PyLiPD User API

The following describes the main classes that makes up PyLiPD. Most users will only interface with the functionalies contained in these classes.

LiPD (pylipd.lipd.LiPD)

class pylipd.lipd.LiPD(graph=None)[source]

The LiPD class describes a LiPD (Linked Paleo Data) object. It contains an RDF Graph which is serialization of the LiPD data into an RDF graph containing terms from the LiPD Ontology <http://linked.earth/Ontology/release/core/1.2.0/index-en.html> How to browse and query LiPD objects is described in a short example below.

Examples

In this example, we read an online LiPD file and convert it into a time series object dictionary.

from pylipd.lipd import LiPD

lipd = LiPD()
lipd.load(["https://lipdverse.org/data/LCf20b99dfe8d78840ca60dfb1f832b9ec/1_0_1//Nunalleq.Ledger.2018.lpd"])

ts_list = lipd.get_timeseries(lipd.get_all_dataset_names())

for dsname, tsos in ts_list.items():
    for tso in tsos:
        if 'paleoData_variableName' in tso:
            print(dsname+': '+tso['paleoData_variableName']+': '+tso['archiveType'])
Loading 1 LiPD files
Loaded..
Extracting timeseries from dataset: Nunalleq.Ledger.2018 ...
Nunalleq.Ledger.2018: depth: Archaeological
Nunalleq.Ledger.2018: precipitation: Archaeological
Nunalleq.Ledger.2018: uncertainty: Archaeological
Nunalleq.Ledger.2018: precipitation: Archaeological
Nunalleq.Ledger.2018: uncertainty: Archaeological
Nunalleq.Ledger.2018: uncertainty: Archaeological
Nunalleq.Ledger.2018: uncertainty: Archaeological
Nunalleq.Ledger.2018: age: Archaeological
Nunalleq.Ledger.2018: uncertainty: Archaeological
Nunalleq.Ledger.2018: uncertainty: Archaeological
Nunalleq.Ledger.2018: age: Archaeological
Nunalleq.Ledger.2018: uncertainty: Archaeological
Nunalleq.Ledger.2018: uncertaintyHigh: Archaeological
Nunalleq.Ledger.2018: uncertainty: Archaeological
Nunalleq.Ledger.2018: temperature: Archaeological
Nunalleq.Ledger.2018: uncertainty: Archaeological
Nunalleq.Ledger.2018: precipitation: Archaeological
Nunalleq.Ledger.2018: temperature: Archaeological
Nunalleq.Ledger.2018: uncertainty: Archaeological
Nunalleq.Ledger.2018: uncertainty: Archaeological
Nunalleq.Ledger.2018: uncertainty: Archaeological
Nunalleq.Ledger.2018: uncertainty: Archaeological
Nunalleq.Ledger.2018: temperature: Archaeological
Nunalleq.Ledger.2018: temperature: Archaeological
Nunalleq.Ledger.2018: precipitation: Archaeological
Nunalleq.Ledger.2018: uncertaintyLow: Archaeological
Nunalleq.Ledger.2018: temperature: Archaeological
Nunalleq.Ledger.2018: temperature: Archaeological
Nunalleq.Ledger.2018: temperature: Archaeological
Nunalleq.Ledger.2018: precipitation: Archaeological
Nunalleq.Ledger.2018: temperature: Archaeological

Methods

clear()

Clears the graph

convert_lipd_dir_to_rdf(lipd_dir, rdf_file)

Convert a directory containing LiPD files into a single RDF file (to be used for uploading to Knowledge Bases like GraphDB)

copy()

Makes a copy of the object

create_lipd(dsname, lipdfile)

Create LiPD file for a dataset

filter_by_archive_type(archiveType)

Filters datasets to return a new LiPD object that only keeps datasets that have the specified archive type

filter_by_geo_bbox(lonMin, latMin, lonMax, ...)

Filters datasets to return a new LiPD object that only keeps datasets that fall within the bounding box

filter_by_time(timeBound[, timeBoundType, ...])

Filter the records according to a specified time interval and the length of the record within that interval.

get(dsnames)

Gets dataset(s) from the graph and returns the popped LiPD object

get_all_archiveTypes()

Returns a list of all the unique archiveTypes present in the LiPD object

get_all_dataset_ids()

Get all Dataset ids

get_all_dataset_names()

Get all Dataset Names

get_all_graph_ids()

Get all Graph ids

get_all_locations([dsname])

Return geographical coordinates for all the datasets.

get_all_variable_names()

Get a list of all possible distinct variableNames.

get_all_variables()

Returns a list of all variables in the graph

get_bibtex([remote, save, path, verbose])

Get BibTeX for loaded datasets

get_dataset_properties()

Get a list of unique properties attached to a dataset.

get_datasets()

Return datasets as instances of the Dataset class

get_ensemble_tables([dsname, ...])

Gets ensemble tables from the LiPD graph

get_lipd(dsname)

Get LiPD json for a dataset

get_model_properties()

Get all the properties associated with a model

get_timeseries(dsnames[, to_dataframe, ...])

Get Legacy LiPD like Time Series Object (tso)

get_timeseries_essentials([dsnames, mode])

Returns specific properties for timeseries: 'dataSetName', 'archiveType', 'geo_meanLat', 'geo_meanLon',

get_variable_properties()

Get a list of variable properties that can be used for querying

load(lipdfiles[, parallel, standardize, ...])

Load LiPD files.

load_datasets(datasets)

Loads instances of Dataset class into the LiPD graph

load_from_dir(dir_path[, parallel, cutoff, ...])

Load LiPD files from a directory

load_remote_datasets(dsnames[, ...])

Loads remote datasets into cache if a remote endpoint is set

merge(rdf)

Merges the current LiPD object with another LiPD object

pop(dsnames)

Pops dataset(s) from the graph and returns the popped LiPD object

query(query[, remote, result])

Once data is loaded into the graph (or remote endpoint set), one can make SparQL queries to the graph

remove(dsnames)

Removes dataset(s) from the graph

serialize()

Returns RDF quad serialization of the current combined Graph .

set_endpoint(endpoint)

Sets a SparQL endpoint for a remote Knowledge Base (example: GraphDB)

to_lipd_series([parallel])

Converts the LiPD object to a LiPDSeries object

update_remote_datasets(dsnames)

Updates local LiPD Graph for datasets to remote endpoint

convert_lipd_dir_to_rdf(lipd_dir, rdf_file, parallel=False, standardize=True, add_labels=False)[source]

Convert a directory containing LiPD files into a single RDF file (to be used for uploading to Knowledge Bases like GraphDB)

Parameters:
  • lipd_dir (str) – Path to the directory containing lipd files

  • rdf_file (str) – Path to the output rdf file

create_lipd(dsname, lipdfile)[source]

Create LiPD file for a dataset

Parameters:
  • dsname (str) – dataset id

  • lipdfile (str) – path to LiPD file

Returns:

lipdjson – LiPD json

Return type:

dict

Examples

from pylipd.lipd import LiPD

# Load a local file
lipd = LiPD()
lipd.load([
    "../examples/data/Ocn-MadangLagoonPapuaNewGuinea.Kuhnert.2001.lpd",
])
dsname = lipd.get_all_dataset_names()[0]
lipd.create_lipd(dsname, "test.lpd")
Loading 1 LiPD files
Loaded..
{'dataContributor': {'name': 'Wu KLD'},
 'originalDataURL': 'https://www.ncdc.noaa.gov/paleo/study/1866',
 'changelog': {'curator': 'nicholas',
  'timestamp': datetime.date(2022, 8, 23),
  'notes': 'Starting the changelog',
  'version': '1.0.0'},
 'studyName': 'Madang, Papua New Guinea oxygen isotope record 1880-1993',
 'paleoData': [{'measurementTable': [{'tableName': 'Kuhnert',
     'googleWorkSheetKey': 'ov9tjw6',
     'filename': 'Ocn-MadangLagoonPapuaNewGuinea.Kuhnert.2001.paleo1measurement1.csv',
     'columns': [{'TSid': 'Ocean2kHR_140',
       'proxyObservationType': 'd18O',
       'wDSPaleoUrl': 'https://www1.ncdc.noaa.gov/pub/data/paleo/pages2k/pages2k-temperature-v2-2017/data-version-2.0.0/Ocn-MadangLagoonPapuaNewGuinea.Kuhnert.2001.txt',
       'measurementTableName': 'measurementTable1',
       'hasMeanValue': -4.9453,
       'hasMedianValue': -4.942,
       'resolution': {'hasMinValue': 0.25,
        'hasMeanValue': 0.25,
        'hasMaxValue': 0.25,
        'hasMedianValue': 0.25,
        'units': 'yr AD'},
       'hasMaxValue': -4.344,
       'useInGlobalTemperatureAnalysis': True,
       'notes': '; climateInterpretation_seasonality changed - was originally seasonal',
       'variableName': 'd18O',
       'interpretation': [{'variableDetail': 'sea@surface',
         'scope': 'climate',
         'direction': 'negative',
         'seasonality': 'subannual',
         'variable': 'temperature'}],
       'measurementTableMD5': '793853407e414221c486d2e63b32dd87',
       'inCompilationBeta': {'compilationName': 'Pages2kTemperature',
        'compilationVersion': '2_1_1'},
       'variableType': 'measured',
       'qCCertification': 'KLD, NJA',
       'ocean2kID': 'PacificMadangTudhope2001',
       'sensorGenus': 'Porites',
       'number': 1,
       'pages2kID': 'Ocn_097',
       'hasArchiveType': {'label': 'Coral'},
       'hasMinValue': -5.515,
       'paleoDataTableName': 'measTable',
       'iso2kUI': 'CO01TUNG01A',
       'units': 'permil',
       'proxy': 'd18O'},
      {'inferredVariableType': 'Year',
       'hasMaxValue': 1993.042,
       'hasArchiveType': {'label': 'Coral'},
       'TSid': 'PYTDAS7AM1Y',
       'wDSPaleoUrl': 'https://www1.ncdc.noaa.gov/pub/data/paleo/pages2k/pages2k-temperature-v2-2017/data-version-2.0.0/Ocn-MadangLagoonPapuaNewGuinea.Kuhnert.2001.txt',
       'variableType': 'inferred',
       'measurementTableName': 'measurementTable1',
       'number': 2,
       'description': 'Year AD',
       'variableName': 'year',
       'hasMinValue': 1880.792,
       'hasMedianValue': 1936.917,
       'resolution': {'hasMedianValue': 0.25,
        'hasMinValue': 0.25,
        'hasMeanValue': 0.25,
        'hasMaxValue': 0.25,
        'units': 'yr AD'},
       'dataType': 'float',
       'measurementTableMD5': '793853407e414221c486d2e63b32dd87',
       'hasMeanValue': 1936.917,
       'paleoDataTableName': 'measTable',
       'units': 'yr AD'}],
     'missingValue': 'NaN'}]}],
 'googleMetadataWorksheet': 'oruuxfm',
 'googleSpreadSheetKey': '1wf30P-s54OTBdLw4dyeaIN53VDoN0u_hOqIwvAeLxtc',
 'dataSetName': 'Ocn-MadangLagoonPapuaNewGuinea.Kuhnert.2001',
 'inCompilation1_': 'Ocean2k_v1.0.0',
 'minYear': 1880.792,
 'datasetId': 'm8yv2VgG97zJmSg3XhqQ',
 'inCompilation3_': 'PAGES2k_v2.1.0',
 'geo': {'geometry': {'coordinates': [145.8167, -5.2167, -2.2],
   'type': 'Point'},
  'properties': {'siteName': 'Madang Lagoon, Papua New Guinea',
   'ocean': 'Pacific',
   'type': 'http://linked.earth/ontology#Location',
   'pages2kRegion': 'Ocean'}},
 'inCompilation2_': 'PAGES2k_v2.0.0',
 'googleDataURL': 'https://docs.google.com/spreadsheets/d/1wf30P-s54OTBdLw4dyeaIN53VDoN0u_hOqIwvAeLxtc',
 'pub': [{'author': [{'name': 'A. W. Tudhope'}],
   'journal': 'Science',
   'title': 'Variability in the El Nino-Southern Oscillation Through a Glacial-Interglacial Cycle',
   'pages': '1511-1517',
   'publisher': 'American Association for the Advancement of Science (AAAS)',
   'dataUrl': ['doi.org'],
   'issue': 5508.0,
   'year': 2001,
   'volume': '291',
   'citeKey': 'tudhope2001variabilityintheelninosou',
   'doi': '10.1126/science.1057969'},
  {'author': [{'name': 'H. Kuhnert'}],
   'citeKey': 'kuhnert2001httpswwwncdcnoaagovpaleostudy1866DataCitation',
   'url': ['https://www.ncdc.noaa.gov/paleo/study/1866'],
   'urldate': 2001.0,
   'title': 'World Data Center for Paleoclimatology',
   'institution': 'World Data Center for Paleoclimatology'},
  {'author': [{'name': 'Henry C. Wu'},
    {'name': 'Jens Zinke'},
    {'name': 'K. Halimeda Kilbourne'},
    {'name': 'Cyril Giry'},
    {'name': 'Nerilie J. Abram'},
    {'name': 'Casey P. Saenger'},
    {'name': 'Jessica E. Tierney'},
    {'name': 'Kevin J. Anchukaitis'},
    {'name': 'Michael N. Evans'}],
   'title': 'Tropical sea surface temperatures for the past four centuries reconstructed from coral archives',
   'pages': '226-252',
   'dataUrl': ['doi.org'],
   'year': 2015,
   'volume': '30',
   'issue': 3.0,
   'citeKey': 'tierney2015tropicalseasurfacetempera',
   'publisher': 'Wiley-Blackwell',
   'doi': '10.1002/2014PA002717',
   'journal': 'Paleoceanography'}],
 'maxYear': 1993.042,
 'hasUrl': 'https://data.mint.isi.edu/files/lipd/Ocn-MadangLagoonPapuaNewGuinea.Kuhnert.2001.lpd',
 'lipdVersion': 1.3,
 'createdBy': 'matlab',
 'archiveType': 'Coral'}
filter_by_archive_type(archiveType)[source]

Filters datasets to return a new LiPD object that only keeps datasets that have the specified archive type

Parameters:

archiveType (str) – The archive type to filter by

Returns:

A new LiPD object that only contains datasets that have the specified archive type (regex)

Return type:

pylipd.lipd.LiPD

Examples

pyLipd ships with existing datasets that can be loaded directly through the package. Let’s load the Pages2k sample datasets using this method.

from pylipd.utils.dataset import load_dir

lipd = load_dir('Pages2k')
Lfiltered = lipd.filter_by_archive_type('marine')
Lfiltered.get_all_dataset_names()
Loading 16 LiPD files
Loaded..
['Ocn-AlboranSea436B.Nieto-Moreno.2013',
 'Ocn-FeniDrift.Richter.2009',
 'Eur-CoastofPortugal.Abrantes.2011']
filter_by_geo_bbox(lonMin, latMin, lonMax, latMax)[source]

Filters datasets to return a new LiPD object that only keeps datasets that fall within the bounding box

Parameters:
  • lonMin (float) – Minimum longitude

  • latMin (float) – Minimum latitude

  • lonMax (float) – Maximum longitude

  • latMax (float) – Maximum latitude

Returns:

A new LiPD object that only contains datasets that fall within the bounding box

Return type:

pylipd.lipd.LiPD

Examples

pyLipd ships with existing datasets that can be loaded directly through the package. Let’s load the Pages2k sample datasets using this method.

from pylipd.utils.dataset import load_dir

lipd = load_dir()
Lfiltered = lipd.filter_by_geo_bbox(0,25,50,50)
Lfiltered.get_all_dataset_names()
Loading 16 LiPD files
Loaded..
['Ocn-RedSea.Felis.2000',
 'Eur-SpannagelCave.Mangini.2005',
 'Eur-SpanishPyrenees.Dorado-Linan.2012',
 'Eur-LakeSilvaplana.Trachsel.2010',
 'Ocn-SinaiPeninsula_RedSea.Moustafa.2000']
filter_by_time(timeBound, timeBoundType='any', recordLength=None)[source]

Filter the records according to a specified time interval and the length of the record within that interval. Note that this function assumes that all records use the same time representation.

If you are unsure about the time representation, you may need to use .get_timeseries_essentials.

Parameters:
  • timeBound (list) – Minimum and Maximum age value to search for.

  • timeBoundType (str, optional) – The type of querying to perform. Possible values include: “any”, “entire”, and “entirely”. - any: Overlap any portions of matching datasets (default) - entirely: are entirely overlapped by matching datasets - entire: overlap entire matching datasets but dataset can be shorter than the bounds The default is ‘any’.

  • recordLength (float, optional) – The minimum length the record needs to have while matching the ageBound criteria. The default is None.

Raises:

ValueError – timeBoundType must take the values in [“any”, “entire”, and “entirely”]

Returns:

A new LiPD object that only contains datasets that have the specified time interval

Return type:

pylipd.lipd.LiPD

Examples

pyLipd ships with existing datasets that can be loaded directly through the package. Let’s load the Pages2k sample datasets using this method.

from pylipd.utils.dataset import load_dir

lipd = load_dir('Pages2k')
Lfiltered = lipd.filter_by_time(timeBound=[0,1800])
Lfiltered.get_all_dataset_names()
Loading 16 LiPD files
Loaded..
['Ocn-AlboranSea436B.Nieto-Moreno.2013',
 'Ant-WAIS-Divide.Severinghaus.2012',
 'Asi-SourthAndMiddleUrals.Demezhko.2007',
 'Ocn-RedSea.Felis.2000',
 'Eur-SpannagelCave.Mangini.2005',
 'Eur-SpanishPyrenees.Dorado-Linan.2012',
 'Eur-NorthernSpain.Martin-Chivelet.2011',
 'Eur-NorthernScandinavia.Esper.2012',
 'Ocn-FeniDrift.Richter.2009',
 'Eur-Stockholm.Leijonhufvud.2009',
 'Eur-CoastofPortugal.Abrantes.2011',
 'Eur-FinnishLakelands.Helama.2014',
 'Eur-LakeSilvaplana.Trachsel.2010']
get(dsnames)[source]

Gets dataset(s) from the graph and returns the popped LiPD object

Parameters:

dsnames (str or list of str) – dataset name(s) to get.

