point_data_analysis.ipynb

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   "source": [
    "### Piont data anlysis\n",
    "This script will walk you through the basic point data anlysis using Tethys library. The scripts below includes retrieving data from envlib.org, plotting composite averages, plotting statistical distributions using violin plots and windrose for wind data."
   ]
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   "source": [
    "#### import libraries"
   ]
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   "id": "27f836b8-8ac8-4bb3-b19d-fb16cb3d94dd",
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   "source": [
    "from tethysts import Tethys\n",
    "from windrose import WindroseAxes\n",
    "from matplotlib import pyplot as plt\n",
    "import matplotlib.cm as cm\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import xarray as xr\n",
    "from envlib_helper import *"
   ]
  },
  {
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   "id": "dc1a45cd-342b-4be1-b255-f6982ac0b6ab",
   "metadata": {},
   "source": [
    "The line below initiates the Tethys instance (service) before retrieving data from the server."
   ]
  },
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   "id": "2de29749-fba1-456f-b78e-d35276fc16c1",
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   "source": [
    "ts = Tethys()"
   ]
  },
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   "id": "7ee0f0d9-11c2-4fac-826e-f381fd3374cb",
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   "source": [
    "We can get information of all the available datasets on [envlib.org](https://www.envlib.org) using the following line. This will save an excel file called \"envlib_data_catalog.xlsx\" in the current Jupyter environment. Once created, you can download to your own computer and find the information you need in the later process to retrieve any specific data.\n",
    "You can also check the [web GUI](https://wai.tethys-ts.xyz) for all the information."
   ]
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       "                                                                       method  \\\n",
       "feature    parameter           owner                                            \n",
       "atmosphere barometric_pressure ECMWF                               simulation   \n",
       "                               Met Solutions                       simulation   \n",
       "                               NZ Open Modelling Consortium        simulation   \n",
       "                               NZ Open Modelling Consortium        simulation   \n",
       "                               NZ Open Modelling Consortium        simulation   \n",
       "...                                                                       ...   \n",
       "waterway   temperature         Environment Canterbury        sensor_recording   \n",
       "                               Environment Canterbury          field_activity   \n",
       "           water_use           Environment Southland               simulation   \n",
       "                               Environment Southland               simulation   \n",
       "                               Environment Southland               simulation   \n",
       "\n",
       "                                                                                              product_code  \\\n",
       "feature    parameter           owner                                                                         \n",
       "atmosphere barometric_pressure ECMWF                                                  reanalysis-era5-land   \n",
       "                               Met Solutions                         WRF NZ South Island Central Otago 3km   \n",
       "                               NZ Open Modelling Consortium    UC WRF NZ South Island North Canterbury 1km   \n",
       "                               NZ Open Modelling Consortium       UC WRF NZ South Island Central Otago 1km   \n",
       "                               NZ Open Modelling Consortium  UC WRF NZ South Island Marlborough Nelson 1km   \n",
       "...                                                                                                    ...   \n",
       "waterway   temperature         Environment Canterbury                              quality_controlled_data   \n",
       "                               Environment Canterbury                              quality_controlled_data   \n",
       "           water_use           Environment Southland                               WAP allocation method 1   \n",
       "                               Environment Southland                                   estimation method 1   \n",
       "                               Environment Southland                             stream depletion method 1   \n",
       "\n",
       "                                                            aggregation_statistic  \\\n",
       "feature    parameter           owner                                                \n",
       "atmosphere barometric_pressure ECMWF                                instantaneous   \n",
       "                               Met Solutions                        instantaneous   \n",
       "                               NZ Open Modelling Consortium         instantaneous   \n",
