ERDDAP > tabledap > Make A Graph

Dataset Title:	NAUTILOS - Citizien Science - Temperature in the water column
Institution:	ETT S.p.A.   (Dataset ID: env_logger_data_test)
Range:	longitude = 8.855 to 9.20411°E, latitude = 44.421 to 44.77011°N, depth = 0.0 to 0.0m, time = 2023-09-06T09:43:10Z to 2024-10-31T10:40:46Z
Information:	Summary | License | FGDC | ISO 19115 | Metadata | Background | Subset | Data Access Form | Files

 

Graph Type:  lines linesAndMarkers markers sticks vectors X Axis:  time temp latitude longitude accuracy depth Y Axis:  time temp latitude longitude accuracy depth Color:  time temp latitude longitude accuracy depth   Constraints Optional Constraint #1 Optional Constraint #2 time temp serial_number sensor_id latitude longitude accuracy depth     != =~ <= >= = < >     != =~ <= >= = < >     time temp serial_number sensor_id latitude longitude accuracy depth     != =~ <= >= = < >     != =~ <= >= = < >     time temp serial_number sensor_id latitude longitude accuracy depth     != =~ <= >= = < >     != =~ <= >= = < >     time temp serial_number sensor_id latitude longitude accuracy depth     != =~ <= >= = < >     != =~ <= >= = < >     time temp serial_number sensor_id latitude longitude accuracy depth     != =~ <= >= = < >     != =~ <= >= = < >       Server-side Functions  distinct() orderBy orderByDescending orderByClosest orderByCount orderByLimit orderByMax orderByMin orderByMinMax orderByMean orderBySum (" time temp serial_number sensor_id latitude longitude accuracy depth time temp serial_number sensor_id latitude longitude accuracy depth time temp serial_number sensor_id latitude longitude accuracy depth time temp serial_number sensor_id latitude longitude accuracy depth ")   Graph Settings Marker Type:  None Plus X Dot Square Filled Square Circle Filled Circle Up Triangle Filled Up Triangle Borderless Filled Square Borderless Filled Circle Borderless Filled Up Triangle  Size:  3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 Color:  Color Bar:  BlackBlueWhite BlackGreenWhite BlackRedWhite BlackWhite BlueWhiteRed BlueWideWhiteRed LightRainbow Ocean OceanDepth Rainbow Rainbow2 Rainfall ReverseRainbow RedWhiteBlue RedWhiteBlue2 RedWideWhiteBlue Spectrum Topography TopographyDepth WhiteBlueBlack WhiteGreenBlack WhiteRedBlack WhiteBlack YellowRed KT_algae KT_amp KT_balance KT_curl KT_deep KT_delta KT_dense KT_gray KT_haline KT_ice KT_matter KT_oxy KT_phase KT_solar KT_speed KT_tempo KT_thermal KT_turbid EK80  Continuity:  Continuous Discrete  Scale:  Linear Log    Minimum:   Maximum:   N Sections:  2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 Draw land mask:  under over outline off Y Axis Minimum:   Maximum:    Ascending Descending Linear Log   Redraw the Graph (Please be patient. It may take a while to get the data.)   Optional: Then set the File Type: .asc .csv .csvp .csv0 .dataTable .das .dds .dods .esriCsv .fgdc .geoJson .graph .help .html .htmlTable .iso19115 .itx .json .jsonlCSV1 .jsonlCSV .jsonlKVP .mat .nc .ncHeader .ncCF .ncCFHeader .ncCFMA .ncCFMAHeader .nccsv .nccsvMetadata .ncoJson .odvTxt .subset .tsv .tsvp .tsv0 .wav .xhtml .kml .smallPdf .pdf .largePdf .smallPng .png .largePng .transparentPng (File Type information) and or view the URL: (Documentation / Bypass this form )

Click on the map to specify a new center point. Zoom:  Time range:  1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 second(s) minute(s) hour(s) day(s) month(s) year(s)

 

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Things You Can Do With Your Graphs

Well, you can do anything you want with your graphs, of course. But some things you might not have considered are:

• Web page authors can embed a graph of the latest data in a web page using HTML <img> tags.
• Anyone can use ERDDAPs Slide Sorter to build a personal web page that displays graphs with the latest data (or other images or HTML content), each in its own, draggable slide.
   

