{ "cells": [ { "cell_type": "markdown", "id": "5e656f0d", "metadata": {}, "source": [ "# 💻 Aggregering av data\n", "\n", "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/GMGI221-2024/forelesninger/blob/main/06_aggregering_av_data.ipynb)\n", "\n", "Dataaggregering refererer til en prosess der vi kombinerer data i grupper. Når\n", "vi gjør romlig dataaggregering, slår vi geometriene sammen til grovere\n", "enheter (basert på noen attributter), og kan også beregne sammendragsstatistikk for\n", "disse kombinerte geometriene fra de opprinnelige, mer detaljerte verdiene. For eksempel,\n", "anta at vi er interessert i å studere kontinenter, men vi har bare\n", "landnivådata som datsettet for land; Hvis vi aggregerer dataene etter\n", "kontinent, vil vi konvertere dataene på landsnivå til et datasett på\n", "kontinentnivå.\n", "\n", "I denne opplæringen vil vi aggregere befolkningsdataene våre i Ås, dvs. rutenettcellene som har samme antall innbyggere vil bli slått sammen.\n", "\n", "La oss starte med å laste inn befolkningsdata i Ås fra filen: `aas_befolkning_2023.geojson`:" ] }, { "cell_type": "code", "execution_count": 5, "id": "0da59bd4", "metadata": {}, "outputs": [], "source": [ "import pathlib \n", "NOTEBOOK_PATH = pathlib.Path().resolve()\n", "DATA_MAPPE = NOTEBOOK_PATH / \"data\"" ] }, { "cell_type": "code", "execution_count": 6, "id": "f60699fb", "metadata": {}, "outputs": [], "source": [ "import geopandas\n", "intersection = geopandas.read_file(DATA_MAPPE / \"ssb_rutenett\" / \"aas_befolkning_2023.geojson\")" ] }, { "cell_type": "markdown", "id": "af58fe34", "metadata": {}, "source": [ "For å gjøre aggregeringen vil vi bruke en metode som heter `dissolve()` som tar\n", "som inngang kolonnen som vil bli brukt til å utføre aggregeringen:" ] }, { "cell_type": "code", "execution_count": 7, "id": "c4befebe", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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geometryru250mgml_idlokalIdnavneromversjonIdoppdateringsdatogyldigFradatauttaksdatonavnspråkkommunenummerkommunenavnsamiskForvaltningsområde
pop_tot
1MULTIPOLYGON (((261225.860 6618040.140, 261183...22605006626000kommune.28d285e9c4-8da0-4dfc-b927-31ba7ee17e6ahttps://data.geonorge.no/sosi/inndelinger/innd...32023-11-28 16:00:222024-01-012024-03-04 12:27:57Ã…snor3218Ã…sFalse
2MULTIPOLYGON (((260250.000 6618500.000, 260250...22650006625250kommune.28d285e9c4-8da0-4dfc-b927-31ba7ee17e6ahttps://data.geonorge.no/sosi/inndelinger/innd...32023-11-28 16:00:222024-01-012024-03-04 12:27:57Ã…snor3218Ã…sFalse
3MULTIPOLYGON (((260000.000 6619250.000, 260250...22617506625250kommune.28d285e9c4-8da0-4dfc-b927-31ba7ee17e6ahttps://data.geonorge.no/sosi/inndelinger/innd...32023-11-28 16:00:222024-01-012024-03-04 12:27:57Ã…snor3218Ã…sFalse
4MULTIPOLYGON (((262000.000 6618000.000, 262000...22602506625750kommune.28d285e9c4-8da0-4dfc-b927-31ba7ee17e6ahttps://data.geonorge.no/sosi/inndelinger/innd...32023-11-28 16:00:222024-01-012024-03-04 12:27:57Ã…snor3218Ã…sFalse
5MULTIPOLYGON (((261079.690 6617980.860, 261078...22650006625500kommune.28d285e9c4-8da0-4dfc-b927-31ba7ee17e6ahttps://data.geonorge.no/sosi/inndelinger/innd...32023-11-28 16:00:222024-01-012024-03-04 12:27:57Ã…snor3218Ã…sFalse
\n", "
