ERDDAP > tabledap > Data Access Form

Dataset Title:	Daily Fish Counts at Newport, County Mayo (1970-2019)
Institution:	Marine Institute   (Dataset ID: newport_daily_fish_counts)
Information:	Summary | License | FGDC | ISO 19115 | Metadata | Background | Subset | Make a graph

 

Variable	Optional Constraint #1		Optional Constraint #2		Minimum    or a List of Values	Maximum
time (Date Time, UTC)	!= =~ <= >= = < >		!= =~ <= >= = < >
latitude (degrees_north)	!= =~ <= >= = < >		!= =~ <= >= = < >		-9.578038
longitude (degrees_east)	!= =~ <= >= = < >		!= =~ <= >= = < >		53.922202
year	!= =~ <= >= = < >		!= =~ <= >= = < >		1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019
month	!= =~ <= >= = < >		!= =~ <= >= = < >		1 2 3 4 5 6 7 8 9 10 11 12
day	!= =~ <= >= = < >		!= =~ <= >= = < >		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
station (station id)	!= =~ <= >= = < >		!= =~ <= >= = < >		"Newport"
salmon_smolt_count_per_day (count d-1)	!= =~ <= >= = < >		!= =~ <= >= = < >
eel_count_per_day (count d-1)	!= =~ <= >= = < >		!= =~ <= >= = < >
sea_trout_smolt_count_per_day (count d-1)	!= =~ <= >= = < >		!= =~ <= >= = < >

 

Server-side Functions

distinct()

orderBy orderByClosest orderByCount orderByLimit orderByMax orderByMin orderByMinMax orderByMean (" time latitude longitude year month day station salmon_smolt_count_per_day eel_count_per_day sea_trout_smolt_count_per_day time latitude longitude year month day station salmon_smolt_count_per_day eel_count_per_day sea_trout_smolt_count_per_day time latitude longitude year month day station salmon_smolt_count_per_day eel_count_per_day sea_trout_smolt_count_per_day time latitude longitude year month day station salmon_smolt_count_per_day eel_count_per_day sea_trout_smolt_count_per_day time latitude longitude year month day station salmon_smolt_count_per_day eel_count_per_day sea_trout_smolt_count_per_day ")

File type: (more info) .asc - View OPeNDAP-style ISO-8859-1 comma-separated text. .csv - Download a ISO-8859-1 comma-separated text table (line 1: names; line 2: units; ISO 8601 times). .csvp - Download a ISO-8859-1 .csv file with line 1: name (units). Times are ISO 8601 strings. .csv0 - Download a ISO-8859-1 .csv file without column names or units. Times are ISO 8601 strings. .dataTable - A JSON file formatted for use with the Google Visualization client library (Google Charts). .das - View the dataset's metadata via an ISO-8859-1 OPeNDAP Dataset Attribute Structure (DAS). .dds - View the dataset's structure via an ISO-8859-1 OPeNDAP Dataset Descriptor Structure (DDS). .dods - OPeNDAP clients use this to download the data in the DODS binary format. .esriCsv - Download a ISO_8859_1 .csv file for ESRI's ArcGIS 9.x and below (separate date and time columns). .fgdc - View the dataset's UTF-8 FGDC .xml metadata. .geoJson - Download longitude,latitude,otherColumns data as a UTF-8 GeoJSON .json file. .graph - View a Make A Graph web page. .help - View a web page with a description of tabledap. .html - View an OPeNDAP-style HTML Data Access Form. .htmlTable - View a UTF-8 .html web page with the data in a table. Times are ISO 8601 strings. .iso19115 - View the dataset's ISO 19115-2/19139 UTF-8 .xml metadata. .itx - Download an ISO-8859-1 Igor Text File. Each response column becomes a wave. .json - View a table-like UTF-8 JSON file (missing value = 'null'; times are ISO 8601 strings). .jsonlCSV1 - View a UTF-8 JSON Lines CSV file with column names on line 1 (mv = 'null'; times are ISO 8601 strings). .jsonlCSV - View a UTF-8 JSON Lines CSV file without column names (mv = 'null'; times are ISO 8601 strings). .jsonlKVP - View a UTF-8 JSON Lines file with Key:Value pairs (missing value = 'null'; times are ISO 8601 strings). .mat - Download a MATLAB binary file. .nc - Download a flat, table-like, NetCDF-3 binary file with COARDS/CF/ACDD metadata. .ncHeader - View the UTF-8 header (the metadata) for the NetCDF-3 .nc file. .ncCF - Download a NetCDF-3 CF Discrete Sampling Geometries file (Contiguous Ragged Array). .ncCFHeader - View the UTF-8 header (the metadata) for the .ncCF file. .ncCFMA - Download a NetCDF-3 CF Discrete Sampling Geometries file (Multidimensional Array). .ncCFMAHeader - View the UTF-8 header (the metadata) for the .ncCFMA file. .nccsv - Download a NetCDF-3-like 7-bit ASCII NCCSV .csv file with COARDS/CF/ACDD metadata. .nccsvMetadata - View the dataset's metadata as the top half of a 7-bit ASCII NCCSV .csv file. .ncoJson - Download a UTF-8 NCO lvl=2 JSON file with COARDS/CF/ACDD metadata. .odvTxt - Download longitude,latitude,time,otherColumns as an ISO-8859-1 ODV Generic Spreadsheet File (.txt). .subset - View an HTML form which uses faceted search to simplify picking subsets of the data. .tsv - Download a ISO-8859-1 tab-separated text table (line 1: names; line 2: units; ISO 8601 times). .tsvp - Download a ISO-8859-1 .tsv file with line 1: name (units). Times are ISO 8601 strings. .tsv0 - Download a ISO-8859-1 .tsv file without column names or units. Times are ISO 8601 strings. .wav - Download a .wav audio file. All columns must be numeric and of the same type. .xhtml - View a UTF-8 XHTML (XML) file with the data in a table. Times are ISO 8601 strings. .kml - View a .kml file, suitable for Google Earth. .smallPdf - View a small .pdf image file with a graph or map. .pdf - View a standard, medium-sized .pdf image file with a graph or map. .largePdf - View a large .pdf image file with a graph or map. .smallPng - View a small .png image file with a graph or map. .png - View a standard, medium-sized .png image file with a graph or map. .largePng - View a large .png image file with a graph or map. .transparentPng - View a .png image file (just the data, without axes, landmask, or legend).