Returns:

LiPD object with the retrieved dataset(s)

Return type:

pylipd.lipd.LiPD

Examples

from pylipd.lipd import LiPD

# Load LiPD files from a local directory
lipd = LiPD()
lipd.load([
    "../examples/data/Ocn-MadangLagoonPapuaNewGuinea.Kuhnert.2001.lpd",
    "../examples/data/MD98_2181.Stott.2007.lpd"
])

all_datasets = lipd.get_all_dataset_names()
print("Loaded datasets: " + str(all_datasets))
ds = lipd.get(all_datasets[0])
print("Got dataset: " + str(ds.get_all_dataset_names()))
Loading 2 LiPD files
Loaded..
Loaded datasets: ['Ocn-MadangLagoonPapuaNewGuinea.Kuhnert.2001', 'MD98_2181.Stott.2007']
Got dataset: ['Ocn-MadangLagoonPapuaNewGuinea.Kuhnert.2001']
get_all_archiveTypes()[source]

Returns a list of all the unique archiveTypes present in the LiPD object

Returns:

A list of archiveTypes

Return type:

list

Examples

from pylipd.lipd import LiPD

# Load Local files
lipd = LiPD()
lipd.load([
    "../examples/data/Ocn-MadangLagoonPapuaNewGuinea.Kuhnert.2001.lpd",
    "../examples/data/MD98_2181.Stott.2007.lpd"
])
print(lipd.get_all_archiveTypes())
Loading 2 LiPD files
Loaded..
['Coral', 'Marine sediment']
get_all_dataset_ids()[source]

Get all Dataset ids

Returns:

  • dsids (list)

  • A list of datasetnames

Examples

from pylipd.lipd import LiPD

# Load local files
lipd = LiPD()
lipd.load([
    "../examples/data/Ocn-MadangLagoonPapuaNewGuinea.Kuhnert.2001.lpd",
    "../examples/data/MD98_2181.Stott.2007.lpd"
])
print(lipd.get_all_dataset_ids())
Loading 2 LiPD files
Loaded..
['m8yv2VgG97zJmSg3XhqQ', 't0E8pOLYdyzmUspGZwbe']
get_all_dataset_names()[source]

Get all Dataset Names

Returns:

  • dsnames (list)

  • A list of datasetnames

Examples

from pylipd.lipd import LiPD

# Load local files
lipd = LiPD()
lipd.load([
    "../examples/data/Ocn-MadangLagoonPapuaNewGuinea.Kuhnert.2001.lpd",
    "../examples/data/MD98_2181.Stott.2007.lpd"
])
print(lipd.get_all_dataset_names())
Loading 2 LiPD files
Loaded..
['Ocn-MadangLagoonPapuaNewGuinea.Kuhnert.2001', 'MD98_2181.Stott.2007']
get_all_locations(dsname=None)[source]

Return geographical coordinates for all the datasets.

Parameters:

dsname (str, optional) – The name of the dataset for which to return the timeseries information. The default is None.

Returns:

df – A pandas dataframe returning the latitude, longitude and elevation for each dataset

Return type:

pandas.DataFrame

Examples

from pylipd.utils.dataset import load_dir
lipd = load_dir('Pages2k')
df = lipd.get_all_locations()
print(df)
Loading 16 LiPD files
Loaded..
                                    dataSetName  geo_meanLat  geo_meanLon  \
0             Eur-CoastofPortugal.Abrantes.2011      41.1000      -8.9000   
1            Eur-NorthernScandinavia.Esper.2012      68.0000      25.0000   
2        Asi-SourthAndMiddleUrals.Demezhko.2007      55.0000      59.5000   
3              Arc-Kongressvatnet.D'Andrea.2012      78.0217      13.9311   
4                         Ocn-RedSea.Felis.2000      27.8500      34.3200   
5             Ant-WAIS-Divide.Severinghaus.2012     -79.4630    -112.1250   
6                    Ocn-FeniDrift.Richter.2009      55.5000     -13.9000   
7          Ocn-AlboranSea436B.Nieto-Moreno.2013      36.2053      -4.3133   
8        Eur-NorthernSpain.Martin-Chivelet.2011      42.9000      -3.5000   
9   Ocn-PedradeLume-CapeVerdeIslands.Moses.2006      16.7600     -22.8883   
10               Eur-SpannagelCave.Mangini.2005      47.1000      11.6000   
11        Eur-SpanishPyrenees.Dorado-Linan.2012      42.5000       1.0000   
12              Eur-Stockholm.Leijonhufvud.2009      59.3200      18.0600   
13             Eur-FinnishLakelands.Helama.2014      62.0000      28.3250   
14      Ocn-SinaiPeninsula,RedSea.Moustafa.2000      27.8483      34.3100   
15             Eur-LakeSilvaplana.Trachsel.2010      46.5000       9.8000   

    geo_meanElev  
0          -80.0  
1          300.0  
2         1900.0  
3           94.0  
4           -6.0  
5         1766.0  
6        -2543.0  
7        -1108.0  
8         1250.0  
9           -5.0  
10        2347.0  
11        1200.0  
12          10.0  
13         130.0  
14          -3.0  
15        1791.0  
get_all_variable_names()[source]

Get a list of all possible distinct variableNames. Useful for filtering and qeurying.

Returns:

A list of unique variableName

Return type:

list

Examples

from pylipd.utils.dataset import load_dir
lipd = load_dir('Pages2k')
varName = lipd.get_all_variable_names()
print(varName)
Loading 16 LiPD files
Loaded..
['year', 'temperature', 'MXD', 'Uk37', 'd18O', 'uncertainty_temperature', 'Mg_Ca', 'notes', 'depth_bottom', 'depth_top', 'trsgi']
get_all_variables()[source]

Returns a list of all variables in the graph

Returns:

A dataframe of all variables in the graph with columns uri, varid, varname

Return type:

pandas.DataFrame

Examples

from pylipd.lipd import LiPD

lipd = LiPD()
lipd.load([
    "../examples/data/ODP846.Lawrence.2006.lpd"
])

df = lipd.get_all_variables()
print(df)
Loading 1 LiPD files
Loaded..
                                                  uri         TSID  \
0   http://linked.earth/lipd/chron0model0summary0....  PYTDIEKUM44   
1   http://linked.earth/lipd/chron0model0summary0....  PYT7DLYN7X4   
2   http://linked.earth/lipd/chron0model0ensemble0...  PYTUHE3XLGQ   
3   http://linked.earth/lipd/paleo0measurement0.PY...  PYTXJB98403   
4   http://linked.earth/lipd/chron0measurement0.PY...  PYTTD7XCQGS   
5   http://linked.earth/lipd/paleo0measurement0.PY...  PYTKRFVW61B   
6   http://linked.earth/lipd/chron0measurement0.PY...  PYT9CFQ4GK0   
7   http://linked.earth/lipd/chron0model0ensemble0...  PYTGOFY4KZD   
8   http://linked.earth/lipd/paleo0measurement1.PY...  PYTS96EE0CB   
9   http://linked.earth/lipd/chron0model0summary0....  PYTPWX0LH3I   
10  http://linked.earth/lipd/paleo0model0ensemble0...  PYTCHXB40SL   
11  http://linked.earth/lipd/paleo0measurement0.PY...  PYT10H23U2E   
12  http://linked.earth/lipd/chron0model0summary0....  PYTI487BQDZ   
13  http://linked.earth/lipd/paleo0measurement0.PY...  PYT95DVDUU3   
14  http://linked.earth/lipd/paleo0measurement0.PY...  PYTGO6NV72Y   
15  http://linked.earth/lipd/paleo0measurement0.PY...  PYT2ZB6MLZ9   
16  http://linked.earth/lipd/paleo0measurement1.PY...  PYTYDOYFVYD   
17  http://linked.earth/lipd/chron0measurement0.PY...  PYTLEHYPAYV   
18  http://linked.earth/lipd/paleo0measurement0.PY...  PYT8BDSRW3H   
19  http://linked.earth/lipd/paleo0measurement1.PY...  PYT68HYMYHH   
20  http://linked.earth/lipd/paleo0measurement0.PY...  PYTJ3PSH0LT   
21  http://linked.earth/lipd/paleo0measurement1.PY...  PYTE5EC1JBW   
22  http://linked.earth/lipd/paleo0model0ensemble0...  PYTDW6AIJPW   
23  http://linked.earth/lipd/paleo0measurement0.PY...  PYTM9N6HCQM   
24  http://linked.earth/lipd/paleo0measurement1.PY...  PYTTUPVG4K3   
25  http://linked.earth/lipd/paleo0measurement1.PY...  PYT19MC8WE2   
26  http://linked.earth/lipd/paleo0measurement1.PY...  PYTJZ4GLRYP   
27  http://linked.earth/lipd/chron0model0summary0....  PYT4Y96QMUU   
28  http://linked.earth/lipd/paleo0measurement1.PY...  PYT3ZMI0BXW   
29  http://linked.earth/lipd/paleo0measurement1.PY...  PYTPQ0FJO1S   

             variableName  
0                 upper95  
1                  median  
2                     age  
3                     age  
4                     age  
5                   depth  
6                   depth  
7                   depth  
8                   depth  
9                   depth  
10                  depth  
11              c37 total  
12                lower95  
13             temp prahl  
14            temp muller  
15               interval  
16      u. peregrina d18o  
17                   d18o  
18                section  
19               depth cr  
20              site/hole  
21                  event  
22                    sst  
23              ukprime37  
24      u. peregrina d13c  
25  c. wuellerstorfi d13c  
26           sample label  
27                   d180  
28  c. wuellerstorfi d18o  
29             depth comp  
get_bibtex(remote=True, save=True, path='mybiblio.bib', verbose=False)[source]

Get BibTeX for loaded datasets

Parameters:
  • remote (bool) – (Optional) If set to True, will return the bibliography by checking against the DOI

  • save (bool) – (Optional) Whether to save the bibliography to a file

  • path (str) – (Optional) Path where to save the file

  • verbose (bool) – (Optional) Whether to print out on the console. Note that this option will turn on automatically if saving to a file fails.

Returns:

  • bibs (list) – List of BiBTex entry

  • df (pandas.DataFrame) – Bibliography information in a Pandas DataFrame

Examples

from pylipd.lipd import LiPD

# Fetch LiPD data from remote RDF Graph
lipd = LiPD()
lipd.load([
    "../examples/data/Ocn-MadangLagoonPapuaNewGuinea.Kuhnert.2001.lpd",
    "../examples/data/MD98_2181.Stott.2007.lpd"
])
print(lipd.get_bibtex(save=False))
Loading 2 LiPD files
Loaded..
Cannot find a matching record for the provided DOI (None), creating the entry manually
([' @article{Tierney_2015, title={Tropical sea surface temperatures for the past four centuries reconstructed from coral archives}, volume={30}, ISSN={1944-9186}, url={http://dx.doi.org/10.1002/2014PA002717}, DOI={10.1002/2014pa002717}, number={3}, journal={Paleoceanography}, publisher={American Geophysical Union (AGU)}, author={Tierney, Jessica E. and Abram, Nerilie J. and Anchukaitis, Kevin J. and Evans, Michael N. and Giry, Cyril and Kilbourne, K. Halimeda and Saenger, Casey P. and Wu, Henry C. and Zinke, Jens}, year={2015}, month=mar, pages={226–252} }\n', ' @article{Tudhope_2001, title={Variability in the El Niño-Southern Oscillation Through a Glacial-Interglacial Cycle}, volume={291}, ISSN={1095-9203}, url={http://dx.doi.org/10.1126/science.1057969}, DOI={10.1126/science.1057969}, number={5508}, journal={Science}, publisher={American Association for the Advancement of Science (AAAS)}, author={Tudhope, Alexander W. and Chilcott, Colin P. and McCulloch, Malcolm T. and Cook, Edward R. and Chappell, John and Ellam, Robert M. and Lea, David W. and Lough, Janice M. and Shimmield, Graham B.}, year={2001}, month=feb, pages={1511–1517} }\n', '@misc{kuhnert2001httpswwwncdcnoaagovpaleostudy1866DataCitation,\n    author = "H. Kuhnert",\n    title = "World Data Center for Paleoclimatology",\n    institution = "World Data Center for Paleoclimatology",\n    url = "https://www.ncdc.noaa.gov/paleo/study/1866"\n}\n', ' @article{Stott_2007, title={Comment on “Anomalous radiocarbon ages for foraminifera shells” by W. Broecker et al.: A correction to the western tropical Pacific MD9821‐81 record}, volume={22}, ISSN={1944-9186}, url={http://dx.doi.org/10.1029/2006PA001379}, DOI={10.1029/2006pa001379}, number={1}, journal={Paleoceanography}, publisher={American Geophysical Union (AGU)}, author={Stott, Lowell D.}, year={2007}, month=feb }\n', ' @article{Stott_2007, title={Southern Hemisphere and Deep-Sea Warming Led Deglacial Atmospheric CO\n            2\n            Rise and Tropical Warming}, volume={318}, ISSN={1095-9203}, url={http://dx.doi.org/10.1126/science.1143791}, DOI={10.1126/science.1143791}, number={5849}, journal={Science}, publisher={American Association for the Advancement of Science (AAAS)}, author={Stott, Lowell and Timmermann, Axel and Thunell, Robert}, year={2007}, month=oct, pages={435–438} }\n'],                                         dsname  \
0  Ocn-MadangLagoonPapuaNewGuinea.Kuhnert.2001   
1  Ocn-MadangLagoonPapuaNewGuinea.Kuhnert.2001   
2  Ocn-MadangLagoonPapuaNewGuinea.Kuhnert.2001   
3                         MD98_2181.Stott.2007   
4                         MD98_2181.Stott.2007   

                                               title  \
0  Tropical sea surface temperatures for the past...   
1  Variability in the El Nino-Southern Oscillatio...   
2             World Data Center for Paleoclimatology   
3                                               None   
4  Southern Hemisphere and deep-sea warming led d...   

                                             authors                      doi  \
0  Cyril Giry and Nerilie J. Abram and Casey P. S...     10.1002/2014PA002717   
1                                      A. W. Tudhope  10.1126/science.1057969   
2                                         H. Kuhnert                     None   
3                                                        10.1029/2006PA001379   
4          L. Stott and A. Timmermann and R. Thunell  10.1126/science.1143791   

  pubyear    year           journal volume   issue      pages  \
0    None  2015.0  Paleoceanography     30     3.0    226-252   
1    None  2001.0           Science    291  5508.0  1511-1517   
2    None     NaN              None   None     NaN       None   
3    None     NaN              None   None     NaN       None   
4    None  2007.0           Science    318  5849.0  435   438   

              type                                          publisher report  \
0  journal-article                                    Wiley-Blackwell   None   
1  journal-article  American Association for the Advancement of Sc...   None   
2     dataCitation                                               None   None   
3             None                                               None   None   
4             None                                               None   None   

                                             citeKey edition  \
0               tierney2015tropicalseasurfacetempera    None   
1               tudhope2001variabilityintheelninosou    None   
2  kuhnert2001httpswwwncdcnoaagovpaleostudy1866Da...    None   
3                                               None    None   
4                                           WMGAVB7S    None   

                              institution   url  \
0                                    None  None   
1                                    None  None   
2  World Data Center for Paleoclimatology  None   
3                                    None  None   
4                                    None  None   

                                         url2  
0                                        None  
1                                        None  
2  https://www.ncdc.noaa.gov/paleo/study/1866  
3                                        None  
4                                        None  )
get_dataset_properties()[source]

Get a list of unique properties attached to a dataset.