       "                               NZ Open Modelling Consortium         instantaneous   \n",
       "                               NZ Open Modelling Consortium         instantaneous   \n",
       "...                                                                           ...   \n",
       "waterway   temperature         Environment Canterbury                        mean   \n",
       "                               Environment Canterbury                    sporadic   \n",
       "           water_use           Environment Southland                   cumulative   \n",
       "                               Environment Southland                   cumulative   \n",
       "                               Environment Southland                         mean   \n",
       "\n",
       "                                                            frequency_interval  \\\n",
       "feature    parameter           owner                                             \n",
       "atmosphere barometric_pressure ECMWF                                         H   \n",
       "                               Met Solutions                                 H   \n",
       "                               NZ Open Modelling Consortium                  H   \n",
       "                               NZ Open Modelling Consortium                  H   \n",
       "                               NZ Open Modelling Consortium                  H   \n",
       "...                                                                        ...   \n",
       "waterway   temperature         Environment Canterbury                       1H   \n",
       "                               Environment Canterbury                        T   \n",
       "           water_use           Environment Southland                       24H   \n",
       "                               Environment Southland                       24H   \n",
       "                               Environment Southland                       24H   \n",
       "\n",
       "                                                            utc_offset  ...  \\\n",
       "feature    parameter           owner                                    ...   \n",
       "atmosphere barometric_pressure ECMWF                                0H  ...   \n",
       "                               Met Solutions                        0H  ...   \n",
       "                               NZ Open Modelling Consortium         0H  ...   \n",
       "                               NZ Open Modelling Consortium         0H  ...   \n",
       "                               NZ Open Modelling Consortium         0H  ...   \n",
       "...                                                                ...  ...   \n",
       "waterway   temperature         Environment Canterbury               0H  ...   \n",
       "                               Environment Canterbury               0H  ...   \n",
       "           water_use           Environment Southland               12H  ...   \n",
       "                               Environment Southland               12H  ...   \n",
       "                               Environment Southland               12H  ...   \n",
       "\n",
       "                                                            spatial_resolution  \\\n",
       "feature    parameter           owner                                             \n",
       "atmosphere barometric_pressure ECMWF                                     0.100   \n",
       "                               Met Solutions                             0.027   \n",
       "                               NZ Open Modelling Consortium              0.009   \n",
       "                               NZ Open Modelling Consortium              0.009   \n",
       "                               NZ Open Modelling Consortium              0.009   \n",
       "...                                                                        ...   \n",
       "waterway   temperature         Environment Canterbury                      NaN   \n",
       "                               Environment Canterbury                      NaN   \n",
       "           water_use           Environment Southland                       NaN   \n",
       "                               Environment Southland                       NaN   \n",
       "                               Environment Southland                       NaN   \n",
       "\n",
       "                                                            wrf_standard_name  \\\n",
       "feature    parameter           owner                                            \n",
       "atmosphere barometric_pressure ECMWF                                     PSFC   \n",
       "                               Met Solutions                             PSFC   \n",
       "                               NZ Open Modelling Consortium              PSFC   \n",
       "                               NZ Open Modelling Consortium              PSFC   \n",
       "                               NZ Open Modelling Consortium              PSFC   \n",
       "...                                                                       ...   \n",
       "waterway   temperature         Environment Canterbury                     NaN   \n",
       "                               Environment Canterbury                     NaN   \n",