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The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  time {
    String _CoordinateAxisType "Time";
    String axis "T";
    String ioos_category "Time";
    String long_name "Date Time";
    String standard_name "time";
    String time_origin "01-JAN-1970 00:00:00";
    String units "seconds since 1970-01-01T00:00:00Z";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 actual_range -9.578038, -9.578038;
    String axis "Y";
    String ioos_category "Location";
    String long_name "Latitude";
    String standard_name "latitude";
    String units "degrees_north";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float64 actual_range 53.922202, 53.922202;
    String axis "X";
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
  }
  year {
    Int32 actual_range 1970, 2019;
    String ioos_category "Time";
    String long_name "Year";
  }
  month {
    Int32 actual_range 1, 12;
    String ioos_category "Time";
    String long_name "Month";
  }
  day {
    Int32 actual_range 1, 31;
    String ioos_category "Time";
    String long_name "day";
  }
  station {
    String cf_role "timeseries_id";
    String ioos_category "Identifier";
    String long_name "station id";
  }
  salmon_smolt_count_per_day {
    String colorBarMaximum "1000.0";
    String colorBarMinimum "0.0";
    String comment "count of Salmon (Salmo salar) Smolts per day";
    String ioos_category "Fish Abundance";
    String long_name "salmon_smolt_count_per_day";
    String units "count d-1";
  }
  eel_count_per_day {
    String colorBarMaximum "1000.0";
    String colorBarMinimum "0.0";
    String comment "count of Eel (Anguilla anguilla) per day";
    String ioos_category "Fish Abundance";
    String long_name "eel_count_per_day";
    String units "count d-1";
  }
  sea_trout_smolt_count_per_day {
    String colorBarMaximum "1000.0";
    String colorBarMinimum "0.0";
    String comment "count of Sea trout (Salmo trutta) Smolts per day";
    String ioos_category "Fish Abundance";
    String long_name "sea_trout_smolt_count_per_day";
    String units "count d-1";
  }
 }
  NC_GLOBAL {
    String cdm_data_type "TimeSeries";
    String cdm_timeseries_variables "station, longitude, latitude, year, month";
    String Conventions "COARDS, CF-1.6, ACDD-1.3";
    String creator_name "Marien Institute";
    String defaultDataQuery "&year=%222019%22&month=%227%22";
    String defaultGraphQuery "time,salmon_smolt_count_per_day&year=%222019%22&.draw=lines";
    Float64 Easternmost_Easting 53.922202;
    String featureType "TimeSeries";
    Float64 geospatial_lat_max -9.578038;
    Float64 geospatial_lat_min -9.578038;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 53.922202;
    Float64 geospatial_lon_min 53.922202;
    String geospatial_lon_units "degrees_east";
    String history 
"2024-12-21T11:59:34Z (source database)
2024-12-21T11:59:34Z https://erddap.marine.ie/erddap/tabledap/newport_daily_fish_counts.html";
    String infoUrl "https://data.marine.ie/geonetwork/srv/eng/catalog.search#/metadata/ie.marine.data:dataset.4343";
    String institution "Marine Institute";
    String keywords "fish counts, latitude, longitude, Mayo, Newport";
    String license "Creative Commons Attribution 4.0 (https://creativecommons.org/licenses/by/4.0/)";
    Float64 Northernmost_Northing -9.578038;
    String sourceUrl "(source database)";
    Float64 Southernmost_Northing -9.578038;
    String subsetVariables "station, longitude, latitude, year, month, day";
    String summary "Newport Daily Fish Counter Time Series";
    String title "Daily Fish Counts at Newport, County Mayo (1970-2019)";
    Float64 Westernmost_Easting 53.922202;
  }
}

 

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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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