" ], "text/plain": [ " geometry ru250m \\\n", "pop_tot \n", "1 MULTIPOLYGON (((261225.860 6618040.140, 261183... 22605006626000 \n", "2 MULTIPOLYGON (((260250.000 6618500.000, 260250... 22650006625250 \n", "3 MULTIPOLYGON (((260000.000 6619250.000, 260250... 22617506625250 \n", "4 MULTIPOLYGON (((262000.000 6618000.000, 262000... 22602506625750 \n", "5 MULTIPOLYGON (((261079.690 6617980.860, 261078... 22650006625500 \n", "\n", " gml_id lokalId \\\n", "pop_tot \n", "1 kommune.28 d285e9c4-8da0-4dfc-b927-31ba7ee17e6a \n", "2 kommune.28 d285e9c4-8da0-4dfc-b927-31ba7ee17e6a \n", "3 kommune.28 d285e9c4-8da0-4dfc-b927-31ba7ee17e6a \n", "4 kommune.28 d285e9c4-8da0-4dfc-b927-31ba7ee17e6a \n", "5 kommune.28 d285e9c4-8da0-4dfc-b927-31ba7ee17e6a \n", "\n", " navnerom versjonId \\\n", "pop_tot \n", "1 https://data.geonorge.no/sosi/inndelinger/innd... 3 \n", "2 https://data.geonorge.no/sosi/inndelinger/innd... 3 \n", "3 https://data.geonorge.no/sosi/inndelinger/innd... 3 \n", "4 https://data.geonorge.no/sosi/inndelinger/innd... 3 \n", "5 https://data.geonorge.no/sosi/inndelinger/innd... 3 \n", "\n", " oppdateringsdato gyldigFra datauttaksdato navn språk \\\n", "pop_tot \n", "1 2023-11-28 16:00:22 2024-01-01 2024-03-04 12:27:57 Ås nor \n", "2 2023-11-28 16:00:22 2024-01-01 2024-03-04 12:27:57 Ås nor \n", "3 2023-11-28 16:00:22 2024-01-01 2024-03-04 12:27:57 Ås nor \n", "4 2023-11-28 16:00:22 2024-01-01 2024-03-04 12:27:57 Ås nor \n", "5 2023-11-28 16:00:22 2024-01-01 2024-03-04 12:27:57 Ås nor \n", "\n", " kommunenummer kommunenavn samiskForvaltningsområde \n", "pop_tot \n", "1 3218 Ås False \n", "2 3218 Ås False \n", "3 3218 Ås False \n", "4 3218 Ås False \n", "5 3218 Ås False " ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Utføre aggregeringen\n", "dissolved = intersection.dissolve(by=\"pop_tot\")\n", "\n", "# Hva fikk vi\n", "dissolved.head()" ] }, { "cell_type": "markdown", "id": "c6adf892", "metadata": {}, "source": [ "La oss sammenligne antall celler i lagene før og etter aggregeringen:" ] }, { "cell_type": "code", "execution_count": 8, "id": "9b36aa39", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Rader i opprinnelig intersection GeoDataFrame: 636\n", "Rader i oppløst lag: 142\n" ] } ], "source": [ "print(f\"Rader i opprinnelig intersection GeoDataFrame: {len(intersection)}\")\n", "print(f\"Rader i oppløst lag: {len(dissolved)}\")" ] }, { "cell_type": "markdown", "id": "1a0b8056", "metadata": {}, "source": [ "Faktisk har antall rader i dataene våre blitt redusert og polygonene har blitt\n", "slått sammen.\n", "\n", "Hva skjedde egentlig her? La oss ta en nærmere titt. \n", "\n", "La oss se hvilke kolonner vi nå har i vår GeoDataFrame:" ] }, { "cell_type": "code", "execution_count": 9, "id": "de0d71c9", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Index(['geometry', 'ru250m', 'gml_id', 'lokalId', 'navnerom', 'versjonId',\n", " 'oppdateringsdato', 'gyldigFra', 'datauttaksdato', 'navn', 'språk',\n", " 'kommunenummer', 'kommunenavn', 'samiskForvaltningsområde'],\n", " dtype='object')" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "dissolved.columns" ] }, { "cell_type": "markdown", "id": "026ce48f", "metadata": {}, "source": [ "Som vi kan se, kan ikke kolonnen som vi brukte for å utføre aggregeringen\n", "(`pop_tot`) finnes lenger i kolonnelisten. Hva skjedde med\n", "den?