       "           water_use           Environment Southland                      NaN   \n",
       "                               Environment Southland                      NaN   \n",
       "                               Environment Southland                      NaN   \n",
       "\n",
       "                                                                                           product_description  \\\n",
       "feature    parameter           owner                                                                             \n",
       "atmosphere barometric_pressure ECMWF                         ERA5-Land is a reanalysis dataset providing a ...   \n",
       "                               Met Solutions                 The Weather Research and Forecasting (WRF) mod...   \n",
       "                               NZ Open Modelling Consortium  The Weather Research and Forecasting (WRF) mod...   \n",
       "                               NZ Open Modelling Consortium  The Weather Research and Forecasting (WRF) mod...   \n",
       "                               NZ Open Modelling Consortium  The Weather Research and Forecasting (WRF) mod...   \n",
       "...                                                                                                        ...   \n",
       "waterway   temperature         Environment Canterbury                                                      NaN   \n",
       "                               Environment Canterbury                                                      NaN   \n",
       "           water_use           Environment Southland                                                       NaN   \n",
       "                               Environment Southland                                                       NaN   \n",
       "                               Environment Southland                                                       NaN   \n",
       "\n",
       "                                                            parent_datasets  \\\n",
       "feature    parameter           owner                                          \n",
       "atmosphere barometric_pressure ECMWF                                    NaN   \n",
       "                               Met Solutions                            NaN   \n",
       "                               NZ Open Modelling Consortium             NaN   \n",
       "                               NZ Open Modelling Consortium             NaN   \n",
       "                               NZ Open Modelling Consortium             NaN   \n",
       "...                                                                     ...   \n",
       "waterway   temperature         Environment Canterbury                   NaN   \n",
       "                               Environment Canterbury                   NaN   \n",
       "           water_use           Environment Southland                    NaN   \n",
       "                               Environment Southland                    NaN   \n",
       "                               Environment Southland                    NaN   \n",
       "\n",
       "                                                            result_type  \n",
       "feature    parameter           owner                                     \n",
       "atmosphere barometric_pressure ECMWF                                NaN  \n",
       "                               Met Solutions                        NaN  \n",
       "                               NZ Open Modelling Consortium         NaN  \n",
       "                               NZ Open Modelling Consortium         NaN  \n",
       "                               NZ Open Modelling Consortium         NaN  \n",
       "...                                                                 ...  \n",
       "waterway   temperature         Environment Canterbury               NaN  \n",
       "                               Environment Canterbury               NaN  \n",
       "           water_use           Environment Southland                NaN  \n",
       "                               Environment Southland                NaN  \n",
       "                               Environment Southland                NaN  \n",
       "\n",
       "[127 rows x 25 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_all_dataset_information(ts)"
   ]
  },
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   "cell_type": "markdown",
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   "source": [
    "#### Retrive a point data\n",
    "\n",
    "You can use various ways to retrive time series from any point locations (AWS statoin observation, WRF simulation etc.). The code below demenstrates a most commonly way of retriving a dataset from the closiest lat and lon. The below example will retrieve all tier1 datasets from a FENZ AWS."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "c3f838e7-c942-4873-8b48-b52294a9ebff",
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   "outputs": [],
   "source": [
    "owner = \"FENZ\"\n",
    "method = \"sensor_recording\"\n",
    "product_code = \"raw_data\"\n",
    "lat = -43.47\n",
    "lon = 171.672"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "3e55f571-c7ee-4d40-9990-652e390c1df8",
   "metadata": {},
   "outputs": [],
   "source": [
