g4g22_feature_collection_to_csv.ipynb

g4g22_feature_collection_to_csv.ipynb

{
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  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "authorship_tag": "ABX9TyNgdUapalBFXo56bh4NQfOU",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/gist/jdbcode/490b567812db4c95bbe6a3c19fe30a55/g4g22_feature_collection_to_csv.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "r6Lw9A7kCIXV"
      },
      "outputs": [],
      "source": [
        "import ee\n",
        "ee.Authenticate()\n",
        "ee.Initialize()"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "import altair as alt\n",
        "import numpy as np\n",
        "import io\n",
        "import requests"
      ],
      "metadata": {
        "id": "l6XrOYDkCbxo"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "today = ee.Date(pd.to_datetime('today'))\n",
        "date_range = ee.DateRange(today.advance(-20, 'years'), today)\n",
        "pdsi = ee.ImageCollection('GRIDMET/DROUGHT').filterDate(date_range).select('pdsi')\n",
        "aoi = ee.FeatureCollection('EPA/Ecoregions/2013/L3').filter(\n",
        "    ee.Filter.eq('na_l3name', 'Sierra Nevada')).geometry()"
      ],
      "metadata": {
        "id": "z5TxdJANCNeV"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def reduce(img):\n",
        "    stat = img.reduceRegion(**{\n",
        "        'reducer': ee.Reducer.mean(),\n",
        "        'geometry': aoi,\n",
        "        'scale': 5000\n",
        "    })\n",
        "    return ee.Feature(aoi, stat).set('date', img.date().format('YYYY-MM-dd'))\n",
        "\n",
        "pdsi_median = ee.FeatureCollection(pdsi.map(reduce))"
      ],
      "metadata": {
        "id": "dJnYb2U3Cz36"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "url = pdsi_median.getDownloadURL(\n",
        "    **{'filetype': 'csv', 'selectors': pdsi_median.first().propertyNames().getInfo()})"
      ],
      "metadata": {
        "id": "XVNvHE1aE8cp"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def get_pd_from_url(url):\n",
        "  return pd.read_csv(io.StringIO(requests.get(url).content.decode('utf-8')))"
      ],
      "metadata": {
        "id": "ZiQ_WNBVGhBp"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "pdsi_df = get_pd_from_url(url)"
      ],
      "metadata": {
        "id": "91DPj-hOXpvT"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "pdsi_df"
      ],
      "metadata": {
        "id": "2YTO4FQhZQTP"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "alt.Chart(pdsi_df).mark_bar(size=1).encode(\n",
        "    x='date:T',\n",
        "    y='pdsi:Q',\n",
        "    color=alt.Color(\n",
        "        'pdsi:Q', scale=alt.Scale(scheme='redblue', domain=(-5, 5))),\n",
        "    tooltip=[\n",
        "        alt.Tooltip('Timestamp:T', title='Date'),\n",
        "        alt.Tooltip('pdsi:Q', title='PDSI')\n",
        "    ]).properties(width=600, height=300)"
      ],
      "metadata": {
        "id": "1w8ft-QlXsj4"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# In R!"
      ],
      "metadata": {
        "id": "jqvNoP-Ondin"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "%reload_ext rpy2.ipython"
      ],
      "metadata": {
        "id": "oi648u0ErEvm"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "%%R\n",
        "library(\"readr\")"
      ],
      "metadata": {
        "id": "juUh10wEbyOw"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "%R -i url"
      ],
      "metadata": {
        "id": "OitneUnNcSZr"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "%%R\n",
        "data = read_csv(url)\n",
        "head(data)"
      ],
      "metadata": {
        "id": "l_uloDkMcCRV"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}