Note: Some properties will return another object (e.g., ‘publishedIn’ will give you a Publication object with its own properties) Note: Not all datasets will have the same available properties (i.e., not filled in by a user)

Returns:

clean_list – A list of avialable properties that can queried

Return type:

list

Examples

from pylipd.utils.dataset import load_dir
lipd = load_dir(name='Pages2k')
dataset_properties = lipd.get_dataset_properties()
print(dataset_properties)
Loading 16 LiPD files
Loaded..
['hasName', 'hasUrl', 'hasSpreadsheetLink', 'lipdVersion', 'googleMetadataWorksheet', 'hasLocation', 'maxYear', 'hasPublication', 'hasDatasetId', 'googleDataURL', 'minYear', 'type', 'hasOriginalDataUrl', 'hasArchiveType', 'createdBy', 'hasChangeLog', 'hasPaleoData', 'inCompilation2_', 'inCompilation3_', 'inCompilation1_', 'hasContributor', 'studyName', 'hasInvestigator', 'hasNotes', 'hasFunding']
get_datasets() list[Dataset][source]

Return datasets as instances of the Dataset class

Returns:

A list of Dataset objects

Return type:

list of pylipd.classes.Dataset

Examples

pyLipd ships with existing datasets that can be loaded directly through the package. Let’s load the Pages2k sample datasets using this method.

from pylipd.utils.dataset import load_dir

lipd = load_dir('Pages2k')
lipd.get_datasets()
Loading 16 LiPD files
Loaded..
[<pylipd.classes.dataset.Dataset at 0x7fd9c59f90c0>,
 <pylipd.classes.dataset.Dataset at 0x7fd9cbff37c0>,
 <pylipd.classes.dataset.Dataset at 0x7fd9d0c8b130>,
 <pylipd.classes.dataset.Dataset at 0x7fd9d0c8a290>,
 <pylipd.classes.dataset.Dataset at 0x7fd9d0c88520>,
 <pylipd.classes.dataset.Dataset at 0x7fd9d09b64d0>,
 <pylipd.classes.dataset.Dataset at 0x7fd9d0c8b040>,
 <pylipd.classes.dataset.Dataset at 0x7fd9d1088610>,
 <pylipd.classes.dataset.Dataset at 0x7fd9cbff11b0>,
 <pylipd.classes.dataset.Dataset at 0x7fd9cbff3f70>,
 <pylipd.classes.dataset.Dataset at 0x7fd9d0af0160>,
 <pylipd.classes.dataset.Dataset at 0x7fd9cbff16f0>,
 <pylipd.classes.dataset.Dataset at 0x7fd9d0c8bf70>,
 <pylipd.classes.dataset.Dataset at 0x7fd9d0f84d30>,
 <pylipd.classes.dataset.Dataset at 0x7fd9d0c8bee0>,
 <pylipd.classes.dataset.Dataset at 0x7fd9d14f6ef0>]
get_ensemble_tables(dsname=None, ensembleVarName=None, ensembleDepthVarName='depth')[source]

Gets ensemble tables from the LiPD graph

Parameters:
  • dsname (str) – The name of the dataset if you wish to analyse one at a time (Set to “.*” to match all datasets with a common root)

  • ensembleVarName (None or str) – ensemble variable name. Default is None, which searches for names that contain “year” or “age” (Set to “.*” to match all ensemble variable names)

  • ensembleDepthVarName (str) – ensemble depth variable name. Default is ‘depth’ (Set to “.*” to match all ensemble depth variable names)

Returns:

ensemble_tables – A dataframe containing the ensemble tables

Return type:

dataframe

Examples

from pylipd.lipd import LiPD

lipd = LiPD()
lipd.load([
    "../examples/data/ODP846.Lawrence.2006.lpd"
])
all_datasets = lipd.get_all_dataset_names()
print("Loaded datasets: " + str(all_datasets))

ens_df = lipd.get_ensemble_tables(
    ensembleVarName="age",
    ensembleDepthVarName="depth"
)
print(ens_df)
Loading 1 LiPD files
Loaded..
Loaded datasets: ['ODP846.Lawrence.2006']
            datasetName                                   ensembleTable  \
0  ODP846.Lawrence.2006  http://linked.earth/lipd/chron0model0ensemble0   

  ensembleVariableName                             ensembleVariableValues  \
0                  age  [[4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0,...   

  ensembleVariableUnits ensembleDepthName  \
0                kyr BP             depth   

                                 ensembleDepthValues ensembleDepthUnits notes  \
0  [0.12, 0.23, 0.33, 0.43, 0.53, 0.63, 0.73, 0.8...                  m  None   

  methodobj methods  
0      None    None  
get_lipd(dsname)[source]

Get LiPD json for a dataset

Parameters:

dsname (str) – dataset id

Returns:

lipdjson – LiPD json

Return type:

dict

Examples

from pylipd.lipd import LiPD

# Load a local LiPD file
lipd = LiPD()
lipd.load([
    "../examples/data/Ocn-MadangLagoonPapuaNewGuinea.Kuhnert.2001.lpd",
])
lipd_json = lipd.get_lipd(lipd.get_all_dataset_names()[0])
print(lipd_json)
Loading 1 LiPD files
Loaded..
{'dataContributor': {'name': 'Wu KLD'}, 'originalDataURL': 'https://www.ncdc.noaa.gov/paleo/study/1866', 'changelog': {'curator': 'nicholas', 'timestamp': datetime.date(2022, 8, 23), 'notes': 'Starting the changelog', 'version': '1.0.0'}, 'pub': [{'issue': 3.0, 'author': [{'name': 'Nerilie J. Abram'}, {'name': 'Jessica E. Tierney'}, {'name': 'Kevin J. Anchukaitis'}, {'name': 'Michael N. Evans'}, {'name': 'K. Halimeda Kilbourne'}, {'name': 'Henry C. Wu'}, {'name': 'Jens Zinke'}, {'name': 'Casey P. Saenger'}, {'name': 'Cyril Giry'}], 'citeKey': 'tierney2015tropicalseasurfacetempera', 'journal': 'Paleoceanography', 'title': 'Tropical sea surface temperatures for the past four centuries reconstructed from coral archives', 'publisher': 'Wiley-Blackwell', 'doi': '10.1002/2014PA002717', 'year': 2015, 'pages': '226-252', 'volume': '30', 'dataUrl': ['doi.org']}, {'institution': 'World Data Center for Paleoclimatology', 'title': 'World Data Center for Paleoclimatology', 'citeKey': 'kuhnert2001httpswwwncdcnoaagovpaleostudy1866DataCitation', 'url': ['https://www.ncdc.noaa.gov/paleo/study/1866'], 'author': [{'name': 'H. Kuhnert'}], 'urldate': 2001.0}, {'year': 2001, 'volume': '291', 'doi': '10.1126/science.1057969', 'citeKey': 'tudhope2001variabilityintheelninosou', 'author': [{'name': 'A. W. Tudhope'}], 'dataUrl': ['doi.org'], 'journal': 'Science', 'title': 'Variability in the El Nino-Southern Oscillation Through a Glacial-Interglacial Cycle', 'publisher': 'American Association for the Advancement of Science (AAAS)', 'issue': 5508.0, 'pages': '1511-1517'}], 'studyName': 'Madang, Papua New Guinea oxygen isotope record 1880-1993', 'paleoData': [{'measurementTable': [{'tableName': 'Kuhnert', 'googleWorkSheetKey': 'ov9tjw6', 'filename': 'Ocn-MadangLagoonPapuaNewGuinea.Kuhnert.2001.paleo1measurement1.csv', 'columns': [{'inferredVariableType': 'Year', 'hasMaxValue': 1993.042, 'hasArchiveType': {'label': 'Coral'}, 'TSid': 'PYTDAS7AM1Y', 'wDSPaleoUrl': 'https://www1.ncdc.noaa.gov/pub/data/paleo/pages2k/pages2k-temperature-v2-2017/data-version-2.0.0/Ocn-MadangLagoonPapuaNewGuinea.Kuhnert.2001.txt', 'variableType': 'inferred', 'measurementTableName': 'measurementTable1', 'number': 2, 'description': 'Year AD', 'variableName': 'year', 'hasMinValue': 1880.792, 'hasMedianValue': 1936.917, 'resolution': {'hasMedianValue': 0.25, 'hasMinValue': 0.25, 'hasMeanValue': 0.25, 'hasMaxValue': 0.25, 'units': 'yr AD'}, 'dataType': 'float', 'measurementTableMD5': '793853407e414221c486d2e63b32dd87', 'hasMeanValue': 1936.917, 'paleoDataTableName': 'measTable', 'units': 'yr AD', 'values': [1993.042, 1992.792, 1992.542, 1992.292, 1992.042, 1991.792, 1991.542, 1991.292, 1991.042, 1990.792, 1990.542, 1990.292, 1990.042, 1989.792, 1989.542, 1989.292, 1989.042, 1988.792, 1988.542, 1988.292, 1988.042, 1987.792, 1987.542, 1987.292, 1987.042, 1986.792, 1986.542, 1986.292, 1986.042, 1985.792, 1985.542, 1985.292, 1985.042, 1984.792, 1984.542, 1984.292, 1984.042, 1983.792, 1983.542, 1983.292, 1983.042, 1982.792, 1982.542, 1982.292, 1982.042, 1981.792, 1981.542, 1981.292, 1981.042, 1980.792, 1980.542, 1980.292, 1980.042, 1979.792, 1979.542, 1979.292, 1979.042, 1978.792, 1978.542, 1978.292, 1978.042, 1977.792, 1977.542, 1977.292, 1977.042, 1976.792, 1976.542, 1976.292, 1976.042, 1975.792, 1975.542, 1975.292, 1975.042, 1974.792, 1974.542, 1974.292, 1974.042, 1973.792, 1973.542, 1973.292, 1973.042, 1972.792, 1972.542, 1972.292, 1972.042, 1971.792, 1971.542, 1971.292, 1971.042, 1970.792, 1970.542, 1970.292, 1970.042, 1969.792, 1969.542, 1969.292, 1969.042, 1968.792, 1968.542, 1968.292, 1968.042, 1967.792, 1967.542, 1967.292, 1967.042, 1966.792, 1966.542, 1966.292, 1966.042, 1965.792, 1965.542, 1965.292, 1965.042, 1964.792, 1964.542, 1964.292, 1964.042, 1963.792, 1963.542, 1963.292, 1963.042, 1962.792, 1962.542, 1962.292, 1962.042, 1961.792, 1961.542, 1961.292, 1961.042, 1960.792, 1960.542, 1960.292, 1960.042, 1959.792, 1959.542, 1959.292, 1959.042, 1958.792, 1958.542, 1958.292, 1958.042, 1957.792, 1957.542, 1957.292, 1957.042, 1956.792, 1956.542, 1956.292, 1956.042, 1955.792, 1955.542, 1955.292, 1955.042, 1954.792, 1954.542, 1954.292, 1954.042, 1953.792, 1953.542, 1953.292, 1953.042, 1952.792, 1952.542, 1952.292, 1952.042, 1951.792, 1951.542, 1951.292, 1951.042, 1950.792, 1950.542, 1950.292, 1950.042, 1949.792, 1949.542, 1949.292, 1949.042, 1948.792, 1948.542, 1948.292, 1948.042, 1947.792, 1947.542, 1947.292, 1947.042, 1946.792, 1946.542, 1946.292, 1946.042, 1945.792, 1945.542, 1945.292, 1945.042, 1944.792, 1944.542, 1944.292, 1944.042, 1943.792, 1943.542, 1943.292, 1943.042, 1942.792, 1942.542, 1942.292, 1942.042, 1941.792, 1941.542, 1941.292, 1941.042, 1940.792, 1940.542, 1940.292, 1940.042, 1939.792, 1939.542, 1939.292, 1939.042, 1938.792, 1938.542, 1938.292, 1938.042, 1937.792, 1937.542, 1937.292, 1937.042, 1936.792, 1936.542, 1936.292, 1936.042, 1935.792, 1935.542, 1935.292, 1935.042, 1934.792, 1934.542, 1934.292, 1934.042, 1933.792, 1933.542, 1933.292, 1933.042, 1932.792, 1932.542, 1932.292, 1932.042, 1931.792, 1931.542, 1931.292, 1931.042, 1930.792, 1930.542, 1930.292, 1930.042, 1929.792, 1929.542, 1929.292, 1929.042, 1928.792, 1928.542, 1928.292, 1928.042, 1927.792, 1927.542, 1927.292, 1927.042, 1926.792, 1926.542, 1926.292, 1926.042, 1925.792, 1925.542, 1925.292, 1925.042, 1924.792, 1924.542, 1924.292, 1924.042, 1923.792, 1923.542, 1923.292, 1923.042, 1922.792, 1922.542, 1922.292, 1922.042, 1921.792, 1921.542, 1921.292, 1921.042, 1920.792, 1920.542, 1920.292, 1920.042, 1919.792, 1919.542, 1919.292, 1919.042, 1918.792, 1918.542, 1918.292, 1918.042, 1917.792, 1917.542, 1917.292, 1917.042, 1916.792, 1916.542, 1916.292, 1916.042, 1915.792, 1915.542, 1915.292, 1915.042, 1914.792, 1914.542, 1914.292, 1914.042, 1913.792, 1913.542, 1913.292, 1913.042, 1912.792, 1912.542, 1912.292, 1912.042, 1911.792, 1911.542, 1911.292, 1911.042, 1910.792, 1910.542, 1910.292, 1910.042, 1909.792, 1909.542, 1909.292, 1909.042, 1908.792, 1908.542, 1908.292, 1908.042, 1907.792, 1907.542, 1907.292, 1907.042, 1906.792, 1906.542, 1906.292, 1906.042, 1905.792, 1905.542, 1905.292, 1905.042, 1904.792, 1904.542, 1904.292, 1904.042, 1903.792, 1903.542, 1903.292, 1903.042, 1902.792, 1902.542, 1902.292, 1902.042, 1901.792, 1901.542, 1901.292, 1901.042, 1900.792, 1900.542, 1900.292, 1900.042, 1899.792, 1899.542, 1899.292, 1899.042, 1898.792, 1898.542, 1898.292, 1898.042, 1897.792, 1897.542, 1897.292, 1897.042, 1896.792, 1896.542, 1896.292, 1896.042, 1895.792, 1895.542, 1895.292, 1895.042, 1894.792, 1894.542, 1894.292, 1894.042, 1893.792, 1893.542, 1893.292, 1893.042, 1892.792, 1892.542, 1892.292, 1892.042, 1891.792, 1891.542, 1891.292, 1891.042, 1890.792, 1890.542, 1890.292, 1890.042, 1889.792, 1889.542, 1889.292, 1889.042, 1888.792, 1888.542, 1888.292, 1888.042, 1887.792, 1887.542, 1887.292, 1887.042, 1886.792, 1886.542, 1886.292, 1886.042, 1885.792, 1885.542, 1885.292, 1885.042, 1884.792, 1884.542, 1884.292, 1884.042, 1883.792, 1883.542, 1883.292, 1883.042, 1882.792, 1882.542, 1882.292, 1882.042, 1881.792, 1881.542, 1881.292, 1881.042, 1880.792]}, {'inCompilationBeta': {'compilationName': 'Pages2kTemperature', 'compilationVersion': '2_1_1'}, 'TSid': 'Ocean2kHR_140', 'proxyObservationType': 'd18O', 'wDSPaleoUrl': 'https://www1.ncdc.noaa.gov/pub/data/paleo/pages2k/pages2k-temperature-v2-2017/data-version-2.0.0/Ocn-MadangLagoonPapuaNewGuinea.Kuhnert.2001.txt', 'measurementTableName': 'measurementTable1', 'hasMeanValue': -4.9453, 'hasMedianValue': -4.942, 'resolution': {'hasMinValue': 0.25, 'hasMeanValue': 0.25, 'hasMaxValue': 0.25, 'hasMedianValue': 0.25, 'units': 'yr AD'}, 'hasMaxValue': -4.344, 'useInGlobalTemperatureAnalysis': True, 'notes': '; climateInterpretation_seasonality changed - was originally seasonal', 'variableName': 'd18O', 'interpretation': [{'variableDetail': 'sea@surface', 'scope': 'climate', 'direction': 'negative', 'seasonality': 'subannual', 'variable': 'temperature'}], 'measurementTableMD5': '793853407e414221c486d2e63b32dd87', 'variableType': 'measured', 'qCCertification': 'KLD, NJA', 'ocean2kID': 'PacificMadangTudhope2001', 'sensorGenus': 'Porites', 'number': 1, 'pages2kID': 'Ocn_097', 'hasArchiveType': {'label': 'Coral'}, 'hasMinValue': -5.515, 'paleoDataTableName': 'measTable', 'iso2kUI': 'CO01TUNG01A', 'units': 'permil', 'proxy': 'd18O', 'values': [-4.827, -4.786, -4.693, -4.852, -4.991, -4.904, -4.855, -4.862, -4.856, -4.947, -5.005, -5.298, -5.196, -5.298, -5.106, -5.375, -5.169, -5.083, -4.996, -5.027, -4.846, -4.646, -4.589, -4.972, -4.917, -4.795, -4.759, -5.301, -5.12, -5.086, -5.103, -5.244, -5.186, -5.059, -4.971, -5.356, -5.206, -4.885, -4.756, -4.959, -4.812, -4.667, -4.494, -5.117, -5.189, -5.133, -5.081, -5.165, -5.049, -4.883, -4.839, -5.103, -5.083, -4.96, -4.921, -5.204, -5.082, -5.133, -5.026, -5.334, -5.129, -4.889, -4.855, -5.214, -5.003, -4.842, -4.864, -5.038, -4.878, -5.027, -5.181, -5.515, -5.334, -5.06, -4.958, -5.268, -5.228, -5.136, -5.123, -5.304, -5.072, -4.748, -4.785, -5.234, -5.164, -5.053, -5.03, -5.188, -4.931, -4.99, -5.142, -5.216, -5.09, -4.865, -4.894, -5.041, -5.037, -5.064, -5.11, -5.291, -5.198, -5.242, -5.297, -5.492, -5.382, -5.087, -5.009, -5.282, -4.831, -4.524, -4.556, -5.071, -4.995, -4.958, -4.991, -5.08, -4.942, -4.908, -4.848, -4.993, -4.964, -5.031, -5.02, -5.245, -5.157, -5.041, -5.19, -5.39, -5.244, -5.072, -5.082, -5.362, -5.148, -4.889, -4.942, -4.895, -4.995, -4.924, -4.962, -5.0, -4.912, -4.774, -4.87, -5.104, -5.01, -4.996, -5.031, -5.112, -4.962, -5.003, -4.886, -5.095, -5.409, -4.992, -4.859, -5.151, -5.087, -5.031, -5.02, -5.355, -5.148, -5.13, -5.106, -5.228, -5.05, -4.868, -4.854, -4.937, -4.903, -4.902, -4.821, -4.963, -4.792, -4.886, -4.891, -5.146, -4.912, -4.856, -4.771, -4.964, -4.866, -4.909, -5.07, -5.459, -5.246, -4.871, -4.847, -5.086, -4.91, -4.912, -4.991, -5.203, -5.149, -4.957, -4.979, -5.232, -5.087, -5.072, -5.013, -5.329, -5.239, -5.016, -5.016, -5.079, -4.87, -4.786, -4.385, -4.525, -4.707, -4.607, -4.403, -4.607, -4.773, -4.846, -4.832, -4.925, -4.677, -4.487, -4.495, -4.597, -4.594, -4.629, -4.582, -4.832, -4.836, -4.687, -4.644, -4.967, -4.739, -4.803, -4.786, -5.133, -4.839, -4.899, -4.813, -4.973, -4.913, -5.002, -4.904, -5.114, -4.917, -4.886, -4.72, -4.926, -4.874, -4.677, -4.601, -4.924, -5.175, -4.906, -4.725, -5.135, -4.907, -4.829, -4.79, -5.185, -5.123, -4.988, -5.104, -5.33, -5.185, -5.158, -5.06, -5.282, -5.163, -5.06, -4.911, -5.03, -5.049, -4.688, -4.775, -5.055, -4.936, -4.807, -4.774, -5.162, -5.014, -4.975, -4.65, -4.919, -5.268, -4.892, -4.984, -5.139, -5.146, -4.998, -4.875, -5.035, -5.149, -5.123, -4.942, -5.108, -5.254, -4.856, -4.766, -5.051, -5.097, -4.715, -4.613, -4.786, -5.022, -4.986, -4.899, -4.96, -4.779, -4.897, -5.019, -5.453, -5.06, -4.788, -4.659, -4.767, -4.79, -4.378, -4.344, -4.727, -4.903, -4.875, -4.756, -4.988, -5.185, -4.943, -4.816, -4.839, -4.795, -4.747, -4.636, -4.753, -4.796, -4.716, -4.636, -4.775, -4.845, -4.809, -4.832, -5.013, -5.084, -4.909, -4.94, -5.031, -4.735, -4.625, -4.703, -4.933, -4.787, -4.808, -4.824, -5.266, -4.987, -4.634, -4.786, -5.08, -4.978, -4.988, -4.774, -5.006, -5.014, -4.866, -4.767, -4.722, -4.546, -4.359, -4.582, -5.062, -5.27, -5.077, -5.174, -5.2, -4.911, -4.96, -4.89, -5.115, -4.926, -4.839, -4.866, -5.211, -5.128, -5.037, -4.995, -5.131, -5.041, -4.969, -4.949, -5.052, -4.941, -4.671, -4.616, -5.11, -5.048, -4.751, -4.634, -5.052, -4.846, -4.742, -4.741, -4.903, -4.947, -4.848, -4.877, -4.886, -4.878, -4.956, -4.681, -4.941, -4.83, -5.185, -5.012, -4.967, -4.924, -4.77, -4.612, -4.957, -5.018, -4.97, -4.792, -4.788, -4.696, -4.525, -4.527, -4.721, -4.691, -4.853, -4.788, -4.931, -4.912, -4.954, -5.027, -4.937, -4.718, -4.512, -4.494, -4.675, -4.651, -4.666, -4.64, -4.849, -4.888, -4.833, -4.803, -4.863, -4.915, -4.733, -4.792, -4.872, -5.023, -4.923, -4.792, -4.906, -4.94, -4.801]}], 'missingValue': 'NaN'}]}], 'googleMetadataWorksheet': 'oruuxfm', 'googleSpreadSheetKey': '1wf30P-s54OTBdLw4dyeaIN53VDoN0u_hOqIwvAeLxtc', 'dataSetName': 'Ocn-MadangLagoonPapuaNewGuinea.Kuhnert.2001', 'inCompilation1_': 'Ocean2k_v1.0.0', 'minYear': 1880.792, 'datasetId': 'm8yv2VgG97zJmSg3XhqQ', 'inCompilation3_': 'PAGES2k_v2.1.0', 'geo': {'geometry': {'coordinates': [145.8167, -5.2167, -2.2], 'type': 'Point'}, 'properties': {'siteName': 'Madang Lagoon, Papua New Guinea', 'ocean': 'Pacific', 'type': 'http://linked.earth/ontology#Location', 'pages2kRegion': 'Ocean'}}, 'inCompilation2_': 'PAGES2k_v2.0.0', 'googleDataURL': 'https://docs.google.com/spreadsheets/d/1wf30P-s54OTBdLw4dyeaIN53VDoN0u_hOqIwvAeLxtc', 'maxYear': 1993.042, 'hasUrl': 'https://data.mint.isi.edu/files/lipd/Ocn-MadangLagoonPapuaNewGuinea.Kuhnert.2001.lpd', 'lipdVersion': 1.3, 'createdBy': 'matlab', 'archiveType': 'Coral'}
get_model_properties()[source]