    "station_data=get_data_from_lat_lon(ts,owner,method,product_code,lat,lon)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "4e08ccbc-1a69-46e4-ad78-b410df75f146",
   "metadata": {},
   "outputs": [],
   "source": [
    "data_slice = station_data.sel(time=slice(\"2019-01-01\", \"2020-12-31\")) # change the data range accordingly"
   ]
  },
  {
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   "execution_count": 20,
   "id": "741ec78c-ab7b-4414-9fe3-7641f31c80ed",
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       "\n",
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       "\n",
       ".xr-wrap {\n",
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       "  padding-bottom: 6px;\n",
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       "\n",
       ".xr-header > div,\n",
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       "  margin-bottom: 0;\n",
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       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
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       "\n",
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       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
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       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
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       ".xr-section-item {\n",
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       ".xr-section-item input {\n",
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       "\n",
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       "\n",
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       "\n",
       ".xr-section-summary {\n",
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       "\n",
       ".xr-section-summary > span {\n",
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       "\n",
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       "\n",
       ".xr-section-summary-in + label:before {\n",
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       "  font-size: 11px;\n",
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       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
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       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
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       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
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       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
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       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
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       "\n",
       ".xr-section-details {\n",
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       "\n",
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       "\n",
       ".xr-array-wrap {\n",
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       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
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       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
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       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
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       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
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       "\n",
       ".xr-var-name {\n",
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       "\n",
       ".xr-var-dims {\n",
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       "}\n",
       "\n",
       ".xr-var-dtype {\n",
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       "  color: var(--xr-font-color2);\n",
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       "\n",
       ".xr-var-preview {\n",
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       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
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       ".xr-preview,\n",
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       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
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       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
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       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
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       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
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       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
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       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
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       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
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       "  float: left;\n",
       "  padding-right: 10px;\n",
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       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
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       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
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       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:                   (time: 17544)\n",
       "Coordinates:\n",
       "  * time                      (time) datetime64[ns] 2019-01-01 ... 2020-12-31...\n",