\n", "\n", "La oss ta en titt på indeksene i vår GeoDataFrame:" ] }, { "cell_type": "code", "execution_count": 10, "id": "0864f418", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Index([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10,\n", " ...\n", " 250, 256, 261, 278, 284, 297, 300, 344, 368, 379],\n", " dtype='int64', name='pop_tot', length=142)" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "dissolved.index" ] }, { "cell_type": "markdown", "id": "41a49537", "metadata": {}, "source": [ "Aha! Vel nå forstår vi hvor kolonnen vår gikk. Den brukes nå som indeks i\n", "vår `dissolved` GeoDataFrame. \n", "\n", "Nå kan vi for eksempel bare velge slike geometrier fra laget som har for\n", "eksempel nøyaktig 15 innbyggere:" ] }, { "cell_type": "code", "execution_count": 11, "id": "6b5f54db", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "geometry MULTIPOLYGON (((259250.00000892268 6620999.999...\n", "ru250m 22612506625750\n", "gml_id kommune.28\n", "lokalId d285e9c4-8da0-4dfc-b927-31ba7ee17e6a\n", "navnerom https://data.geonorge.no/sosi/inndelinger/innd...\n", "versjonId 3\n", "oppdateringsdato 2023-11-28 16:00:22\n", "gyldigFra 2024-01-01\n", "datauttaksdato 2024-03-04 12:27:57\n", "navn Ås\n", "språk nor\n", "kommunenummer 3218\n", "kommunenavn Ås\n", "samiskForvaltningsområde False\n", "Name: 15, dtype: object" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Velg bare geometrier som har 15 innbyggere\n", "dissolved.loc[15]" ] }, { "cell_type": "code", "execution_count": 12, "id": "8806cba1", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "pandas.core.series.Series" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Se datatype\n", "type(dissolved.loc[15])" ] }, { "cell_type": "markdown", "id": "a64a16a3", "metadata": {}, "source": [ "Som vi kan se, har vi nå som et resultat et Pandas `Series` objekt som inneholder\n", "i utgangspunktet en rad fra vår opprinnelige aggregerte GeoDataFrame.\n", "\n", "La oss også visualisere disse 15 innbyggere-rutenettcellene.\n", "\n", "Først må vi konvertere den valgte raden tilbake til en GeoDataFrame:" ] }, { "cell_type": "code", "execution_count": 13, "id": "4eeb2269", "metadata": {}, "outputs": [], "source": [ "# Lag en GeoDataFrame\n", "selection = geopandas.GeoDataFrame([dissolved.loc[15]], crs=dissolved.crs)" ] }, { "cell_type": "markdown", "id": "9541de9a", "metadata": {}, "source": [ "Plott utvalget på toppen av hele rutenettet:" ] }, { "cell_type": "code", "execution_count": 14, "id": "306e562a", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Plott alle rutenettcellene, og rutenettcellene som har 15 innbyggere\n", "ax = dissolved.plot(facecolor=\"gray\")\n", "selection.plot(ax=ax, facecolor=\"red\")" ] }, { "cell_type": "markdown", "id": "b7421fab", "metadata": {}, "source": [ "En annen måte å visualisere befolkningen i hele GeoDataFrame på er å plott ved hjelp av en spesifikk kolonne. For å bruke vår `pop_tot` kolonne, som nå er indeksen i GeoDataFrame, må vi tilbakestille indeksen:" ] }, { "cell_type": "code", "execution_count": 15, "id": "ab8d8424", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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pop_totgeometryru250mgml_idlokalIdnavneromversjonIdoppdateringsdatogyldigFradatauttaksdatonavnspråkkommunenummerkommunenavnsamiskForvaltningsområde