Get all the properties associated with a model

Returns:

A list of unique properties attached to models

Return type:

List

Examples

from pylipd.utils.dataset import load_datasets
lipd = load_datasets(names='ODP846')
model_properties = lipd.get_model_properties()
print(model_properties)
['/home/docs/checkouts/readthedocs.org/user_builds/pylipd/conda/latest/lib/python3.10/site-packages/pylipd/data/ODP846.Lawrence.2006.lpd']
Loading 1 LiPD files
Loaded..
['hasEnsembleTable', 'type', 'hasCode', 'hasSummaryTable']
get_timeseries(dsnames, to_dataframe=False, mode='paleo', time='age')[source]

Get Legacy LiPD like Time Series Object (tso)

Parameters:
  • dsnames (list) – array of dataset id or name strings

  • to_dataframe (bool {True; False}) – Whether to return a dataframe along the dictionary. Default is False

Returns:

  • ts (dict) – A dictionary containing Time Series Object

  • df (Pandas.DataFrame) – If to_dataframe is set to True, returns a queriable Pandas DataFrame

Examples

from pylipd.lipd import LiPD

# Fetch LiPD data from remote RDF Graph
lipd_remote = LiPD()
lipd_remote.set_endpoint("https://linkedearth.graphdb.mint.isi.edu/repositories/LiPDVerse-dynamic")
ts_list = lipd_remote.get_timeseries(["Ocn-MadangLagoonPapuaNewGuinea.Kuhnert.2001", "MD98_2181.Stott.2007", "Ant-WAIS-Divide.Severinghaus.2012"])
for dsname, tsos in ts_list.items():
    for tso in tsos:
        if 'paleoData_variableName' in tso:
            print(dsname+': '+tso['paleoData_variableName']+': '+tso['archiveType'])
Extracting timeseries from dataset: Ocn-MadangLagoonPapuaNewGuinea.Kuhnert.2001 ...
Extracting timeseries from dataset: MD98_2181.Stott.2007 ...
Extracting timeseries from dataset: Ant-WAIS-Divide.Severinghaus.2012 ...
get_timeseries_essentials(dsnames=None, mode='paleo')[source]
Returns specific properties for timeseries: ‘dataSetName’, ‘archiveType’, ‘geo_meanLat’, ‘geo_meanLon’,

‘geo_meanElev’, ‘paleoData_variableName’, ‘paleoData_values’, ‘paleoData_units’, ‘paleoData_proxy’ (paleo only), ‘paleoData_proxyGeneral’ (paleo only), ‘time_variableName’, ‘time_values’, ‘time_units’, ‘depth_variableName’, ‘depth_values’, ‘depth_units’

Parameters:
  • dsnames (list) – array of dataset id or name strings

  • mode (paleo, chron) – Whether to retrun the information stored in the PaleoMeasurementTable or the ChronMeasurementTable. The default is ‘paleo’.

Raises:

ValueError – Need to select either ‘chron’ or ‘paleo’

Returns:

qres_df – A pandas dataframe returning the properties in columns for each series stored in a row of the dataframe

Return type:

pandas.DataFrame

Example

from pylipd.utils.dataset import load_datasets
lipd = load_datasets('ODP846.Lawrence.2006.lpd')
df_paleo = lipd.get_timeseries_essentials(mode='paleo')
print(df_paleo)
['/home/docs/checkouts/readthedocs.org/user_builds/pylipd/conda/latest/lib/python3.10/site-packages/pylipd/data/ODP846.Lawrence.2006.lpd']
Loading 1 LiPD files
Loaded..
             dataSetName      archiveType  geo_meanLat  geo_meanLon  \
0   ODP846.Lawrence.2006  Marine sediment         -3.1        -90.8   
1   ODP846.Lawrence.2006  Marine sediment         -3.1        -90.8   
2   ODP846.Lawrence.2006  Marine sediment         -3.1        -90.8   
3   ODP846.Lawrence.2006  Marine sediment         -3.1        -90.8   
4   ODP846.Lawrence.2006  Marine sediment         -3.1        -90.8   
5   ODP846.Lawrence.2006  Marine sediment         -3.1        -90.8   
6   ODP846.Lawrence.2006  Marine sediment         -3.1        -90.8   
7   ODP846.Lawrence.2006  Marine sediment         -3.1        -90.8   
8   ODP846.Lawrence.2006  Marine sediment         -3.1        -90.8   
9   ODP846.Lawrence.2006  Marine sediment         -3.1        -90.8   
10  ODP846.Lawrence.2006  Marine sediment         -3.1        -90.8   
11  ODP846.Lawrence.2006  Marine sediment         -3.1        -90.8   
12  ODP846.Lawrence.2006  Marine sediment         -3.1        -90.8   
13  ODP846.Lawrence.2006  Marine sediment         -3.1        -90.8   
14  ODP846.Lawrence.2006  Marine sediment         -3.1        -90.8   
15  ODP846.Lawrence.2006  Marine sediment         -3.1        -90.8   
16  ODP846.Lawrence.2006  Marine sediment         -3.1        -90.8   
17  ODP846.Lawrence.2006  Marine sediment         -3.1        -90.8   
18  ODP846.Lawrence.2006  Marine sediment         -3.1        -90.8   
19  ODP846.Lawrence.2006  Marine sediment         -3.1        -90.8   
20  ODP846.Lawrence.2006  Marine sediment         -3.1        -90.8   
21  ODP846.Lawrence.2006  Marine sediment         -3.1        -90.8   
22  ODP846.Lawrence.2006  Marine sediment         -3.1        -90.8   
23  ODP846.Lawrence.2006  Marine sediment         -3.1        -90.8   
24  ODP846.Lawrence.2006  Marine sediment         -3.1        -90.8   

    geo_meanElev paleoData_variableName  \
0        -3296.0              ukprime37   
1        -3296.0  c. wuellerstorfi d18o   
2        -3296.0  c. wuellerstorfi d18o   
3        -3296.0  c. wuellerstorfi d18o   
4        -3296.0                  event   
5        -3296.0                  event   
6        -3296.0                  event   
7        -3296.0           sample label   
8        -3296.0           sample label   
9        -3296.0           sample label   
10       -3296.0             temp prahl   
11       -3296.0              site/hole   
12       -3296.0  c. wuellerstorfi d13c   
13       -3296.0  c. wuellerstorfi d13c   
14       -3296.0  c. wuellerstorfi d13c   
15       -3296.0      u. peregrina d13c   
16       -3296.0      u. peregrina d13c   
17       -3296.0      u. peregrina d13c   
18       -3296.0               interval   
19       -3296.0                section   
20       -3296.0      u. peregrina d18o   
21       -3296.0      u. peregrina d18o   
22       -3296.0      u. peregrina d18o   
23       -3296.0            temp muller   
24       -3296.0              c37 total   

                                     paleoData_values paleoData_units  \
0   [0.821, 0.824, 0.828, 0.787, 0.777, 0.767, 0.7...        unitless   
1   [0.12, 0.23, 0.33, 0.33, 0.43, 0.53, 0.63, 0.7...     per mil PDB   
2   [0.12, 0.23, 0.33, 0.33, 0.43, 0.53, 0.63, 0.7...     per mil PDB   
3   [0.12, 0.23, 0.33, 0.33, 0.43, 0.53, 0.63, 0.7...     per mil PDB   
4   [138-846B, 138-846B, 138-846B, 138-846B, 138-8...        unitless   
5   [138-846B, 138-846B, 138-846B, 138-846B, 138-8...        unitless   
6   [138-846B, 138-846B, 138-846B, 138-846B, 138-8...        unitless   
7   [138-846B-1H-1, 138-846B-1H-1, 138-846B-1H-1, ...        unitless   
8   [138-846B-1H-1, 138-846B-1H-1, 138-846B-1H-1, ...        unitless   
9   [138-846B-1H-1, 138-846B-1H-1, 138-846B-1H-1, ...        unitless   
10  [23.0, 23.1, 23.2, 22.0, 21.7, 21.4, 21.7, 21....           deg C   
11  [846B, 846B, 846B, 846B, 846B, 846B, 846B, 846...        unitless   
12  [3.38, 3.46, 3.65, 3.88, 4.14, 4.47, 4.99, 4.9...     per mil PDB   
13  [3.38, 3.46, 3.65, 3.88, 4.14, 4.47, 4.99, 4.9...     per mil PDB   
14  [3.38, 3.46, 3.65, 3.88, 4.14, 4.47, 4.99, 4.9...     per mil PDB   
15  [nan, nan, nan, nan, nan, nan, nan, nan, nan, ...     per mil PDB   
16  [nan, nan, nan, nan, nan, nan, nan, nan, nan, ...     per mil PDB   
17  [nan, nan, nan, nan, nan, nan, nan, nan, nan, ...     per mil PDB   
18  [15-16, 25-26, 35-36, 45-46, 55-56, 65-66, 75-...              cm   
19  [1H-1, 1H-1, 1H-1, 1H-1, 1H-1, 1H-1, 1H-1, 1H-...        unitless   
20  [0.14, 0.01, -0.1, -0.06, -0.17, -0.21, -0.41,...     per mil PDB   
21  [0.14, 0.01, -0.1, -0.06, -0.17, -0.21, -0.41,...     per mil PDB   
22  [0.14, 0.01, -0.1, -0.06, -0.17, -0.21, -0.41,...     per mil PDB   
23  [23.545, 23.648, 23.752, 22.515, 22.206, 21.89...           deg C   
24  [2.37, 2.1, 1.87, 2.74, 3.75, 7.62, 7.86, 7.73...         nmol/kg   

   paleoData_proxy paleoData_proxyGeneral time_variableName  \
0             None                   None               age   
1             None                   None              None   
2             None                   None              None   
3             None                   None              None   
4             None                   None              None   
5             None                   None              None   
6             None                   None              None   
7             None                   None              None   
8             None                   None              None   
9             None                   None              None   
10            None                   None               age   
11            None                   None               age   
12            None                   None              None   
13            None                   None              None   
14            None                   None              None   
15            None                   None              None   
16            None                   None              None   
17            None                   None              None   
18            None                   None               age   
19            None                   None               age   
20            None                   None              None   
21            None                   None              None   
22            None                   None              None   
23            None                   None               age   
24            None                   None               age   

                                          time_values time_units  \
0   [5.228, 8.947, 11.966, 14.427, 16.502, 18.41, ...     kyr BP   
1                                                None       None   
2                                                None       None   
3                                                None       None   
4                                                None       None   
5                                                None       None   
6                                                None       None   
7                                                None       None   
8                                                None       None   
9                                                None       None   
10  [5.228, 8.947, 11.966, 14.427, 16.502, 18.41, ...     kyr BP   
11  [5.228, 8.947, 11.966, 14.427, 16.502, 18.41, ...     kyr BP   
12                                               None       None   
13                                               None       None   
14                                               None       None   
15                                               None       None   
16                                               None       None   
17                                               None       None   
18  [5.228, 8.947, 11.966, 14.427, 16.502, 18.41, ...     kyr BP   
19  [5.228, 8.947, 11.966, 14.427, 16.502, 18.41, ...     kyr BP   
20                                               None       None   
21                                               None       None   
22                                               None       None   
23  [5.228, 8.947, 11.966, 14.427, 16.502, 18.41, ...     kyr BP   
24  [5.228, 8.947, 11.966, 14.427, 16.502, 18.41, ...     kyr BP   

   depth_variableName                                       depth_values  \
0               depth  [0.16, 0.26, 0.36, 0.46, 0.56, 0.66, 0.76, 0.8...   
1          depth comp  [12.0, 23.0, 33.0, 33.0, 43.0, 53.0, 63.0, 73....   
2               depth  [0.12, 0.23, 0.33, 0.33, 0.43, 0.53, 0.63, 0.7...   
3            depth cr  [0.12, 0.23, 0.33, 0.33, 0.43, 0.53, 0.63, 0.7...   
4          depth comp  [12.0, 23.0, 33.0, 33.0, 43.0, 53.0, 63.0, 73....   
5               depth  [0.12, 0.23, 0.33, 0.33, 0.43, 0.53, 0.63, 0.7...   
6            depth cr  [0.12, 0.23, 0.33, 0.33, 0.43, 0.53, 0.63, 0.7...   
7          depth comp  [12.0, 23.0, 33.0, 33.0, 43.0, 53.0, 63.0, 73....   
8               depth  [0.12, 0.23, 0.33, 0.33, 0.43, 0.53, 0.63, 0.7...   
9            depth cr  [0.12, 0.23, 0.33, 0.33, 0.43, 0.53, 0.63, 0.7...   
10              depth  [0.16, 0.26, 0.36, 0.46, 0.56, 0.66, 0.76, 0.8...   
11              depth  [0.16, 0.26, 0.36, 0.46, 0.56, 0.66, 0.76, 0.8...   
12         depth comp  [12.0, 23.0, 33.0, 33.0, 43.0, 53.0, 63.0, 73....   
13              depth  [0.12, 0.23, 0.33, 0.33, 0.43, 0.53, 0.63, 0.7...   
14           depth cr  [0.12, 0.23, 0.33, 0.33, 0.43, 0.53, 0.63, 0.7...   
15         depth comp  [12.0, 23.0, 33.0, 33.0, 43.0, 53.0, 63.0, 73....   
16              depth  [0.12, 0.23, 0.33, 0.33, 0.43, 0.53, 0.63, 0.7...   
17           depth cr  [0.12, 0.23, 0.33, 0.33, 0.43, 0.53, 0.63, 0.7...   
18              depth  [0.16, 0.26, 0.36, 0.46, 0.56, 0.66, 0.76, 0.8...   
19              depth  [0.16, 0.26, 0.36, 0.46, 0.56, 0.66, 0.76, 0.8...   
20         depth comp  [12.0, 23.0, 33.0, 33.0, 43.0, 53.0, 63.0, 73....   
21              depth  [0.12, 0.23, 0.33, 0.33, 0.43, 0.53, 0.63, 0.7...   
22           depth cr  [0.12, 0.23, 0.33, 0.33, 0.43, 0.53, 0.63, 0.7...   
23              depth  [0.16, 0.26, 0.36, 0.46, 0.56, 0.66, 0.76, 0.8...   
24              depth  [0.16, 0.26, 0.36, 0.46, 0.56, 0.66, 0.76, 0.8...   

