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Dataset Title:	EMSO Ligure Ouest : ALBATROSS capteur MICROCAT (CSV files from 2021-07)
Institution:	MIO UMR7294 CNRS / OSU Pytheas (Dataset ID: Emso_Ligure_Ouest_Albatross_Microcat_CSV_2021)
Range:	depth = -6034.839 to 2370.858m, time = 2000-01-01T00:00:00Z to 2023-05-16T23:00:13Z
Information:	Summary \| License \| Metadata \| Background \| Subset \| Data Access Form

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Server-side Functions

distinct()

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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.

The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 9.466848e+8, 1.684278013e+9;
    String axis "T";
    String ioos_category "Time";
    String long_name "Date";
    String source_name "date";
    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";
  }
  Sensor_serial_number {
    String ioos_category "Statistics";
    String long_name "Sensor Serial Number";
  }
  Sensor_Depth_Theoric {
    Int16 _FillValue 32767;
    Int16 actual_range 500, 2400;
    String ioos_category "Location";
    String long_name "Sensor Depth Theoric";
  }
  Temp_insitu {
    Float32 actual_range -273.15, 22.8412;
    String ioos_category "Unknown";
    String long_name "Temp Insitu";
  }
  Conductivity {
    Float32 actual_range -1.0, 4.89159;
    Float64 colorBarMaximum 40.0;
    Float64 colorBarMinimum 30.0;
    String ioos_category "Salinity";
    String long_name "Sea Water Electrical Conductivity";
    String standard_name "sea_water_electrical_conductivity";
  }
  Pressure {
    Float32 actual_range -5990.591, 2403.465;
    String ioos_category "Pressure";
    String long_name "Pressure";
  }
  Oxygen {
    Float32 actual_range -999.99, 46.969;
    String ioos_category "Dissolved O2";
    String long_name "Oxygen";
  }
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Float32 actual_range -6034.839, 2370.858;
    String axis "Z";
    Float64 colorBarMaximum 8000.0;
    Float64 colorBarMinimum -8000.0;
    String colorBarPalette "TopographyDepth";
    String ioos_category "Location";
    String long_name "Depth";
    String positive "down";
    String standard_name "depth";
    String units "m";
  }
  Salinity {
    Float32 actual_range 0.0, 38.73796;
    Float64 colorBarMaximum 37.0;
    Float64 colorBarMinimum 32.0;
    String ioos_category "Salinity";
    String long_name "Sea Water Practical Salinity";
    String standard_name "sea_water_practical_salinity";
    String units "PSU";
  }
  Temp_Pot {
    Float32 actual_range -1161.737, 22.8412;
    String ioos_category "Unknown";
    String long_name "Temp Pot";
  }
  O2_saturation {
    Float32 actual_range 0.0, 269.7738;
    String ioos_category "Dissolved O2";
    String long_name "O2 Saturation";
  }
  SigmaTheta {
    Float32 actual_range -1.604125e+7, 29.1435;
    String ioos_category "Physical Oceanography";
    String long_name "Sea Water Sigma Theta";
    String standard_name "sea_water_sigma_theta";
  }
 }
  NC_GLOBAL {
    String cdm_data_type "Other";
    String Conventions "COARDS, CF-1.6, ACDD-1.3, NCCSV-1.2";
    String creator_name "MIO UMR7294 CNRS / OSU Pytheas";
    String creator_type "institution";
    String creator_url "http://www.emso-fr.org/EMSO-Western-Ligurian-Sea/Scientific-objectives";
    String defaultGraphQuery "time%2CPressure%2CTemp_insitu&time>=2021-10-01T00%3A00%3A00Z&time<=2021-10-10T00%3A00%3A00Z&.draw=markers&.marker=4|3&.color=0x000000&.colorBar=|||||&.yRange=||false|&.bgColor=0xffccccff";
    Float64 geospatial_vertical_max 2370.858;
    Float64 geospatial_vertical_min -6034.839;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2023-12-10T17:54:45Z (local files)
2023-12-10T17:54:45Z https://erddap.emso-fr.org/tabledap/Emso_Ligure_Ouest_Albatross_Microcat_CSV_2021.das";
    String infoUrl "http://www.emso-fr.org/EMSO-Western-Ligurian-Sea/Scientific-objectives";
    String institution "MIO UMR7294 CNRS / OSU Pytheas";
    String keywords "2021-07, albatross, capteur, cnrs, common, conductivity, csv, data, date, density, depth, dissolved, dissolved o2, earth, Earth Science > Oceans > Salinity/Density > Conductivity, Earth Science > Oceans > Salinity/Density > Density, Earth Science > Oceans > Salinity/Density > Salinity, electrical, files, format, insitu, ligure, microcat, mio, mso, network, number, O2, O2_saturation, ocean, oceanography, oceans, oregon, osu, ouest, oxygen, physical, physical oceanography, pot, practical, pressure, pytheas, salinity, saturation, science, sea, sea_water_electrical_conductivity, sea_water_practical_salinity, sea_water_sigma_theta, seawater, sensor, Sensor_Depth_Theoric, Sensor_serial_number, serial, sigma, SigmaTheta, state, statistics, Temp_insitu, Temp_Pot, temperature, theoric, theta, time, umr7294, university, water";
    String keywords_vocabulary "GCMD Science Keywords";
    String license 
"The data may be used and redistributed for free but is not intended
for legal use, since it may contain inaccuracies. Neither the data
Contributor, ERD, NOAA, nor the United States Government, nor any
of their employees or contractors, makes any warranty, express or
implied, including warranties of merchantability and fitness for a
particular purpose, or assumes any legal liability for the accuracy,
completeness, or usefulness, of this information.";
    String sourceUrl "(local files)";
    String standard_name_vocabulary "CF Standard Name Table v70";
    String subsetVariables "Sensor_serial_number, Sensor_Depth_Theoric, Oxygen";
    String summary "EMSO Ligure Ouest (CSV files). EMSO Ligure Ouest : ALBATROSS : traitement temps reel de fichiers de mesueurs sur une ligne instrumentee - deploiement 2021-07";
    String testOutOfDate "now-1day";
    String time_coverage_end "2023-05-16T23:00:13Z";
    String time_coverage_start "2000-01-01T00:00:00Z";
    String title "EMSO Ligure Ouest : ALBATROSS capteur MICROCAT (CSV files from 2021-07)";
  }
}

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 (external link)

Data Access Protocol (DAP) (external link)

and its selection constraints (external link)

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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