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The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 1.69399339e+9, 1.730371246e+9;
    String axis "T";
    String ioos_category "Time";
    String long_name "Time";
    String standard_name "time";
    String time_origin "01-JAN-1970 00:00:00";
    String time_precision "1970-01-01T00:00:00Z";
    String units "seconds since 1970-01-01T00:00:00Z";
  }
  temp {
    Float32 actual_range 21.1, 34.3;
    String long_name "Temperature";
    String SDN "SDN:P01::TEMPPR01";
    String units "degrees Celsius";
  }
  serial_number {
    String long_name "Serial Number";
  }
  sensor_id {
    String long_name "Sensor Id";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 actual_range 44.421, 44.77011;
    String axis "Y";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String ioos_category "Location";
    String long_name "Latitude";
    String standard_name "latitude";
    String units "degrees_north";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float32 actual_range 8.855, 9.20411;
    String axis "X";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
  }
  accuracy {
    Float32 actual_range 2.5, 11.1;
    String long_name "GPS Position Accuracy";
    String units "meters";
  }
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Float32 actual_range 0.0, 0.0;
    String axis "Z";
    String ioos_category "Location";
    String long_name "Sensor depth";
    String positive "down";
    String standard_name "depth";
    String units "m";
  }
 }
  NC_GLOBAL {
    String cdm_data_type "Point";
    String Citation "This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No. 101000825 (NAUTILOS). This output reflects only the author's view and the European Union cannot be held responsible for any use that may be made of the information contained therein.";
    String Conventions "COARDS, CF-1.6, ACDD-1.3";
    Float64 Easternmost_Easting 9.20411;
    String EDMERP_code "13720";
    String featureType "Point";
    String funding_ID "101000825";
    String funding_statement "This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No. 101000825 (NAUTILOS). This output reflects only the author's view and the European Union cannot be held responsible for any use that may be made of the information contained therein";
    Float64 geospatial_lat_max 44.77011;
    Float64 geospatial_lat_min 44.421;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 9.20411;
    Float64 geospatial_lon_min 8.855;
    String geospatial_lon_units "degrees_east";
    Float64 geospatial_vertical_max 0.0;
    Float64 geospatial_vertical_min 0.0;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2024-11-23T14:07:57Z (local files)
2024-11-23T14:07:57Z http://data-nautilos-h2020.eu/tabledap/env_logger_data_test.das";
    String infoUrl "https://www.nautilos-h2020.eu/";
    String institution "ETT S.p.A.";
    String keywords "temperature, temperature_in_water_column, time";
    String license "CC-BY 4.0";
    Float64 Northernmost_Northing 44.77011;
    String Project_DOI "https://doi.org/10.3030/101000825";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 44.421;
    String standard_name_vocabulary "CF Standard Name Table v70";
    String subsetVariables "serial_number, sensor_id, accuracy";
    String summary "Temperature in the water column collected with static temperature loggher with NFC technology in Citizen Scinece campaigns";
    String testOutOfDate "now-9days";
    String time_coverage_end "2024-10-31T10:40:46Z";
    String time_coverage_start "2023-09-06T09:43:10Z";
    String title "NAUTILOS - Citizien Science - Temperature in the water column";
    Float64 Westernmost_Easting 8.855;
  }
}

 

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Using tabledap to Request Data and Graphs from Tabular Datasets

tabledap lets you request a data subset, a graph, or a map from a tabular dataset (for example, buoy data), via a specially formed URL. tabledap uses the OPeNDAP Data Access Protocol (DAP) and its selection constraints.

The URL specifies what you want: the dataset, a description of the graph or the subset of the data, and the file type for the response.

• (easy) You can get data by using the dataset's Data Access Form or Subset form. They make the URL for you.
• (easy) You can make a graph or map by using the dataset's Make A Graph form. It makes the URL for you.
• (not hard) You can bypass the forms and get the data or make a graph or map by generating the URL by hand or with a computer program or script.

Tabledap request URLs must be in the form
https://coastwatch.pfeg.noaa.gov/erddap/tabledap/datasetID.fileType{?query}
For example,
https://coastwatch.pfeg.noaa.gov/erddap/tabledap/pmelTaoDySst.htmlTable?longitude,latitude,time,station,wmo_platform_code,T_25&time>=2015-05-23T12:00:00Z&time<=2015-05-31T12:00:00Z
Thus, the query is often a comma-separated list of desired variable names, followed by a collection of constraints (e.g., variable<value), each preceded by '&' (which is interpreted as "AND").

For details, see the tabledap Documentation.

 

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