       "    geometry                  &lt;U42 &#x27;01010000002FDD2406817565405C8FC2F528BC45C0&#x27;\n",
       "    height                    int8 2\n",
       "Data variables:\n",
       "    externalId                object &#x27;43.47000S 171.67200E V1.0&#x27;\n",
       "    station_id                object &#x27;05c88b932a06f5409526fad9&#x27;\n",
       "    ref                       object &#x27;snowdon&#x27;\n",
       "    name                      object &#x27;Snowdon&#x27;\n",
       "    wind_speed                (time) float32 0.95 0.85 0.95 ... 0.65 0.64 0.85\n",
       "    lat                       float64 -43.47\n",
       "    lon                       float64 171.7\n",
       "    relative_humidity         (time) float32 77.9 76.9 81.8 ... 74.6 73.5 73.6\n",
       "    volumetric_water_content  (time) float32 37.6 37.0 37.0 ... 27.0 27.0 27.0\n",
       "    wind_direction            (time) float32 217.9 146.9 219.2 ... 219.8 137.2\n",
       "    precipitation             (time) float32 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0\n",
       "    temperature               (time) float32 23.3 23.4 21.2 ... 17.8 19.2 20.2\n",
       "Attributes:\n",
       "    featureType:  timeSeries\n",
       "    title:        mean wind_speed in m/s of the atmosphere by a sensor_record...\n",
       "    institution:  FENZ\n",
       "    license:      https://creativecommons.org/licenses/by/4.0/\n",
       "    source:       sensor_recording\n",
       "    history:      20211024T200003Z: Generated\n",
       "    version:      3</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-f3fc1c47-bc85-46c4-bdac-1ca989156165' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-f3fc1c47-bc85-46c4-bdac-1ca989156165' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 17544</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-207cd8af-18d9-4a69-89fb-17a3059483d9' class='xr-section-summary-in' type='checkbox'  checked><label for='section-207cd8af-18d9-4a69-89fb-17a3059483d9' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2019-01-01 ... 2020-12-31T23:00:00</div><input id='attrs-e0b3f23a-4644-46f3-ad65-05e7933cb707' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e0b3f23a-4644-46f3-ad65-05e7933cb707' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-db356895-2693-4445-9698-4728a2eb129c' class='xr-var-data-in' type='checkbox'><label for='data-db356895-2693-4445-9698-4728a2eb129c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>start_time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2019-01-01T00:00:00.000000000&#x27;, &#x27;2019-01-01T01:00:00.000000000&#x27;,\n",
       "       &#x27;2019-01-01T02:00:00.000000000&#x27;, ..., &#x27;2020-12-31T21:00:00.000000000&#x27;,\n",
       "       &#x27;2020-12-31T22:00:00.000000000&#x27;, &#x27;2020-12-31T23:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geometry</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U42</div><div class='xr-var-preview xr-preview'>&#x27;01010000002FDD2406817565405C8FC...</div><input id='attrs-c9a47671-5127-4ce5-aa69-0c4d5019f66e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c9a47671-5127-4ce5-aa69-0c4d5019f66e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8207330e-1fd2-4b32-a448-15f846754566' class='xr-var-data-in' type='checkbox'><label for='data-8207330e-1fd2-4b32-a448-15f846754566' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>The hexadecimal encoding of the Well-Known Binary (WKB) geometry</dd><dt><span>crs_EPSG :</span></dt><dd>4326</dd></dl></div><div class='xr-var-data'><pre>array(&#x27;01010000002FDD2406817565405C8FC2F528BC45C0&#x27;, dtype=&#x27;&lt;U42&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>height</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int8</div><div class='xr-var-preview xr-preview'>2</div><input id='attrs-8015a1c9-7c9e-4efd-ae40-565e10746f2c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8015a1c9-7c9e-4efd-ae40-565e10746f2c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-994f6634-4c63-4a94-a85e-448da6e32f22' class='xr-var-data-in' type='checkbox'><label for='data-994f6634-4c63-4a94-a85e-448da6e32f22' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>height</dd><dt><span>long_name :</span></dt><dd>vertical distance above the surface</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>positive :</span></dt><dd>up</dd></dl></div><div class='xr-var-data'><pre>array(2, dtype=int8)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-31c039b1-da59-447a-9da1-5116368900c5' class='xr-section-summary-in' type='checkbox'  checked><label for='section-31c039b1-da59-447a-9da1-5116368900c5' class='xr-section-summary' >Data variables: <span>(12)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>externalId</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-6832bff0-9d39-4ee6-ac40-0b56009517bd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6832bff0-9d39-4ee6-ac40-0b56009517bd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-240ab594-5753-4dcd-93df-b03cf421352b' class='xr-var-data-in' type='checkbox'><label for='data-240ab594-5753-4dcd-93df-b03cf421352b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long name :</span></dt><dd>The unique id assigned by NIWA for internal interoperation</dd></dl></div><div class='xr-var-data'><pre>array(&#x27;43.47000S 171.67200E