   depth_units  
0            m  
1          mcd  
2            m  
3         rmcd  
4          mcd  
5            m  
6         rmcd  
7          mcd  
8            m  
9         rmcd  
10           m  
11           m  
12         mcd  
13           m  
14        rmcd  
15         mcd  
16           m  
17        rmcd  
18           m  
19           m  
20         mcd  
21           m  
22        rmcd  
23           m  
24           m  

To return the information stored in the ChronTable:

from pylipd.utils.dataset import load_datasets
lipd = load_datasets('ODP846.Lawrence.2006.lpd')
df_chron = lipd.get_timeseries_essentials(mode='chron')
print(df_chron)
['/home/docs/checkouts/readthedocs.org/user_builds/pylipd/conda/latest/lib/python3.10/site-packages/pylipd/data/ODP846.Lawrence.2006.lpd']
Loading 1 LiPD files
Loaded..
            dataSetName      archiveType  geo_meanLat  geo_meanLon  \
0  ODP846.Lawrence.2006  Marine sediment         -3.1        -90.8   
1  ODP846.Lawrence.2006  Marine sediment         -3.1        -90.8   
2  ODP846.Lawrence.2006  Marine sediment         -3.1        -90.8   

   geo_meanElev chronData_variableName  \
0       -3296.0                   d18o   
1       -3296.0                    age   
2       -3296.0                  depth   

                                    chronData_values chronData_units  \
0  [3.38, 3.46, 3.765, 4.14, 4.47, 4.99, 4.99, 4....          permil   
1  [3.645, 7.99, 11.18, 13.803, 15.886, 17.93, 19...           ky BP   
2  [0.12, 0.23, 0.33, 0.43, 0.53, 0.63, 0.73, 0.8...               m   

  time_variableName                                        time_values  \
0               age  [3.645, 7.99, 11.18, 13.803, 15.886, 17.93, 19...   
1               age  [3.645, 7.99, 11.18, 13.803, 15.886, 17.93, 19...   
2               age  [3.645, 7.99, 11.18, 13.803, 15.886, 17.93, 19...   

  time_units depth_variableName  \
0      ky BP              depth   
1      ky BP              depth   
2      ky BP              depth   

                                        depth_values depth_units  
0  [0.12, 0.23, 0.33, 0.43, 0.53, 0.63, 0.73, 0.8...           m  
1  [0.12, 0.23, 0.33, 0.43, 0.53, 0.63, 0.73, 0.8...           m  
2  [0.12, 0.23, 0.33, 0.43, 0.53, 0.63, 0.73, 0.8...           m  
get_variable_properties()[source]

Get a list of variable properties that can be used for querying

Returns:

A list of unique variable properties

Return type:

list

Examples

from pylipd.utils.dataset import load_dir
lipd = load_dir(name='Pages2k')
variable_properties = lipd.get_variable_properties()
print(variable_properties)
Loading 16 LiPD files
Loaded..
['dataType', 'hasResolution', 'hasType', 'hasVariableId', 'measurementTableMD5', 'hasDescription', 'hasName', 'hasMeanValue', 'hasMinValue', 'hasValues', 'wDSPaleoUrl', 'hasUnits', 'foundInDataset', 'paleoDataTableName', 'hasStandardVariable', 'inferredVariableType', 'type', 'measurementTableName', 'hasColumnNumber', 'hasMedianValue', 'hasMaxValue', 'foundInTable', 'hasArchiveType', 'hasNotes', 'qCCertification', 'hasProxy', 'hasInterpretation', 'partOfCompilation', 'useInGlobalTemperatureAnalysis', 'precededBy', 'pages2kID', 'calibratedVia', 'proxyObservationType', 'detail', 'measurementMaterial', 'hasUncertainty', 'measurementMethod', 'sensorSpecies', 'ocean2kID', 'iso2kUI', 'sensorGenus']
load(lipdfiles, parallel=False, standardize=True, add_labels=True)[source]

Load LiPD files.

Parameters:
  • lipdfiles (list of str) – array of paths to lipd files (the paths could also be urls)

  • parallel (bool) – (Optional) set to True to process lipd files in parallel. You must run this function under the “__main__” process for this to work

Examples

In this example, we load LiPD files for an array of paths.

from pylipd.lipd import LiPD

lipd = LiPD()
lipd.load([
    "../examples/data/Ocn-MadangLagoonPapuaNewGuinea.Kuhnert.2001.lpd",
    "../examples/data/MD98_2181.Stott.2007.lpd",
    "../examples/data/Ant-WAIS-Divide.Severinghaus.2012.lpd",
    "https://lipdverse.org/data/LCf20b99dfe8d78840ca60dfb1f832b9ec/1_0_1/Nunalleq.Ledger.2018.lpd"
])

print(lipd.get_all_dataset_names())
Loading 4 LiPD files
Loaded..
['Ocn-MadangLagoonPapuaNewGuinea.Kuhnert.2001', 'MD98_2181.Stott.2007', 'Ant-WAIS-Divide.Severinghaus.2012', 'Nunalleq.Ledger.2018']
load_datasets(datasets: list[Dataset])[source]

Loads instances of Dataset class into the LiPD graph

Parameters:

pylipd.classes.Dataset (list of) – A list of Dataset objects

Examples

pyLipd ships with existing datasets that can be loaded directly through the package. Let’s load the Pages2k sample datasets using this method.

from pylipd.utils.dataset import load_dir

lipd = load_dir('Pages2k')
dses = lipd.get_datasets()

# Modify the datasets if needed, then write them to the same, or another LiPD object

lipd2 = LiPD()
lipd2.load_datasets(dses)
Loading 16 LiPD files
Loaded..
load_from_dir(dir_path, parallel=False, cutoff=None, standardize=True, add_labels=True)[source]

Load LiPD files from a directory

Parameters:
  • dir_path (str) – path to the directory containing lipd files

  • parallel (bool) – (Optional) set to True to process lipd files in parallel. You must run this function under the “__main__” process for this to work

  • cutoff (int) – (Optional) the maximum number of files to load at once.

Examples

In this example, we load LiPD files from a directory.

from pylipd.lipd import LiPD

lipd = LiPD()
lipd.load_from_dir("../examples/data")

print(lipd.get_all_dataset_names())
Loading 4 LiPD files
Loaded..
['Ant-WAIS-Divide.Severinghaus.2012', 'Ocn-MadangLagoonPapuaNewGuinea.Kuhnert.2001', 'MD98_2181.Stott.2007', 'ODP846.Lawrence.2006']
load_remote_datasets(dsnames, load_default_graph=True)[source]

Loads remote datasets into cache if a remote endpoint is set

Parameters:

dsnames (array) – array of dataset names

Examples

from pylipd.lipd import LiPD

# Fetch LiPD data from remote RDF Graph
lipd_remote = LiPD()
lipd_remote.set_endpoint("https://linkedearth.graphdb.mint.isi.edu/repositories/LiPDVerse-dynamic")
lipd_remote.load_remote_datasets(["Ocn-MadangLagoonPapuaNewGuinea.Kuhnert.2001", "MD98_2181.Stott.2007", "Ant-WAIS-Divide.Severinghaus.2012"])
print(lipd_remote.get_all_dataset_names())
Caching datasets from remote endpoint..
Making remote query to endpoint: https://linkedearth.graphdb.mint.isi.edu/repositories/LiPDVerse-dynamic
Done..
['Ocn-MadangLagoonPapuaNewGuinea.Kuhnert.2001', 'MD98_2181.Stott.2007', 'Ant-WAIS-Divide.Severinghaus.2012']
pop(dsnames)[source]

Pops dataset(s) from the graph and returns the popped LiPD object

Parameters:

dsnames (str or list of str) – dataset name(s) to be popped.

Returns:

LiPD object with the popped dataset(s)

Return type:

pylipd.lipd.LiPD

Examples

from pylipd.lipd import LiPD

# Load local files
lipd = LiPD()
lipd.load([
    "../examples/data/Ocn-MadangLagoonPapuaNewGuinea.Kuhnert.2001.lpd",
    "../examples/data/MD98_2181.Stott.2007.lpd"
])
all_datasets = lipd.get_all_dataset_names()
print("Loaded datasets: " + str(all_datasets))
popped = lipd.pop(all_datasets[0])
print("Loaded datasets after pop: " + str(lipd.get_all_dataset_names()))
print("Popped dataset: " + str(popped.get_all_dataset_names()))
Loading 2 LiPD files
Loaded..
Loaded datasets: ['Ocn-MadangLagoonPapuaNewGuinea.Kuhnert.2001', 'MD98_2181.Stott.2007']
Loaded datasets after pop: ['MD98_2181.Stott.2007']
Popped dataset: ['Ocn-MadangLagoonPapuaNewGuinea.Kuhnert.2001']
remove(dsnames)[source]

Removes dataset(s) from the graph

Parameters:

dsnames (str or list of str) – dataset name(s) to be removed

Examples

from pylipd.lipd import LiPD

# Load local files
lipd = LiPD()
lipd.load([
    "../examples/data/Ocn-MadangLagoonPapuaNewGuinea.Kuhnert.2001.lpd",
    "../examples/data/MD98_2181.Stott.2007.lpd"
])
all_datasets = lipd.get_all_dataset_names()
print("Loaded datasets: " + str(all_datasets))
lipd.remove(all_datasets[0])
print("Loaded datasets after remove: " + str(lipd.get_all_dataset_names()))
Loading 2 LiPD files
Loaded..
Loaded datasets: ['Ocn-MadangLagoonPapuaNewGuinea.Kuhnert.2001', 'MD98_2181.Stott.2007']
Loaded datasets after remove: ['MD98_2181.Stott.2007']
to_lipd_series(parallel=False)[source]

Converts the LiPD object to a LiPDSeries object

Parameters:

parallel (bool) – Whether to use parallel processing to load the data. Default is False

Returns:

A LiPDSeries object

Return type:

pylipd.lipd.LiPDSeries

Examples

from pylipd.lipd import LiPD

lipd = LiPD()
lipd.load([
    "../examples/data/ODP846.Lawrence.2006.lpd"
])

S = lipd.to_lipd_series()
Loading 1 LiPD files
Loaded..
Creating LiPD Series...
- Extracting dataset subgraphs
- Extracting variable subgraphs
Done..
update_remote_datasets(dsnames)[source]

Updates local LiPD Graph for datasets to remote endpoint

LiPDSeries (pylipd.lipd_series.LiPDSeries)

class pylipd.lipd_series.LiPDSeries(graph=None)[source]

The LiPD Series class describes a collection of LiPD (Linked Paleo Data) variables. It contains an RDF Graph which is serialization of LiPD variables into an RDF graph containing terms from the LiPD Ontology <http://linked.earth/Ontology/release/core/1.2.0/index-en.html>. Each LiPD Variable is also associated with the LiPD itself so it can be deserialized into the original LiPD format. How to browse and query the LiPD variables is described in a short example below.

Examples

In this example, we read an online LiPD file and convert it into a time series object dictionary.

from pylipd.lipd_series import LiPDSeries

lipd = LiPD()
lipd.load(["https://lipdverse.org/data/LCf20b99dfe8d78840ca60dfb1f832b9ec/1_0_1//Nunalleq.Ledger.2018.lpd"])
lipd_series = lipd.to_lipd_series()
Loading 1 LiPD files
Loaded..
Creating LiPD Series...
- Extracting dataset subgraphs
- Extracting variable subgraphs
Done..

Methods

clear()

Clears the graph

copy()

Makes a copy of the object

filter_by_name(name)

Filters series to return a new LiPDSeries that only keeps variables that have the specified name (regex)

filter_by_proxy(proxy)

Filters series to return a new LiPDSeries that only keeps variables that have the specified proxy (regex)

filter_by_resolution(threshold[, stats])

Filters series to return a new LiPDSeries that only keeps variables that have a resolution less than the specified threshold.

get(ids)

Get id(s) from the graph and returns the LiPD object

get_all_graph_ids()

Get all Graph ids

get_all_proxy()

Get a list of all possible proxy.

get_all_variable_names()

Get a list of all possible distinct variableNames.

get_all_variables()

Returns a list of all variables in the graph

get_timeseries_essentials()

This function returns information about each variable: dataSetName, archiveType, name, values, units, TSID, proxy.

get_variable_properties()

Get a list of all the properties name associated with the dataset.

load(lipd[, parallel])

Extract Variables from the LiPD object.

merge(rdf)

Merges the current LiPD object with another LiPD object

pop(ids)

Pops graph(s) from the combined graph and returns the popped RDF Graph

query(query[, remote, result])

Once data is loaded into the graph (or remote endpoint set), one can make SparQL queries to the graph

remove(ids)

Removes ids(s) from the graph

serialize()

Returns RDF quad serialization of the current combined Graph .

set_endpoint(endpoint)

Sets a SparQL endpoint for a remote Knowledge Base (example: GraphDB)

filter_by_name(name)[source]

Filters series to return a new LiPDSeries that only keeps variables that have the specified name (regex)

Parameters:

name (str) – The variable name to filter by

Returns:

A new LiPDSeries object that only contains variables that have the specified name (regex)

Return type:

pylipd.lipd_series.LiPDSeries

Examples

from pylipd.utils.dataset import load_datasets
lipd = load_datasets('ODP846.Lawrence.2006.lpd')
S = lipd.to_lipd_series()
sst = S.filter_by_name('sst')

print(sst.get_all_variable_names())
['/home/docs/checkouts/readthedocs.org/user_builds/pylipd/conda/latest/lib/python3.10/site-packages/pylipd/data/ODP846.Lawrence.2006.lpd']
Loading 1 LiPD files
Loaded..
Creating LiPD Series...
- Extracting dataset subgraphs
- Extracting variable subgraphs
Done..
['sst']
filter_by_proxy(proxy)[source]

Filters series to return a new LiPDSeries that only keeps variables that have the specified proxy (regex)

Parameters:

proxy (str) – The name of the proxy to filter by

Returns:

A new LiPDSeries object that only contains variables that have the specified name (regex)

Return type:

pylipd.lipd_series.LiPDSeries

Examples

from pylipd.utils.dataset import load_dir
lipd = load_dir('Pages2k')
S = lipd.to_lipd_series()
S_filtered = S.filter_by_proxy('ring width')
print(S_filtered.get_all_proxy())
Loading 16 LiPD files
Loaded..
Creating LiPD Series...
- Extracting dataset subgraphs
- Extracting variable subgraphs
Done..
['ring width']
filter_by_resolution(threshold, stats='Mean')[source]

Filters series to return a new LiPDSeries that only keeps variables that have a resolution less than the specified threshold.

Parameters:
  • threshold (float) – The maximum resolution to keep

  • stats (str, optional) – Whether to use ‘Mean’, ‘Median’, ‘Min’ or ‘Max’ resolution. The default is ‘Mean’.

Raises:

ValueError – Make sure that the stats is of [‘Mean’,’Median’, ‘Min’, ‘Max’].

Returns:

S – A new LiPDSeries object that only contains the filtered variables

Return type:

pylipd.lipd_series.LiPDSeries

Examples

from pylipd.utils.dataset import load_dir
lipd = load_dir('Pages2k')
S = lipd.to_lipd_series()
S_filtered = S.filter_by_resolution(10)
Loading 16 LiPD files
Loaded..
Creating LiPD Series...
- Extracting dataset subgraphs
- Extracting variable subgraphs
Done..
get_all_proxy()[source]

Get a list of all possible proxy. Useful for filtering and querying.

Returns:

A list of unique proxies

Return type:

list

Examples

from pylipd.utils.dataset import load_dir
lipd = load_dir('Pages2k')
S = lipd.to_lipd_series()
proxyName = S.get_all_proxy()
print(proxyName)
Loading 16 LiPD files
Loaded..
Creating LiPD Series...
- Extracting dataset subgraphs
- Extracting variable subgraphs
Done..
['alkenone', 'borehole', 'd18O', 'ring width', 'maximum latewood density', 'Mg/Ca', 'historical', 'reflectance']
get_all_variable_names()[source]

Get a list of all possible distinct variableNames. Useful for filtering and querying.

