46 lines
1.6 KiB
Bash
46 lines
1.6 KiB
Bash
#!/bin/sh
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set -e
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DB=francecrime.db
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DEPT=department
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REG=region
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DEPT_CRIMES=department_crimes
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rm -f "$DB"
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sqlite-utils create-database "$DB"
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# Region lookup table
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curl -L https://www.insee.fr/fr/statistiques/fichier/6800675/v_region_2023.csv | \
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sqlite-utils insert "$DB" "$REG" - --csv --convert 'return {"code": row["REG"], "name": row["NCCENR"]}'
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sqlite-utils transform "$DB" "$REG" --pk code
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# Department lookup table
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curl -L https://www.insee.fr/fr/statistiques/fichier/6800675/v_departement_2023.csv | \
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sqlite-utils insert "$DB" "$DEPT" - --csv --convert 'return {"code": row["DEP"], "name": row["NCCENR"]}'
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sqlite-utils transform "$DB" "$DEPT" --pk code
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# TODO Add a way to filter out island possessions
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# Crimes by department
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curl -L https://www.data.gouv.fr/fr/datasets/r/acc332f6-92be-42af-9721-f3609bea8cfc | gzip -d | \
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sqlite-utils insert "$DB" "$DEPT_CRIMES" - --csv --delimiter=";" --convert '
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def full_year(year):
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return "20" + year
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def comma_float(s):
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return float(s.replace(",", "."))
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return {
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"class": row["classe"],
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"year": full_year(row["annee"]),
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"department": row["Code.département"],
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"region": row["Code.région"],
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"cases": int(row["faits"]),
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"population": int(row["POP"]),
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"rate_per_thousand": comma_float(row["tauxpourmille"])}'
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sqlite-utils extract "$DB" "$DEPT_CRIMES" class
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sqlite-utils transform "$DB" "$DEPT_CRIMES" --pk class_id --pk year --pk department
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sqlite-utils add-foreign-keys "$DB" \
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"$DEPT_CRIMES" department "$DEPT" code \
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"$DEPT_CRIMES" region "$REG" code
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# TODO Rename class_id to class and show English text using crime_classes.csv
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datasette "$DB" -o
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