V1.0&#x27;, dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>station_id</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-66e696ea-c302-4737-9c54-ec9f77b91880' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-66e696ea-c302-4737-9c54-ec9f77b91880' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b9081554-f9e2-47d9-b1c9-32b11172acb9' class='xr-var-data-in' type='checkbox'><label for='data-b9081554-f9e2-47d9-b1c9-32b11172acb9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cf_role :</span></dt><dd>timeseries_id</dd></dl></div><div class='xr-var-data'><pre>array(&#x27;05c88b932a06f5409526fad9&#x27;, dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-dba0ee3d-2a0a-4a43-baa5-6427bd184a20' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dba0ee3d-2a0a-4a43-baa5-6427bd184a20' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4d1c8f54-064b-42f2-a3db-8386695a2997' class='xr-var-data-in' type='checkbox'><label for='data-4d1c8f54-064b-42f2-a3db-8386695a2997' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>station reference id given by the owner</dd></dl></div><div class='xr-var-data'><pre>array(&#x27;snowdon&#x27;, dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>name</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-4f08fe63-4365-4a5b-9dc3-4aad6418f605' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4f08fe63-4365-4a5b-9dc3-4aad6418f605' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8744ffab-c8fa-49f2-bb72-99dffe977a65' class='xr-var-data-in' type='checkbox'><label for='data-8744ffab-c8fa-49f2-bb72-99dffe977a65' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>station name</dd></dl></div><div class='xr-var-data'><pre>array(&#x27;Snowdon&#x27;, dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>wind_speed</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-644761ac-23c0-48b6-96ac-d655556f128a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-644761ac-23c0-48b6-96ac-d655556f128a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-92e97cf1-aedb-4e00-bb0c-7fa64c58bc77' class='xr-var-data-in' type='checkbox'><label for='data-92e97cf1-aedb-4e00-bb0c-7fa64c58bc77' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>feature :</span></dt><dd>atmosphere</dd><dt><span>parameter :</span></dt><dd>wind_speed</dd><dt><span>method :</span></dt><dd>sensor_recording</dd><dt><span>product_code :</span></dt><dd>raw_data</dd><dt><span>owner :</span></dt><dd>FENZ</dd><dt><span>aggregation_statistic :</span></dt><dd>mean</dd><dt><span>frequency_interval :</span></dt><dd>1H</dd><dt><span>utc_offset :</span></dt><dd>0H</dd><dt><span>units :</span></dt><dd>m/s</dd><dt><span>license :</span></dt><dd>https://creativecommons.org/licenses/by/4.0/</dd><dt><span>spatial_distribution :</span></dt><dd>sparse</dd><dt><span>geometry_type :</span></dt><dd>Point</dd><dt><span>grouping :</span></dt><dd>none</dd><dt><span>attribution :</span></dt><dd>Data licenced by FENZ</dd><dt><span>precision :</span></dt><dd>0.01</dd><dt><span>dataset_id :</span></dt><dd>0b2bd62cc42f3096136f11e9</dd><dt><span>standard_name :</span></dt><dd>wind_speed</dd></dl></div><div class='xr-var-data'><pre>array([0.95, 0.85, 0.95, ..., 0.65, 0.64, 0.85], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1592bcd2-3185-4efb-9931-2457d80ae7ef' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1592bcd2-3185-4efb-9931-2457d80ae7ef' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-16ab7318-dfb8-4bc0-80db-d2828199fd25' class='xr-var-data-in' type='checkbox'><label for='data-16ab7318-dfb8-4bc0-80db-d2828199fd25' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array(-43.47)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-426a255c-cad2-434a-a112-87ac4d99fae6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-426a255c-cad2-434a-a112-87ac4d99fae6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-98a0a334-84f9-4326-b2b4-a296311954fa' class='xr-var-data-in' type='checkbox'><label for='data-98a0a334-84f9-4326-b2b4-a296311954fa' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array(171.672)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>relative_humidity</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>77.9 76.9 81.8 ... 74.6 73.5 73.6</div><input id='attrs-53170f49-62e8-4435-8362-746d06124415' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-53170f49-62e8-4435-8362-746d06124415' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5a083cb5-8991-4e2d-b098-c0c27c5a72fc' class='xr-var-data-in' type='checkbox'><label for='data-5a083cb5-8991-4e2d-b098-c0c27c5a72fc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>feature :</span></dt><dd>atmosphere</dd><dt><span>parameter :</span></dt><dd>relative_humidity</dd><dt><span>method :</span></dt><dd>sensor_recording</dd><dt><span>product_code :</span></dt><dd>raw_data</dd><dt><span>owner :</span></dt><dd>FENZ</dd><dt><span>aggregation_statistic :</span></dt><dd>mean</dd><dt><span>frequency_interval :</span></dt><dd>1H</dd><dt><span>utc_offset :</span></dt><dd>0H</dd><dt><span>units :</span></dt><dd>m^3/m^3</dd><dt><span>license :</span></dt><dd>https://creativecommons.org/licenses/by/4.0/</dd><dt><span>spatial_distribution :</span></dt><dd>sparse</dd><dt><span>geometry_type :</span></dt><dd>Point</dd><dt><span>grouping :</span></dt><dd>none</dd><dt><span>attribution :</span></dt><dd>Data licenced by FENZ</dd><dt><span>precision :</span></dt><dd>0.1</dd><dt><span>dataset_id :</span></dt><dd>11de048221534727a01eee26</dd><dt><span>standard_name :</span></dt><dd>relative_humidity</dd></dl></div><div class='xr-var-data'><pre>array([77.9, 76.9, 81.8, ..., 74.6, 73.5, 73.6], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>volumetric_water_content</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>37.6 37.0 37.0 ... 