https://uk-air.defra.gov.uk/datastore/pcm/mapnox2021.csv",
"csv_link": "https://uk-air.defra.gov.uk/datastore/pcm/mapnox2022.csv",
},
"so_2": {
"pollutant": "SO2",
"metric": "Annual mean",
"header_label": "so22021",
"csv_link": "https://uk-air.defra.gov.uk/datastore/pcm/mapso22021.csv",
"header_label": "so22022",
"csv_link": "https://uk-air.defra.gov.uk/datastore/pcm/mapso22022.csv",
},
"ozone": {
"pollutant": "Ozone",
"metric": "DGT120",
"header_label": "dgt12021",
"header_label": "dgt12022",
"comments": "number of days on which the daily max 8-hr concentration is greater than 120 µg m\u207B\u00B3",
"csv_link": "https://uk-air.defra.gov.uk/datastore/pcm/mapdgt12021.csv",
"csv_link": "https://uk-air.defra.gov.uk/datastore/pcm/mapdgt12022.csv",
},
"benzene": {
"pollutant": "Benzene",
"metric": "Annual mean",
"header_label": "bz2021",
"csv_link": "https://uk-air.defra.gov.uk/datastore/pcm/mapbz2021.csv",
"header_label": "bz2022",
"csv_link": "https://uk-air.defra.gov.uk/datastore/pcm/mapbz2022.csv",
},
}

Expand All @@ -104,6 +108,8 @@ def create_data_types(self, df):
data_set, created = DataSet.objects.update_or_create(
name="constituency_air_quality", defaults=self.defaults
)
data_set.areas_available.add(self.get_area_type())

data_types = []
for col in tqdm(df.columns, disable=self._quiet):
label = self.in_files[col]["pollutant"]
Expand All @@ -114,6 +120,7 @@ def create_data_types(self, df):
data_type, created = DataType.objects.update_or_create(
data_set=data_set,
name=f"air_quality_{col}",
area_type=self.get_area_type(),
defaults={
"data_type": "float",
"label": label,
Expand Down Expand Up @@ -160,7 +167,9 @@ def get_dataframe(self):
skiprows=5,
na_values="MISSING",
dtype={"gridcode": "int", metadata["header_label"]: "float"},
).rename(columns={metadata["header_label"]: label})
)
.rename(columns={metadata["header_label"]: label})
.assign(WHO_AQG=lambda x: metadata.get("WHO_AQG", None))
)

print("Transforming data")
Expand Down
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