Returns:

A list of unique variableName

Return type:

list

Examples

from pylipd.utils.dataset import load_dir
lipd = load_dir('Pages2k')
S = lipd.to_lipd_series()
varName = S.get_all_variable_names()
print(varName)
Loading 16 LiPD files
Loaded..
Creating LiPD Series...
- Extracting dataset subgraphs
- Extracting variable subgraphs
Done..
['temperature', 'year', 'uncertainty_temperature', 'd18O', 'trsgi', 'Uk37', 'MXD', 'depth_bottom', 'Mg_Ca', 'notes', 'depth_top']
get_all_variables()[source]

Returns a list of all variables in the graph

Returns:

A dataframe of all variables in the graph with columns uri, varid, varname

Return type:

pandas.DataFrame

Examples

from pylipd.utils.dataset import load_dir

lipd = load_dir()
S = lipd.to_lipd_series()
df = S.get_all_variables()

print(df)
Loading 16 LiPD files
Loaded..
Creating LiPD Series...
- Extracting dataset subgraphs
- Extracting variable subgraphs
Done..
                                                  uri           TSID  \
0   http://linked.earth/lipd/Ocn-AlboranSea436B.Ni...    LPD0e0867fe   
1   http://linked.earth/lipd/Ant-WAIS-Divide.Sever...    LPDb9285123   
2   http://linked.earth/lipd/Asi-SourthAndMiddleUr...       Asia_230   
3   http://linked.earth/lipd/Arc-Kongressvatnet.D_...        Arc_078   
4   http://linked.earth/lipd/Ocn-FeniDrift.Richter...    LPDb7290ea4   
5   http://linked.earth/lipd/Ocn-FeniDrift.Richter...    LPD47182517   
6   http://linked.earth/lipd/Eur-Stockholm.Leijonh...        Eur_006   
7   http://linked.earth/lipd/Eur-CoastofPortugal.A...        Eur_010   
8   http://linked.earth/lipd/Eur-FinnishLakelands....        Eur_005   
9   http://linked.earth/lipd/Eur-LakeSilvaplana.Tr...        Eur_002   
10  http://linked.earth/lipd/Ocn-AlboranSea436B.Ni...    PYTPD2RJATT   
11  http://linked.earth/lipd/Ant-WAIS-Divide.Sever...    PYTAAFWZCUK   
12  http://linked.earth/lipd/Asi-SourthAndMiddleUr...    PYTX5TD5SOT   
13  http://linked.earth/lipd/Ocn-PedradeLume-CapeV...    PYT296KN772   
14  http://linked.earth/lipd/Ocn-RedSea.Felis.2000...    PYTXPC7HUA2   
15  http://linked.earth/lipd/Eur-SpannagelCave.Man...    PYTSOOGT8HT   
16  http://linked.earth/lipd/Eur-SpanishPyrenees.D...    PYT2K8MIA3N   
17  http://linked.earth/lipd/Eur-NorthernSpain.Mar...    PYTE7VH7UMO   
18  http://linked.earth/lipd/Arc-Kongressvatnet.D_...    PYTOAVDFCGU   
19  http://linked.earth/lipd/Eur-NorthernScandinav...    PYTECO66XAD   
20  http://linked.earth/lipd/Ocn-FeniDrift.Richter...    PYTHS7WC58V   
21  http://linked.earth/lipd/Ocn-FeniDrift.Richter...    PYTA482M43E   
22  http://linked.earth/lipd/Eur-Stockholm.Leijonh...    PYTWVH672OU   
23  http://linked.earth/lipd/Eur-CoastofPortugal.A...    PYTNSKF0DVD   
24  http://linked.earth/lipd/Eur-FinnishLakelands....    PYTUSB62S0A   
25  http://linked.earth/lipd/Eur-LakeSilvaplana.Tr...    PYT1E4X3DDF   
26  http://linked.earth/lipd/Ocn-SinaiPeninsula_Re...    PYTGGLQ9T54   
27  http://linked.earth/lipd/Ant-WAIS-Divide.Sever...    LPDa7a4074f   
28  http://linked.earth/lipd/Ocn-PedradeLume-CapeV...  Ocean2kHR_107   
29  http://linked.earth/lipd/Ocn-RedSea.Felis.2000...  Ocean2kHR_019   
30  http://linked.earth/lipd/Eur-SpannagelCave.Man...        Eur_001   
31  http://linked.earth/lipd/Eur-NorthernSpain.Mar...        Eur_008   
32  http://linked.earth/lipd/Ocn-SinaiPeninsula_Re...  Ocean2kHR_018   
33  http://linked.earth/lipd/Eur-SpanishPyrenees.D...        Eur_020   
34  http://linked.earth/lipd/Arc-Kongressvatnet.D_...        Arc_077   
35  http://linked.earth/lipd/Eur-NorthernScandinav...        Eur_014   
36  http://linked.earth/lipd/Ocn-FeniDrift.Richter...    LPD071f9a58   
37  http://linked.earth/lipd/Ocn-FeniDrift.Richter...    LPDbceb5d84   
38  http://linked.earth/lipd/Ocn-FeniDrift.Richter...    LPDba471ae7   
39  http://linked.earth/lipd/Ocn-FeniDrift.Richter...    LPD6e0eacd1   
40  http://linked.earth/lipd/Ocn-FeniDrift.Richter...    LPD873b43d0   

               variableName  
0               temperature  
1               temperature  
2               temperature  
3               temperature  
4               temperature  
5               temperature  
6               temperature  
7               temperature  
8               temperature  
9               temperature  
10                     year  
11                     year  
12                     year  
13                     year  
14                     year  
15                     year  
16                     year  
17                     year  
18                     year  
19                     year  
20                     year  
21                     year  
22                     year  
23                     year  
24                     year  
25                     year  
26                     year  
27  uncertainty_temperature  
28                     d18O  
29                     d18O  
30                     d18O  
31                     d18O  
32                     d18O  
33                    trsgi  
34                     Uk37  
35                      MXD  
36             depth_bottom  
37                    Mg_Ca  
38                    Mg_Ca  
39                    notes  
40                depth_top  
get_timeseries_essentials()[source]

This function returns information about each variable: dataSetName, archiveType, name, values, units, TSID, proxy.

Returns:

qres_df – A dataframe containing the information in each column

Return type:

pandas.DataFrame

Examples

from pylipd.utils.dataset import load_dir

lipd = load_dir()
S = lipd.to_lipd_series()
df = S.get_timeseries_essentials()

print(df)
Loading 16 LiPD files
Loaded..
Creating LiPD Series...
- Extracting dataset subgraphs
- Extracting variable subgraphs
Done..
                                    dataSetName      archiveType  \
0          Ocn-AlboranSea436B.Nieto-Moreno.2013  Marine sediment   
1          Ocn-AlboranSea436B.Nieto-Moreno.2013  Marine sediment   
2             Ant-WAIS-Divide.Severinghaus.2012         Borehole   
3             Ant-WAIS-Divide.Severinghaus.2012         Borehole   
4             Ant-WAIS-Divide.Severinghaus.2012         Borehole   
5        Asi-SourthAndMiddleUrals.Demezhko.2007         Borehole   
6        Asi-SourthAndMiddleUrals.Demezhko.2007         Borehole   
7   Ocn-PedradeLume-CapeVerdeIslands.Moses.2006            Coral   
8   Ocn-PedradeLume-CapeVerdeIslands.Moses.2006            Coral   
9                         Ocn-RedSea.Felis.2000            Coral   
10                        Ocn-RedSea.Felis.2000            Coral   
11               Eur-SpannagelCave.Mangini.2005       Speleothem   
12               Eur-SpannagelCave.Mangini.2005       Speleothem   
13        Eur-SpanishPyrenees.Dorado-Linan.2012             Wood   
14        Eur-SpanishPyrenees.Dorado-Linan.2012             Wood   
15       Eur-NorthernSpain.Martin-Chivelet.2011       Speleothem   
16       Eur-NorthernSpain.Martin-Chivelet.2011       Speleothem   
17             Arc-Kongressvatnet.D'Andrea.2012    Lake sediment   
18             Arc-Kongressvatnet.D'Andrea.2012    Lake sediment   
19             Arc-Kongressvatnet.D'Andrea.2012    Lake sediment   
20           Eur-NorthernScandinavia.Esper.2012             Wood   
21           Eur-NorthernScandinavia.Esper.2012             Wood   
22                   Ocn-FeniDrift.Richter.2009  Marine sediment   
23                   Ocn-FeniDrift.Richter.2009  Marine sediment   
24                   Ocn-FeniDrift.Richter.2009  Marine sediment   
25                   Ocn-FeniDrift.Richter.2009  Marine sediment   
26                   Ocn-FeniDrift.Richter.2009  Marine sediment   
27                   Ocn-FeniDrift.Richter.2009  Marine sediment   
28                   Ocn-FeniDrift.Richter.2009  Marine sediment   
29                   Ocn-FeniDrift.Richter.2009  Marine sediment   
30                   Ocn-FeniDrift.Richter.2009  Marine sediment   
31              Eur-Stockholm.Leijonhufvud.2009        Documents   
32              Eur-Stockholm.Leijonhufvud.2009        Documents   
33            Eur-CoastofPortugal.Abrantes.2011  Marine sediment   
34            Eur-CoastofPortugal.Abrantes.2011  Marine sediment   
35             Eur-FinnishLakelands.Helama.2014             Wood   
36             Eur-FinnishLakelands.Helama.2014             Wood   
37             Eur-LakeSilvaplana.Trachsel.2010    Lake sediment   
38             Eur-LakeSilvaplana.Trachsel.2010    Lake sediment   
39      Ocn-SinaiPeninsula,RedSea.Moustafa.2000            Coral   
40      Ocn-SinaiPeninsula,RedSea.Moustafa.2000            Coral   

                       name           TSID  \
0               temperature    LPD0e0867fe   
1                      year    PYTPD2RJATT   
2               temperature    LPDb9285123   
3                      year    PYTAAFWZCUK   
4   uncertainty_temperature    LPDa7a4074f   
5               temperature       Asia_230   
6                      year    PYTX5TD5SOT   
7                      year    PYT296KN772   
8                      d18O  Ocean2kHR_107   
9                      d18O  Ocean2kHR_019   
10                     year    PYTXPC7HUA2   
11                     d18O        Eur_001   
12                     year    PYTSOOGT8HT   
13                    trsgi        Eur_020   
14                     year    PYT2K8MIA3N   
15                     year    PYTE7VH7UMO   
16                     d18O        Eur_008   
17              temperature        Arc_078   
18                     Uk37        Arc_077   
19                     year    PYTOAVDFCGU   
20                      MXD        Eur_014   
21                     year    PYTECO66XAD   
22                    notes    LPD6e0eacd1   
23                    Mg_Ca    LPDba471ae7   
24                depth_top    LPD873b43d0   
25             depth_bottom    LPD071f9a58   
26              temperature    LPDb7290ea4   
27                     year    PYTHS7WC58V   
28                     year    PYTA482M43E   
29              temperature    LPD47182517   
30                    Mg_Ca    LPDbceb5d84   
31              temperature        Eur_006   
32                     year    PYTWVH672OU   
33                     year    PYTNSKF0DVD   
34              temperature        Eur_010   
35              temperature        Eur_005   
36                     year    PYTUSB62S0A   
37                     year    PYT1E4X3DDF   
38              temperature        Eur_002   
39                     d18O  Ocean2kHR_018   
40                     year    PYTGGLQ9T54   

                                               values   units proxy  
0   [18.79, 19.38, 19.61, 18.88, 18.74, 19.25, 18....    degC  None  
1   [1999.07, 1993.12, 1987.17, 1975.26, 1963.36, ...   yr AD  None  
2   [-29.607, -29.607, -29.606, -29.606, -29.605, ...    degC  None  
3   [8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19,...   yr AD  None  
4   [1.327, 1.328, 1.328, 1.329, 1.33, 1.33, 1.331...    degC  None  
5   [0.166, 0.264, 0.354, 0.447, 0.538, 0.62, 0.68...    degC  None  
6   [800, 850, 900, 950, 1000, 1050, 1100, 1150, 1...   yr AD  None  
7   [1928.96, 1929.04, 1929.12, 1929.21, 1929.29, ...   yr AD  None  
8   [-3.11, -2.9, -2.88, -2.73, -2.73, -2.84, -2.8...  permil  None  
9   [-4.12, -3.82, -3.05, -3.02, -3.62, -3.96, -3....  permil  None  
10  [1995.583, 1995.417, 1995.25, 1995.083, 1994.9...   yr AD  None  
11  [-7.49, -7.41, -7.36, -7.15, -7.28, -6.99, -6....  permil  None  
12  [1935.0, 1932.0, 1930.0, 1929.0, 1929.0, 1928....   yr AD  None  
13  [-1.612, -0.703, -0.36, -0.767, -0.601, -0.733...    None  None  
14  [1260, 1261, 1262, 1263, 1264, 1265, 1266, 126...   yr AD  None  
15  [2000, 1987, 1983, 1978, 1975, 1971, 1967, 196...   yr AD  None  
16  [0.94, 0.8, 0.23, 0.17, 0.51, 0.36, 0.24, 0.4,...  permil  None  
17  [5.9, 5.1, 6.1, 5.3, 4.3, 4.8, 3.8, 4.8, 4.3, ...    degC  None  
18  [-0.65, -0.67, -0.65, -0.67, -0.69, -0.68, -0....    None  None  
19  [2008, 2004, 2000, 1996, 1990, 1987, 1982, 197...   yr AD  None  
20  [0.46, 1.305, 0.755, -0.1, -0.457, 1.62, 0.765...    None  None  
21  [-138, -137, -136, -135, -134, -133, -132, -13...   yr AD  None  
22  [M200309, M200309, M200309, M200309, M200309, ...    None  None  
23  [2.31, 1.973, 1.901, 1.887, 2.038, 2.394, 1.83...    None  None  
24  [0.5, 1.5, 2.5, 3.5, 4.5, 5.5, 6.5, 7.5, 8.5, ...      cm  None  
25  [0.5, 1.5, 2.5, 3.5, 4.5, 5.5, 6.5, 7.5, 8.5, ...      cm  None  
26  [12.94, 10.99, 10.53, 10.44, 11.39, 13.38, 10....    degC  None  
27  [1998, 1987, 1975, 1962, 1949, 1936, 1924, 191...   yr AD  None  
28  [1998, 1987, 1975, 1962, 1949, 1936, 1924, 191...   yr AD  None  
29  [12.94, 10.99, 10.53, 10.44, 11.39, 13.38, 10....    degC  None  
30  [2.31, 1.973, 1.901, 1.887, 2.038, 2.394, 1.83...    None  None  
31  [-1.7212, -1.6382, -0.6422, 0.1048, -0.7252, -...    degC  None  
32  [1502, 1503, 1504, 1505, 1506, 1507, 1508, 150...   yr AD  None  
33  [971.19, 982.672, 991.858, 1001.044, 1010.23, ...   yr AD  None  
34  [15.235, 15.329, 15.264, 15.376, 15.4, 15.129,...    degC  None  
35  [14.603, 14.643, 12.074, 13.898, 13.671, 13.41...    degC  None  
36  [2000, 1999, 1998, 1997, 1996, 1995, 1994, 199...   yr AD  None  
37  [1175, 1176, 1177, 1178, 1179, 1180, 1181, 118...   yr AD  None  
38  [0.181707222, 0.111082797, 0.001382129, -0.008...    degC  None  
39  [-3.05, -3.63, -3.53, -3.47, -3.1, -3.45, -3.6...  permil  None  
40  [1993.12, 1992.86, 1992.66, 1992.39, 1992.12, ...   yr AD  None  
get_variable_properties()[source]

Get a list of all the properties name associated with the dataset. Useful to write custom queries

Returns:

clean_list – A list of unique variable properties

Return type:

list

Examples

from pylipd.utils.dataset import load_dir

lipd = load_dir()
S = lipd.to_lipd_series()
l = S.get_variable_properties()

print(l)
Loading 16 LiPD files
Loaded..
Creating LiPD Series...
- Extracting dataset subgraphs
- Extracting variable subgraphs
Done..
['hasMinValue', 'hasColumnNumber', 'hasVariableId', 'paleoDataTableName', 'hasVersion', 'hasScope', 'foundInTable', 'hasStandardVariable', 'useInGlobalTemperatureAnalysis', 'foundInDatasetName', 'hasArchiveType', 'hasVariableDetail', 'hasMedianValue', 'hasMeanValue', 'hasMaxValue', 'partOfCompilation', 'measurementTableName', 'pages2kID', 'hasBasis', 'inferredVariableType', 'measurementTableMD5', 'foundInDataset', 'hasName', 'reference', 'hasDescription', 'wDSPaleoUrl', 'hasType', 'detail', 'label', 'hasNotes', 'hasValues', 'hasInterpretation', 'dataType', 'hasProxy', 'ocean2kID', 'hasDirection', 'hasResolution', 'proxyObservationType', 'sensorGenus', 'hasUncertainty', 'hasEquation', 'hasUnits', 'qCCertification', 'calibratedVia', 'sensorSpecies', 'precededBy', 'measurementMaterial', 'iso2kUI', 'measurementMethod']
load(lipd, parallel=False)[source]

Extract Variables from the LiPD object.

Parameters:

lipd (LiPD) – A LiPD object

Examples

from pylipd.lipd_series import LiPDSeries

lipd = LiPD()
lipd.load(["https://lipdverse.org/data/LCf20b99dfe8d78840ca60dfb1f832b9ec/1_0_1//Nunalleq.Ledger.2018.lpd"])
lipd_series = lipd.to_lipd_series()
Loading 1 LiPD files
Loaded..
Creating LiPD Series...
- Extracting dataset subgraphs
- Extracting variable subgraphs
Done..