27.0 27.0 27.0</div><input id='attrs-81962447-0ffe-412d-bb8e-af30c76771d7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-81962447-0ffe-412d-bb8e-af30c76771d7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bd361ab1-5cd4-4dbd-bd8d-1c2634ce4131' class='xr-var-data-in' type='checkbox'><label for='data-bd361ab1-5cd4-4dbd-bd8d-1c2634ce4131' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>feature :</span></dt><dd>pedosphere</dd><dt><span>parameter :</span></dt><dd>volumetric_water_content</dd><dt><span>method :</span></dt><dd>sensor_recording</dd><dt><span>product_code :</span></dt><dd>raw_data</dd><dt><span>owner :</span></dt><dd>FENZ</dd><dt><span>aggregation_statistic :</span></dt><dd>mean</dd><dt><span>frequency_interval :</span></dt><dd>1H</dd><dt><span>utc_offset :</span></dt><dd>0H</dd><dt><span>units :</span></dt><dd>m^3/m^3</dd><dt><span>license :</span></dt><dd>https://creativecommons.org/licenses/by/4.0/</dd><dt><span>spatial_distribution :</span></dt><dd>sparse</dd><dt><span>geometry_type :</span></dt><dd>Point</dd><dt><span>grouping :</span></dt><dd>none</dd><dt><span>attribution :</span></dt><dd>Data licenced by FENZ</dd><dt><span>precision :</span></dt><dd>0.1</dd><dt><span>dataset_id :</span></dt><dd>38138ea1c3350031d1b217f6</dd><dt><span>standard_name :</span></dt><dd>soil_moisture</dd></dl></div><div class='xr-var-data'><pre>array([37.600002, 37.      , 37.      , ..., 27.      , 27.      ,\n",
       "       27.      ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>wind_direction</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>217.9 146.9 219.2 ... 219.8 137.2</div><input id='attrs-07876a06-9493-4f12-80e8-ca38fa59e1f1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-07876a06-9493-4f12-80e8-ca38fa59e1f1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4e16bbee-3723-4947-8971-544f35b63479' class='xr-var-data-in' type='checkbox'><label for='data-4e16bbee-3723-4947-8971-544f35b63479' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>feature :</span></dt><dd>atmosphere</dd><dt><span>parameter :</span></dt><dd>wind_direction</dd><dt><span>method :</span></dt><dd>sensor_recording</dd><dt><span>product_code :</span></dt><dd>raw_data</dd><dt><span>owner :</span></dt><dd>FENZ</dd><dt><span>aggregation_statistic :</span></dt><dd>mean</dd><dt><span>frequency_interval :</span></dt><dd>1H</dd><dt><span>utc_offset :</span></dt><dd>0H</dd><dt><span>units :</span></dt><dd>deg</dd><dt><span>license :</span></dt><dd>https://creativecommons.org/licenses/by/4.0/</dd><dt><span>spatial_distribution :</span></dt><dd>sparse</dd><dt><span>geometry_type :</span></dt><dd>Point</dd><dt><span>grouping :</span></dt><dd>none</dd><dt><span>attribution :</span></dt><dd>Data licenced by FENZ</dd><dt><span>precision :</span></dt><dd>0.1</dd><dt><span>dataset_id :</span></dt><dd>a7561f55ad53ea0647f8ce56</dd><dt><span>standard_name :</span></dt><dd>wind_from_direction</dd></dl></div><div class='xr-var-data'><pre>array([217.90001, 146.90001, 219.2    , ..., 198.90001, 219.8    ,\n",
       "       137.2    ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>precipitation</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-ddd67d3f-3a90-4f1a-8384-be7410977d43' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ddd67d3f-3a90-4f1a-8384-be7410977d43' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-66dc4b47-5317-4854-8b23-79d749f8a991' class='xr-var-data-in' type='checkbox'><label for='data-66dc4b47-5317-4854-8b23-79d749f8a991' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>feature :</span></dt><dd>atmosphere</dd><dt><span>parameter :</span></dt><dd>precipitation</dd><dt><span>method :</span></dt><dd>sensor_recording</dd><dt><span>product_code :</span></dt><dd>raw_data</dd><dt><span>owner :</span></dt><dd>FENZ</dd><dt><span>aggregation_statistic :</span></dt><dd>cumulative</dd><dt><span>frequency_interval :</span></dt><dd>1H</dd><dt><span>utc_offset :</span></dt><dd>0H</dd><dt><span>units :</span></dt><dd>mm</dd><dt><span>license :</span></dt><dd>https://creativecommons.org/licenses/by/4.0/</dd><dt><span>spatial_distribution :</span></dt><dd>sparse</dd><dt><span>geometry_type :</span></dt><dd>Point</dd><dt><span>grouping :</span></dt><dd>none</dd><dt><span>attribution :</span></dt><dd>Data licenced by FENZ</dd><dt><span>precision :</span></dt><dd>0.1</dd><dt><span>dataset_id :</span></dt><dd>c5f55d97e71e7cd73295ad7f</dd><dt><span>standard_name :</span></dt><dd>precipitation_amount</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temperature</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>23.3 23.4 21.2 ... 