01MULTIPOLYGON (((261225.860 6618040.140, 261183...22605006626000kommune.28d285e9c4-8da0-4dfc-b927-31ba7ee17e6ahttps://data.geonorge.no/sosi/inndelinger/innd...32023-11-28 16:00:222024-01-012024-03-04 12:27:57Ã…snor3218Ã…sFalse
12MULTIPOLYGON (((260250.000 6618500.000, 260250...22650006625250kommune.28d285e9c4-8da0-4dfc-b927-31ba7ee17e6ahttps://data.geonorge.no/sosi/inndelinger/innd...32023-11-28 16:00:222024-01-012024-03-04 12:27:57Ã…snor3218Ã…sFalse
23MULTIPOLYGON (((260000.000 6619250.000, 260250...22617506625250kommune.28d285e9c4-8da0-4dfc-b927-31ba7ee17e6ahttps://data.geonorge.no/sosi/inndelinger/innd...32023-11-28 16:00:222024-01-012024-03-04 12:27:57Ã…snor3218Ã…sFalse
34MULTIPOLYGON (((262000.000 6618000.000, 262000...22602506625750kommune.28d285e9c4-8da0-4dfc-b927-31ba7ee17e6ahttps://data.geonorge.no/sosi/inndelinger/innd...32023-11-28 16:00:222024-01-012024-03-04 12:27:57Ã…snor3218Ã…sFalse
45MULTIPOLYGON (((261079.690 6617980.860, 261078...22650006625500kommune.28d285e9c4-8da0-4dfc-b927-31ba7ee17e6ahttps://data.geonorge.no/sosi/inndelinger/innd...32023-11-28 16:00:222024-01-012024-03-04 12:27:57Ã…snor3218Ã…sFalse
\n", "
" ], "text/plain": [ " pop_tot geometry ru250m \\\n", "0 1 MULTIPOLYGON (((261225.860 6618040.140, 261183... 22605006626000 \n", "1 2 MULTIPOLYGON (((260250.000 6618500.000, 260250... 22650006625250 \n", "2 3 MULTIPOLYGON (((260000.000 6619250.000, 260250... 22617506625250 \n", "3 4 MULTIPOLYGON (((262000.000 6618000.000, 262000... 22602506625750 \n", "4 5 MULTIPOLYGON (((261079.690 6617980.860, 261078... 22650006625500 \n", "\n", " gml_id lokalId \\\n", "0 kommune.28 d285e9c4-8da0-4dfc-b927-31ba7ee17e6a \n", "1 kommune.28 d285e9c4-8da0-4dfc-b927-31ba7ee17e6a \n", "2 kommune.28 d285e9c4-8da0-4dfc-b927-31ba7ee17e6a \n", "3 kommune.28 d285e9c4-8da0-4dfc-b927-31ba7ee17e6a \n", "4 kommune.28 d285e9c4-8da0-4dfc-b927-31ba7ee17e6a \n", "\n", " navnerom versjonId \\\n", "0 https://data.geonorge.no/sosi/inndelinger/innd... 3 \n", "1 https://data.geonorge.no/sosi/inndelinger/innd... 3 \n", "2 https://data.geonorge.no/sosi/inndelinger/innd... 3 \n", "3 https://data.geonorge.no/sosi/inndelinger/innd... 3 \n", "4 https://data.geonorge.no/sosi/inndelinger/innd... 3 \n", "\n", " oppdateringsdato gyldigFra datauttaksdato navn språk \\\n", "0 2023-11-28 16:00:22 2024-01-01 2024-03-04 12:27:57 Ås nor \n", "1 2023-11-28 16:00:22 2024-01-01 2024-03-04 12:27:57 Ås nor \n", "2 2023-11-28 16:00:22 2024-01-01 2024-03-04 12:27:57 Ås nor \n", "3 2023-11-28 16:00:22 2024-01-01 2024-03-04 12:27:57 Ås nor \n", "4 2023-11-28 16:00:22 2024-01-01 2024-03-04 12:27:57 Ås nor \n", "\n", " kommunenummer kommunenavn samiskForvaltningsområde \n", "0 3218 Ås False \n", "1 3218 Ås False \n", "2 3218 Ås False \n", "3 3218 Ås False \n", "4 3218 Ås False " ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "dissolved = dissolved.reset_index()\n", "dissolved.head()" ] }, { "cell_type": "markdown", "id": "f9aad113", "metadata": {}, "source": [ "Som vi kan se, har vi nå vår `pop_tot` som en kolonne igjen, og kan da plott GeoDataFrame ved å sende denne kolonnen ved hjelp av `column` parameteren:" ] }, { "cell_type": "code", "execution_count": 16, "id": "0578d89a", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", 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