LiPD Classes

class pylipd.classes.dataset.Dataset[source]

Methods

addChronData

addCreator

addFunding

addInvestigator

addPaleoData

addPublication

add_non_standard_property

from_data

from_json

getArchiveType

getChangeLog

getChronData

getCollectionName

getCollectionYear

getCompilationNest

getContributor

getCreators

getDataSource

getDatasetId

getFundings

getInvestigators

getLocation

getName

getNotes

getOriginalDataUrl

getPaleoData

getPublications

getSpreadsheetLink

getVersion

get_all_non_standard_properties

get_non_standard_property

setArchiveType

setChangeLog

setChronData

setCollectionName

setCollectionYear

setCompilationNest

setContributor

setCreators

setDataSource

setDatasetId

setFundings

setInvestigators

setLocation

setName

setNotes

setOriginalDataUrl

setPaleoData

setPublications

setSpreadsheetLink

setVersion

set_non_standard_property

to_data

to_json

addChronData(chronData: ChronData)[source]
addCreator(creators: Person)[source]
addFunding(fundings: Funding)[source]
addInvestigator(investigators: Person)[source]
addPaleoData(paleoData: PaleoData)[source]
addPublication(publications: Publication)[source]
add_non_standard_property(key, value)[source]
static from_data(id, data) Dataset[source]
static from_json(data) Dataset[source]
getArchiveType() ArchiveType[source]
getChangeLog() ChangeLog[source]
getChronData() list[ChronData][source]
getCollectionName() str[source]
getCollectionYear() str[source]
getCompilationNest() str[source]
getContributor() Person[source]
getCreators() list[Person][source]
getDataSource() str[source]
getDatasetId() str[source]
getFundings() list[Funding][source]
getInvestigators() list[Person][source]
getLocation() Location[source]
getName() str[source]
getNotes() str[source]
getOriginalDataUrl() str[source]
getPaleoData() list[PaleoData][source]
getPublications() list[Publication][source]
getVersion() str[source]
get_all_non_standard_properties()[source]
get_non_standard_property(key)[source]
setArchiveType(archiveType: ArchiveType)[source]
setChangeLog(changeLog: ChangeLog)[source]
setChronData(chronData: list[ChronData])[source]
setCollectionName(collectionName: str)[source]
setCollectionYear(collectionYear: str)[source]
setCompilationNest(compilationNest: str)[source]
setContributor(contributor: Person)[source]
setCreators(creators: list[Person])[source]
setDataSource(dataSource: str)[source]
setDatasetId(datasetId: str)[source]
setFundings(fundings: list[Funding])[source]
setInvestigators(investigators: list[Person])[source]
setLocation(location: Location)[source]
setName(name: str)[source]
setNotes(notes: str)[source]
setOriginalDataUrl(originalDataUrl: str)[source]
setPaleoData(paleoData: list[PaleoData])[source]
setPublications(publications: list[Publication])[source]
setVersion(version: str)[source]
set_non_standard_property(key, value)[source]
to_data(data={})[source]
to_json()[source]
class pylipd.classes.paleodata.PaleoData[source]

Methods

addMeasurementTable

addModeledBy

add_non_standard_property

from_data

from_json

getMeasurementTables

getModeledBy

getName

get_all_non_standard_properties

get_non_standard_property

setMeasurementTables

setModeledBy

setName

set_non_standard_property

to_data

to_json

addMeasurementTable(measurementTables: DataTable)[source]
addModeledBy(modeledBy: Model)[source]
add_non_standard_property(key, value)[source]
static from_data(id, data) PaleoData[source]
static from_json(data) PaleoData[source]
getMeasurementTables() list[DataTable][source]
getModeledBy() list[Model][source]
getName() str[source]
get_all_non_standard_properties()[source]
get_non_standard_property(key)[source]
setMeasurementTables(measurementTables: list[DataTable])[source]
setModeledBy(modeledBy: list[Model])[source]
setName(name: str)[source]
set_non_standard_property(key, value)[source]
to_data(data={})[source]
to_json()[source]
class pylipd.classes.chrondata.ChronData[source]

Methods

addMeasurementTable

addModeledBy

add_non_standard_property

from_data

from_json

getMeasurementTables

getModeledBy

get_all_non_standard_properties

get_non_standard_property

setMeasurementTables

setModeledBy

set_non_standard_property

to_data

to_json

addMeasurementTable(measurementTables: DataTable)[source]
addModeledBy(modeledBy: Model)[source]
add_non_standard_property(key, value)[source]
static from_data(id, data) ChronData[source]
static from_json(data) ChronData[source]
getMeasurementTables() list[DataTable][source]
getModeledBy() list[Model][source]
get_all_non_standard_properties()[source]
get_non_standard_property(key)[source]
setMeasurementTables(measurementTables: list[DataTable])[source]
setModeledBy(modeledBy: list[Model])[source]
set_non_standard_property(key, value)[source]
to_data(data={})[source]
to_json()[source]
class pylipd.classes.datatable.DataTable[source]

Methods

getDataFrame([use_standard_names])

addVariable

add_non_standard_property

from_data

from_json

getFileName

getMissingValue

getVariables

get_all_non_standard_properties

get_non_standard_property

setDataFrame

setFileName

setMissingValue

setVariables

set_non_standard_property

to_data

to_json

addVariable(variables: Variable)[source]
add_non_standard_property(key, value)[source]
static from_data(id, data) DataTable[source]
static from_json(data) DataTable[source]
getDataFrame(use_standard_names=False) DataFrame[source]
getFileName() str[source]
getMissingValue() str[source]
getVariables() list[Variable][source]
get_all_non_standard_properties()[source]
get_non_standard_property(key)[source]
setDataFrame(df: DataFrame)[source]
setFileName(fileName: str)[source]
setMissingValue(missingValue: str)[source]
setVariables(variables: list[Variable])[source]
set_non_standard_property(key, value)[source]
to_data(data={})[source]
to_json()[source]
class pylipd.classes.variable.Variable[source]

Methods

addCalibratedVia

addInterpretation

add_non_standard_property

from_data

from_json

getArchiveType

getCalibratedVias

getColumnNumber

getDescription

getFoundInDataset

getFoundInTable

getInstrument

getInterpretations

getMaxValue

getMeanValue

getMedianValue

getMinValue

getMissingValue

getName

getNotes

getPartOfCompilation

getPhysicalSample

getProxy

getProxyGeneral

getResolution

getStandardVariable

getUncertainty

getUncertaintyAnalytical

getUncertaintyReproducibility

getUnits

getValues

getVariableId

getVariableType

get_all_non_standard_properties

get_non_standard_property

isComposite

isPrimary

setArchiveType

setCalibratedVias

setColumnNumber

setComposite

setDescription

setFoundInDataset

setFoundInTable

setInstrument

setInterpretations

setMaxValue

setMeanValue

setMedianValue

setMinValue

setMissingValue

setName

setNotes

setPartOfCompilation

setPhysicalSample

setPrimary

setProxy

setProxyGeneral

setResolution

setStandardVariable

setUncertainty

setUncertaintyAnalytical

setUncertaintyReproducibility

setUnits

setValues

setVariableId

setVariableType

set_non_standard_property

to_data

to_json

addCalibratedVia(calibratedVias: Calibration)[source]
addInterpretation(interpretations: Interpretation)[source]
add_non_standard_property(key, value)[source]
static from_data(id, data) Variable[source]
static from_json(data) Variable[source]
getArchiveType() ArchiveType[source]
getCalibratedVias() list[Calibration][source]
getColumnNumber() int[source]
getDescription() str[source]
getFoundInDataset() None[source]
getFoundInTable() None[source]
getInstrument() None[source]
getInterpretations() list[Interpretation][source]
getMaxValue() float[source]
getMeanValue() float[source]
getMedianValue() float[source]
getMinValue() float[source]
getMissingValue() str[source]
getName() str[source]
getNotes() str[source]
getPartOfCompilation() Compilation[source]
getPhysicalSample() None[source]
getProxy() PaleoProxy[source]
getProxyGeneral() PaleoProxyGeneral[source]
getResolution() Resolution[source]
getStandardVariable() PaleoVariable[source]
getUncertainty() str[source]
getUncertaintyAnalytical() str[source]
getUncertaintyReproducibility() str[source]
getUnits() PaleoUnit[source]
getValues() str[source]
getVariableId() str[source]
getVariableType() str[source]
get_all_non_standard_properties()[source]
get_non_standard_property(key)[source]
isComposite() bool[source]
isPrimary() bool[source]
setArchiveType(archiveType: ArchiveType)[source]
setCalibratedVias(calibratedVias: list[Calibration])[source]
setColumnNumber(columnNumber: int)[source]
setComposite(composite: bool)[source]
setDescription(description: str)[source]
setFoundInDataset(foundInDataset: None)[source]
setFoundInTable(foundInTable: None)[source]
setInstrument(instrument: None)[source]
setInterpretations(interpretations: list[Interpretation])[source]
setMaxValue(maxValue: float)[source]
setMeanValue(meanValue: float)[source]
setMedianValue(medianValue: float)[source]
setMinValue(minValue: float)[source]
setMissingValue(missingValue: str)[source]
setName(name: str)[source]
setNotes(notes: str)[source]
setPartOfCompilation(partOfCompilation: Compilation)[source]
setPhysicalSample(physicalSample: None)[source]
setPrimary(primary: bool)[source]
setProxy(proxy: PaleoProxy)[source]
setProxyGeneral(proxyGeneral: PaleoProxyGeneral)[source]
setResolution(resolution: Resolution)[source]
setStandardVariable(standardVariable: PaleoVariable)[source]
setUncertainty(uncertainty: str)[source]
setUncertaintyAnalytical(uncertaintyAnalytical: str)[source]
setUncertaintyReproducibility(uncertaintyReproducibility: str)[source]
setUnits(units: PaleoUnit)[source]
setValues(values: str)[source]
setVariableId(variableId: str)[source]
setVariableType(variableType: str)[source]
set_non_standard_property(key, value)[source]
to_data(data={})[source]
to_json()[source]
class pylipd.classes.calibration.Calibration[source]

Methods

add_non_standard_property

from_data

from_json

getDOI

getDatasetRange

getEquation

getEquationIntercept

getEquationR2

getEquationSlope

getEquationSlopeUncertainty

getMethod

getMethodDetail

getNotes

getProxyDataset

getSeasonality

getTargetDataset

getUncertainty

get_all_non_standard_properties

get_non_standard_property

setDOI

setDatasetRange

setEquation

setEquationIntercept

setEquationR2

setEquationSlope

setEquationSlopeUncertainty

setMethod

setMethodDetail

setNotes

setProxyDataset

setSeasonality

setTargetDataset

setUncertainty

set_non_standard_property

to_data

to_json

add_non_standard_property(key, value)[source]
static from_data(id, data) Calibration[source]
static from_json(data) Calibration[source]
getDOI() str[source]
getDatasetRange() str[source]
getEquation() str[source]
getEquationIntercept() str[source]
getEquationR2() str[source]
getEquationSlope() str[source]
getEquationSlopeUncertainty() str[source]
getMethod() str[source]
getMethodDetail() str[source]
getNotes() str[source]
getProxyDataset() str[source]
getSeasonality() str[source]
getTargetDataset() str[source]
getUncertainty() str[source]
get_all_non_standard_properties()[source]
get_non_standard_property(key)[source]
setDOI(dOI: str)[source]
setDatasetRange(datasetRange: str)[source]
setEquation(equation: str)[source]
setEquationIntercept(equationIntercept: str)[source]
setEquationR2(equationR2: str)[source]
setEquationSlope(equationSlope: str)[source]
setEquationSlopeUncertainty(equationSlopeUncertainty: str)[source]
setMethod(method: str)[source]
setMethodDetail(methodDetail: str)[source]
setNotes(notes: str)[source]
setProxyDataset(proxyDataset: str)[source]
setSeasonality(seasonality: str)[source]
setTargetDataset(targetDataset: str)[source]
setUncertainty(uncertainty: str)[source]
set_non_standard_property(key, value)[source]
to_data(data={})[source]
to_json()[source]
class pylipd.classes.uncertainty.Uncertainty[source]

Methods

add_non_standard_property

from_data

from_json

getUncertaintyType

get_all_non_standard_properties

get_non_standard_property

setUncertaintyType

set_non_standard_property

to_data

to_json

add_non_standard_property(key, value)[source]
static from_data(id, data) Uncertainty[source]
static from_json(data) Uncertainty[source]
getUncertaintyType() str[source]
get_all_non_standard_properties()[source]
get_non_standard_property(key)[source]
setUncertaintyType(uncertaintyType: str)[source]
set_non_standard_property(key, value)[source]
to_data(data={})[source]
to_json()[source]
class pylipd.classes.interpretation.Interpretation[source]

Methods

add_non_standard_property

from_data

from_json

getBasis

getDirection

getMathematicalRelation

getNotes

getRank

getScope

getSeasonality

getSeasonalityGeneral

getSeasonalityOriginal

getVariable

getVariableDetail

getVariableGeneral

getVariableGeneralDirection

get_all_non_standard_properties

get_non_standard_property

isLocal

setBasis

setDirection

setLocal

setMathematicalRelation

setNotes

setRank

setScope

setSeasonality

setSeasonalityGeneral

setSeasonalityOriginal

setVariable

setVariableDetail

setVariableGeneral

setVariableGeneralDirection

set_non_standard_property

to_data

to_json

add_non_standard_property(key, value)[source]
static from_data(id, data) Interpretation[source]
static from_json(data) Interpretation[source]
getBasis() str[source]
getDirection() str[source]
getMathematicalRelation() str[source]
getNotes() str[source]
getRank() str[source]
getScope() str[source]
getSeasonality() InterpretationSeasonality[source]
getSeasonalityGeneral() InterpretationSeasonality[source]
getSeasonalityOriginal() InterpretationSeasonality[source]
getVariable() InterpretationVariable[source]
getVariableDetail() str[source]
getVariableGeneral() str[source]
getVariableGeneralDirection() str[source]
get_all_non_standard_properties()[source]
get_non_standard_property(key)[source]
isLocal() str[source]
setBasis(basis: str)[source]
setDirection(direction: str)[source]
setLocal(local: str)[source]
setMathematicalRelation(mathematicalRelation: str)[source]
setNotes(notes: str)[source]
setRank(rank: str)[source]
setScope(scope: str)[source]
setSeasonality(seasonality: InterpretationSeasonality)[source]
setSeasonalityGeneral(seasonalityGeneral: InterpretationSeasonality)[source]
setSeasonalityOriginal(seasonalityOriginal: InterpretationSeasonality)[source]
setVariable(variable: InterpretationVariable)[source]
setVariableDetail(variableDetail: str)[source]
setVariableGeneral(variableGeneral: str)[source]
setVariableGeneralDirection(variableGeneralDirection: str)[source]
set_non_standard_property(key, value)[source]
to_data(data={})[source]
to_json()[source]
class pylipd.classes.changelog.ChangeLog[source]

Methods

add_non_standard_property

from_data

from_json

getChanges

getNotes

get_all_non_standard_properties

get_non_standard_property

setChanges

setNotes

set_non_standard_property

to_data

to_json

add_non_standard_property(key, value)[source]
static from_data(id, data) ChangeLog[source]
static from_json(data) ChangeLog[source]
getChanges() None[source]
getNotes() str[source]
get_all_non_standard_properties()[source]
get_non_standard_property(key)[source]
setChanges(changes: None)[source]
setNotes(notes: str)[source]
set_non_standard_property(key, value)[source]
to_data(data={})[source]
to_json()[source]
class pylipd.classes.funding.Funding[source]

Methods

addGrant

addInvestigator

add_non_standard_property

from_data

from_json

getFundingAgency

getFundingCountry

getGrants

getInvestigators

get_all_non_standard_properties

get_non_standard_property

setFundingAgency

setFundingCountry

setGrants

setInvestigators

set_non_standard_property

to_data

to_json

addGrant(grants: str)[source]
addInvestigator(investigators: Person)[source]
add_non_standard_property(key, value)[source]
static from_data(id, data) Funding[source]
static from_json(data) Funding[source]
getFundingAgency() str[source]
getFundingCountry() str[source]
getGrants() list[str][source]
getInvestigators() list[Person][source]
get_all_non_standard_properties()[source]
get_non_standard_property(key)[source]
setFundingAgency(fundingAgency: str)[source]
setFundingCountry(fundingCountry: str)[source]
setGrants(grants: list[str])[source]
setInvestigators(investigators: list[Person])[source]
set_non_standard_property(key, value)[source]
to_data(data={})[source]
to_json()[source]
class pylipd.classes.location.Location[source]

Methods

add_non_standard_property

from_data

from_json

getContinent

getCoordinates

getCoordinatesFor

getCountry

getCountryOcean

getDescription

getElevation

getGeometryType

getLatitude

getLocationName

getLocationType

getLongitude

getNotes

getOcean

getSiteName

get_all_non_standard_properties

get_non_standard_property

setContinent

setCoordinates

setCoordinatesFor

setCountry

setCountryOcean

setDescription

setElevation

setGeometryType

setLatitude

setLocationName

setLocationType

setLongitude

setNotes

setOcean

setSiteName

set_non_standard_property

to_data

to_json

add_non_standard_property(key, value)[source]
static from_data(id, data) Location[source]
static from_json(data) Location[source]
getContinent() str[source]
getCoordinates() str[source]
getCoordinatesFor() None[source]
getCountry() str[source]
getCountryOcean() str[source]
getDescription() str[source]
getElevation() str[source]
getGeometryType() str[source]
getLatitude() str[source]
getLocationName() str[source]
getLocationType() str[source]
getLongitude() str[source]
getNotes() str[source]
getOcean() str[source]
getSiteName() str[source]
get_all_non_standard_properties()[source]
get_non_standard_property(key)[source]
setContinent(continent: str)[source]
setCoordinates(coordinates: str)[source]
setCoordinatesFor(coordinatesFor: None)[source]
setCountry(country: str)[source]
setCountryOcean(countryOcean: str)[source]
setDescription(description: str)[source]
setElevation(elevation: str)[source]
setGeometryType(geometryType: str)[source]
setLatitude(latitude: str)[source]
setLocationName(locationName: str)[source]
setLocationType(locationType: str)[source]
setLongitude(longitude: str)[source]
setNotes(notes: str)[source]
setOcean(ocean: str)[source]
setSiteName(siteName: str)[source]
set_non_standard_property(key, value)[source]
to_data(data={})[source]
to_json()[source]
class pylipd.classes.model.Model[source]

Methods

addDistributionTable

addEnsembleTable

addSummaryTable

add_non_standard_property

from_data

from_json

getCode

getDistributionTables

getEnsembleTables

getSummaryTables

get_all_non_standard_properties

get_non_standard_property

setCode

setDistributionTables

setEnsembleTables

setSummaryTables

set_non_standard_property

to_data

to_json

addDistributionTable(distributionTables: DataTable)[source]
addEnsembleTable(ensembleTables: DataTable)[source]
addSummaryTable(summaryTables: DataTable)[source]
add_non_standard_property(key, value)[source]
static from_data(id, data) Model[source]
static from_json(data) Model[source]
getCode() str[source]
getDistributionTables() list[DataTable][source]
getEnsembleTables() list[DataTable][source]
getSummaryTables() list[DataTable][source]
get_all_non_standard_properties()[source]
get_non_standard_property(key)[source]
setCode(code: str)[source]
setDistributionTables(distributionTables: list[DataTable])[source]
setEnsembleTables(ensembleTables: list[DataTable])[source]
setSummaryTables(summaryTables: list[DataTable])[source]
set_non_standard_property(key, value)[source]
to_data(data={})[source]
to_json()[source]
class pylipd.classes.publication.Publication[source]