17.8 19.2 20.2</div><input id='attrs-17f4cbf0-b63c-4832-857f-e4635be4b2ca' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-17f4cbf0-b63c-4832-857f-e4635be4b2ca' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9b9ad2ac-7d72-4ce1-8f3a-d206cef2b9f1' class='xr-var-data-in' type='checkbox'><label for='data-9b9ad2ac-7d72-4ce1-8f3a-d206cef2b9f1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>feature :</span></dt><dd>atmosphere</dd><dt><span>parameter :</span></dt><dd>temperature</dd><dt><span>method :</span></dt><dd>sensor_recording</dd><dt><span>product_code :</span></dt><dd>raw_data</dd><dt><span>owner :</span></dt><dd>FENZ</dd><dt><span>aggregation_statistic :</span></dt><dd>mean</dd><dt><span>frequency_interval :</span></dt><dd>1H</dd><dt><span>utc_offset :</span></dt><dd>0H</dd><dt><span>units :</span></dt><dd>degC</dd><dt><span>license :</span></dt><dd>https://creativecommons.org/licenses/by/4.0/</dd><dt><span>spatial_distribution :</span></dt><dd>sparse</dd><dt><span>geometry_type :</span></dt><dd>Point</dd><dt><span>grouping :</span></dt><dd>none</dd><dt><span>attribution :</span></dt><dd>Data licenced by FENZ</dd><dt><span>precision :</span></dt><dd>0.1</dd><dt><span>dataset_id :</span></dt><dd>dddb02cd5cb7ae191311ab19</dd><dt><span>standard_name :</span></dt><dd>air_temperature</dd></dl></div><div class='xr-var-data'><pre>array([23.300001, 23.4     , 21.2     , ..., 17.800001, 19.2     ,\n",
       "       20.2     ], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ae667c00-d3cf-4bca-89a2-bfe2aed2fe8b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ae667c00-d3cf-4bca-89a2-bfe2aed2fe8b' class='xr-section-summary' >Attributes: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>featureType :</span></dt><dd>timeSeries</dd><dt><span>title :</span></dt><dd>mean wind_speed in m/s of the atmosphere by a sensor_recording owned by FENZ</dd><dt><span>institution :</span></dt><dd>FENZ</dd><dt><span>license :</span></dt><dd>https://creativecommons.org/licenses/by/4.0/</dd><dt><span>source :</span></dt><dd>sensor_recording</dd><dt><span>history :</span></dt><dd>20211024T200003Z: Generated</dd><dt><span>version :</span></dt><dd>3</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:                   (time: 17544)\n",
       "Coordinates:\n",
       "  * time                      (time) datetime64[ns] 2019-01-01 ... 2020-12-31...\n",
       "    geometry                  <U42 '01010000002FDD2406817565405C8FC2F528BC45C0'\n",
       "    height                    int8 2\n",
       "Data variables:\n",
       "    externalId                object ...\n",
       "    station_id                object ...\n",
       "    ref                       object ...\n",
       "    name                      object ...\n",
       "    wind_speed                (time) float32 ...\n",
       "    lat                       float64 ...\n",
       "    lon                       float64 ...\n",
       "    relative_humidity         (time) float32 77.9 76.9 81.8 ... 74.6 73.5 73.6\n",
       "    volumetric_water_content  (time) float32 37.6 37.0 37.0 ... 27.0 27.0 27.0\n",
       "    wind_direction            (time) float32 217.9 146.9 219.2 ... 219.8 137.2\n",
       "    precipitation             (time) float32 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0\n",
       "    temperature               (time) float32 23.3 23.4 21.2 ... 17.8 19.2 20.2\n",
       "Attributes:\n",
       "    featureType:  timeSeries\n",
       "    title:        mean wind_speed in m/s of the atmosphere by a sensor_record...\n",
       "    institution:  FENZ\n",
       "    license:      https://creativecommons.org/licenses/by/4.0/\n",
       "    source:       sensor_recording\n",
       "    history:      20211024T200003Z: Generated\n",
       "    version:      3"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_slice"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0d493940-3210-479f-a407-4333a3a5628c",
   "metadata": {
    "tags": []
   },
   "source": [
    "### Composite average anlysis \n",
    "\n",
    "Composite average is commonly used for climatological anlysis."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "e0623f05-706e-46d9-87f9-f92e37918b33",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 960x720 with 2 Axes>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot_hourly_composite(data_slice[\"temperature\"],average=\"month\",save_fig=True,save_files=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "83567a05-e533-4d3c-a029-c43564aee401",
   "metadata": {},
   "source": [
    "### violin plot"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "57054d93-0828-44e8-8902-0dc8661ea126",
   "metadata": {},
   "source": [
    "#### select time period"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "f5f8c247-66f2-4c8a-9293-38d9ed3345b1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 960x720 with 1 Axes>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot_violinplot(data_slice[\"wind_speed\"],\"month\",save_fig=True,save_files=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "633ac1e8-7131-41a6-b411-fac9629e0497",
   "metadata": {},
   "source": [
    "#### Windrose"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "437ed71d-565e-451d-b013-5993c8b5378f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x640 with 1 Axes>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot_wind_rose(data_slice.wind_speed,data_slice.wind_direction,save_fig=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5147d52e-3442-4127-87f8-7cbe88240b0a",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python (baseline)",
   "language": "python",
   "name": "baseline"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}