Methods

addAuthor

addDataUrl

addUrl

add_non_standard_property

from_data

from_json

getAbstract

getAuthors

getCitation

getCiteKey

getDOI

getDataUrls

getFirstAuthor

getInstitution

getIssue

getJournal

getPages

getPublicationType

getPublisher

getReport

getTitle

getUrls

getVolume

getYear

get_all_non_standard_properties

get_non_standard_property

setAbstract

setAuthors

setCitation

setCiteKey

setDOI

setDataUrls

setFirstAuthor

setInstitution

setIssue

setJournal

setPages

setPublicationType

setPublisher

setReport

setTitle

setUrls

setVolume

setYear

set_non_standard_property

to_data

to_json

addAuthor(authors: Person)[source]
addDataUrl(dataUrls: str)[source]
addUrl(urls: str)[source]
add_non_standard_property(key, value)[source]
static from_data(id, data) Publication[source]
static from_json(data) Publication[source]
getAbstract() str[source]
getAuthors() list[Person][source]
getCitation() str[source]
getCiteKey() str[source]
getDOI() str[source]
getDataUrls() list[str][source]
getFirstAuthor() Person[source]
getInstitution() str[source]
getIssue() str[source]
getJournal() str[source]
getPages() str[source]
getPublicationType() str[source]
getPublisher() str[source]
getReport() str[source]
getTitle() str[source]
getUrls() list[str][source]
getVolume() str[source]
getYear() int[source]
get_all_non_standard_properties()[source]
get_non_standard_property(key)[source]
setAbstract(abstract: str)[source]
setAuthors(authors: list[Person])[source]
setCitation(citation: str)[source]
setCiteKey(citeKey: str)[source]
setDOI(dOI: str)[source]
setDataUrls(dataUrls: list[str])[source]
setFirstAuthor(firstAuthor: Person)[source]
setInstitution(institution: str)[source]
setIssue(issue: str)[source]
setJournal(journal: str)[source]
setPages(pages: str)[source]
setPublicationType(publicationType: str)[source]
setPublisher(publisher: str)[source]
setReport(report: str)[source]
setTitle(title: str)[source]
setUrls(urls: list[str])[source]
setVolume(volume: str)[source]
setYear(year: int)[source]
set_non_standard_property(key, value)[source]
to_data(data={})[source]
to_json()[source]
class pylipd.classes.resolution.Resolution[source]

Methods

add_non_standard_property

from_data

from_json

getMaxValue

getMeanValue

getMedianValue

getMinValue

getUnits

get_all_non_standard_properties

get_non_standard_property

setMaxValue

setMeanValue

setMedianValue

setMinValue

setUnits

set_non_standard_property

to_data

to_json

add_non_standard_property(key, value)[source]
static from_data(id, data) Resolution[source]
static from_json(data) Resolution[source]
getMaxValue() float[source]
getMeanValue() float[source]
getMedianValue() float[source]
getMinValue() float[source]
getUnits() PaleoUnit[source]
get_all_non_standard_properties()[source]
get_non_standard_property(key)[source]
setMaxValue(maxValue: float)[source]
setMeanValue(meanValue: float)[source]
setMedianValue(medianValue: float)[source]
setMinValue(minValue: float)[source]
setUnits(units: PaleoUnit)[source]
set_non_standard_property(key, value)[source]
to_data(data={})[source]
to_json()[source]
class pylipd.classes.physicalsample.PhysicalSample[source]

Methods

add_non_standard_property

from_data

from_json

getHousedAt

getIGSN

getName

get_all_non_standard_properties

get_non_standard_property

setHousedAt

setIGSN

setName

set_non_standard_property

to_data

to_json

add_non_standard_property(key, value)[source]
static from_data(id, data) PhysicalSample[source]
static from_json(data) PhysicalSample[source]
getHousedAt() str[source]
getIGSN() str[source]
getName() str[source]
get_all_non_standard_properties()[source]
get_non_standard_property(key)[source]
setHousedAt(housedAt: str)[source]
setIGSN(iGSN: str)[source]
setName(name: str)[source]
set_non_standard_property(key, value)[source]
to_data(data={})[source]
to_json()[source]
class pylipd.classes.publication.Person[source]

Methods

add_non_standard_property

from_data

from_json

getName

get_all_non_standard_properties

get_non_standard_property

setName

set_non_standard_property

to_data

to_json

add_non_standard_property(key, value)[source]
static from_data(id, data) Person[source]
static from_json(data) Person[source]
getName() str[source]
get_all_non_standard_properties()[source]
get_non_standard_property(key)[source]
setName(name: str)[source]
set_non_standard_property(key, value)[source]
to_data(data={})[source]
to_json()[source]

LiPD Controlled Vocabulary

class pylipd.classes.archivetype.ArchiveType(id, label)[source]

Methods

from_synonym

getId

getLabel

to_data

to_json

classmethod from_synonym(synonym)[source]
getId()[source]
getLabel()[source]
synonyms = {'bivalve': {'id': 'http://linked.earth/ontology/archive#MolluskShell', 'label': 'Mollusk shell'}, 'bog': {'id': 'http://linked.earth/ontology/archive#Peat', 'label': 'Peat'}, 'borehole': {'id': 'http://linked.earth/ontology/archive#Borehole', 'label': 'Borehole'}, 'bulk ice': {'id': 'http://linked.earth/ontology/archive#GroundIce', 'label': 'Ground ice'}, 'cave': {'id': 'http://linked.earth/ontology/archive#Speleothem', 'label': 'Speleothem'}, 'coral': {'id': 'http://linked.earth/ontology/archive#Coral', 'label': 'Coral'}, 'creek': {'id': 'http://linked.earth/ontology/archive#FluvialSediment', 'label': 'Fluvial sediment'}, 'delta': {'id': 'http://linked.earth/ontology/archive#MarineSediment', 'label': 'Marine sediment'}, 'documents': {'id': 'http://linked.earth/ontology/archive#Documents', 'label': 'Documents'}, 'dune': {'id': 'http://linked.earth/ontology/archive#TerrestrialSediment', 'label': 'Terrestrial sediment'}, 'fen': {'id': 'http://linked.earth/ontology/archive#Peat', 'label': 'Peat'}, 'fluvial': {'id': 'http://linked.earth/ontology/archive#FluvialSediment', 'label': 'Fluvial sediment'}, 'fluvial sediment': {'id': 'http://linked.earth/ontology/archive#FluvialSediment', 'label': 'Fluvial sediment'}, 'fluvialsediment': {'id': 'http://linked.earth/ontology/archive#FluvialSediment', 'label': 'Fluvial sediment'}, 'glacier ice': {'id': 'http://linked.earth/ontology/archive#GlacierIce', 'label': 'Glacier ice'}, 'glacierice': {'id': 'http://linked.earth/ontology/archive#GlacierIce', 'label': 'Glacier ice'}, 'ground ice': {'id': 'http://linked.earth/ontology/archive#GroundIce', 'label': 'Ground ice'}, 'groundice': {'id': 'http://linked.earth/ontology/archive#GroundIce', 'label': 'Ground ice'}, 'ice cores': {'id': 'http://linked.earth/ontology/archive#GlacierIce', 'label': 'Glacier ice'}, 'lagoon': {'id': 'http://linked.earth/ontology/archive#LakeSediment', 'label': 'Lake sediment'}, 'lake': {'id': 'http://linked.earth/ontology/archive#LakeSediment', 'label': 'Lake sediment'}, 'lake levels': {'id': 'http://linked.earth/ontology/archive#Shoreline', 'label': 'Shoreline'}, 'lake sediment': {'id': 'http://linked.earth/ontology/archive#LakeSediment', 'label': 'Lake sediment'}, 'lakedeposit': {'id': 'http://linked.earth/ontology/archive#Shoreline', 'label': 'Shoreline'}, 'lakedeposits': {'id': 'http://linked.earth/ontology/archive#Shoreline', 'label': 'Shoreline'}, 'lakesediment': {'id': 'http://linked.earth/ontology/archive#LakeSediment', 'label': 'Lake sediment'}, 'loess': {'id': 'http://linked.earth/ontology/archive#TerrestrialSediment', 'label': 'Terrestrial sediment'}, 'marine': {'id': 'http://linked.earth/ontology/archive#MarineSediment', 'label': 'Marine sediment'}, 'marine sediment': {'id': 'http://linked.earth/ontology/archive#MarineSediment', 'label': 'Marine sediment'}, 'marinesediment': {'id': 'http://linked.earth/ontology/archive#MarineSediment', 'label': 'Marine sediment'}, 'marsh': {'id': 'http://linked.earth/ontology/archive#Peat', 'label': 'Peat'}, 'midden': {'id': 'http://linked.earth/ontology/archive#Midden', 'label': 'Midden'}, 'mire': {'id': 'http://linked.earth/ontology/archive#Peat', 'label': 'Peat'}, 'mollusk shell': {'id': 'http://linked.earth/ontology/archive#MolluskShell', 'label': 'Mollusk shell'}, 'molluskshell': {'id': 'http://linked.earth/ontology/archive#MolluskShell', 'label': 'Mollusk shell'}, 'molluskshells': {'id': 'http://linked.earth/ontology/archive#MolluskShell', 'label': 'Mollusk shell'}, 'other': {'id': 'http://linked.earth/ontology/archive#Other', 'label': 'Other'}, 'peat': {'id': 'http://linked.earth/ontology/archive#Peat', 'label': 'Peat'}, 'river': {'id': 'http://linked.earth/ontology/archive#FluvialSediment', 'label': 'Fluvial sediment'}, 'sclerosponge': {'id': 'http://linked.earth/ontology/archive#Sclerosponge', 'label': 'Sclerosponge'}, 'shoreline': {'id': 'http://linked.earth/ontology/archive#Shoreline', 'label': 'Shoreline'}, 'speleothem': {'id': 'http://linked.earth/ontology/archive#Speleothem', 'label': 'Speleothem'}, 'speleothems': {'id': 'http://linked.earth/ontology/archive#Speleothem', 'label': 'Speleothem'}, 'stream': {'id': 'http://linked.earth/ontology/archive#FluvialSediment', 'label': 'Fluvial sediment'}, 'swamp': {'id': 'http://linked.earth/ontology/archive#Peat', 'label': 'Peat'}, 'terrestrial sediment': {'id': 'http://linked.earth/ontology/archive#TerrestrialSediment', 'label': 'Terrestrial sediment'}, 'terrestrialsediment': {'id': 'http://linked.earth/ontology/archive#TerrestrialSediment', 'label': 'Terrestrial sediment'}, 'tree': {'id': 'http://linked.earth/ontology/archive#Wood', 'label': 'Wood'}, 'tree ring': {'id': 'http://linked.earth/ontology/archive#Wood', 'label': 'Wood'}, 'wood': {'id': 'http://linked.earth/ontology/archive#Wood', 'label': 'Wood'}}
to_data(data={})[source]
to_json()[source]
class pylipd.classes.archivetype.ArchiveTypeConstants[source]
Borehole = <pylipd.classes.archivetype.ArchiveType object>
Coral = <pylipd.classes.archivetype.ArchiveType object>
Documents = <pylipd.classes.archivetype.ArchiveType object>
FluvialSediment = <pylipd.classes.archivetype.ArchiveType object>
GlacierIce = <pylipd.classes.archivetype.ArchiveType object>
GroundIce = <pylipd.classes.archivetype.ArchiveType object>
LakeSediment = <pylipd.classes.archivetype.ArchiveType object>
MarineSediment = <pylipd.classes.archivetype.ArchiveType object>
Midden = <pylipd.classes.archivetype.ArchiveType object>
MolluskShell = <pylipd.classes.archivetype.ArchiveType object>
Other = <pylipd.classes.archivetype.ArchiveType object>
Peat = <pylipd.classes.archivetype.ArchiveType object>
Sclerosponge = <pylipd.classes.archivetype.ArchiveType object>
Shoreline = <pylipd.classes.archivetype.ArchiveType object>
Speleothem = <pylipd.classes.archivetype.ArchiveType object>
TerrestrialSediment = <pylipd.classes.archivetype.ArchiveType object>
Wood = <pylipd.classes.archivetype.ArchiveType object>
class pylipd.classes.paleounit.PaleoUnitConstants[source]
SI = <pylipd.classes.paleounit.PaleoUnit object>
atomic_ratio = <pylipd.classes.paleounit.PaleoUnit object>
cgs = <pylipd.classes.paleounit.PaleoUnit object>
cm = <pylipd.classes.paleounit.PaleoUnit object>
cm3 = <pylipd.classes.paleounit.PaleoUnit object>
cm_kyr = <pylipd.classes.paleounit.PaleoUnit object>
cm_yr = <pylipd.classes.paleounit.PaleoUnit object>
count = <pylipd.classes.paleounit.PaleoUnit object>
count_century = <pylipd.classes.paleounit.PaleoUnit object>
count_cm2 = <pylipd.classes.paleounit.PaleoUnit object>
count_cm2_yr = <pylipd.classes.paleounit.PaleoUnit object>
count_cm3 = <pylipd.classes.paleounit.PaleoUnit object>
count_g = <pylipd.classes.paleounit.PaleoUnit object>
count_kyr = <pylipd.classes.paleounit.PaleoUnit object>
count_mL = <pylipd.classes.paleounit.PaleoUnit object>
count_yr = <pylipd.classes.paleounit.PaleoUnit object>
cps = <pylipd.classes.paleounit.PaleoUnit object>
day = <pylipd.classes.paleounit.PaleoUnit object>
degC = <pylipd.classes.paleounit.PaleoUnit object>
degree = <pylipd.classes.paleounit.PaleoUnit object>
fraction = <pylipd.classes.paleounit.PaleoUnit object>
g = <pylipd.classes.paleounit.PaleoUnit object>
g_L = <pylipd.classes.paleounit.PaleoUnit object>
g_cm2 = <pylipd.classes.paleounit.PaleoUnit object>
g_cm2_kyr = <pylipd.classes.paleounit.PaleoUnit object>
g_cm2_yr = <pylipd.classes.paleounit.PaleoUnit object>
g_cm3 = <pylipd.classes.paleounit.PaleoUnit object>
g_cm_yr = <pylipd.classes.paleounit.PaleoUnit object>
g_m2 = <pylipd.classes.paleounit.PaleoUnit object>
g_m2_yr = <pylipd.classes.paleounit.PaleoUnit object>
grayscale = <pylipd.classes.paleounit.PaleoUnit object>
kg_m2_yr = <pylipd.classes.paleounit.PaleoUnit object>
kg_m3 = <pylipd.classes.paleounit.PaleoUnit object>
km2 = <pylipd.classes.paleounit.PaleoUnit object>
km3 = <pylipd.classes.paleounit.PaleoUnit object>
log_mg_L_ = <pylipd.classes.paleounit.PaleoUnit object>
m = <pylipd.classes.paleounit.PaleoUnit object>
m3_kg = <pylipd.classes.paleounit.PaleoUnit object>
mg = <pylipd.classes.paleounit.PaleoUnit object>
mg_L = <pylipd.classes.paleounit.PaleoUnit object>
mg_cm2_yr = <pylipd.classes.paleounit.PaleoUnit object>
mg_g = <pylipd.classes.paleounit.PaleoUnit object>
mg_kg = <pylipd.classes.paleounit.PaleoUnit object>
mm = <pylipd.classes.paleounit.PaleoUnit object>
mm_day = <pylipd.classes.paleounit.PaleoUnit object>
mm_season = <pylipd.classes.paleounit.PaleoUnit object>
mm_yr = <pylipd.classes.paleounit.PaleoUnit object>
mmol_mol = <pylipd.classes.paleounit.PaleoUnit object>
months_year = <pylipd.classes.paleounit.PaleoUnit object>
needsToBeChanged = <pylipd.classes.paleounit.PaleoUnit object>
ng = <pylipd.classes.paleounit.PaleoUnit object>
ng_g = <pylipd.classes.paleounit.PaleoUnit object>
pH = <pylipd.classes.paleounit.PaleoUnit object>
peak_area = <pylipd.classes.paleounit.PaleoUnit object>
percent = <pylipd.classes.paleounit.PaleoUnit object>
permil = <pylipd.classes.paleounit.PaleoUnit object>
ppb = <pylipd.classes.paleounit.PaleoUnit object>
ppm = <pylipd.classes.paleounit.PaleoUnit object>
practical_salinity_unit = <pylipd.classes.paleounit.PaleoUnit object>
ratio = <pylipd.classes.paleounit.PaleoUnit object>
ug_cm2_yr = <pylipd.classes.paleounit.PaleoUnit object>
ug_g = <pylipd.classes.paleounit.PaleoUnit object>
um = <pylipd.classes.paleounit.PaleoUnit object>
umol_mol = <pylipd.classes.paleounit.PaleoUnit object>
unitless = <pylipd.classes.paleounit.PaleoUnit object>
yr_14C_BP = <pylipd.classes.paleounit.PaleoUnit object>
yr_AD = <pylipd.classes.paleounit.PaleoUnit object>
yr_BP = <pylipd.classes.paleounit.PaleoUnit object>
yr_b2k = <pylipd.classes.paleounit.PaleoUnit object>
yr_ka = <pylipd.classes.paleounit.PaleoUnit object>
z_score = <pylipd.classes.paleounit.PaleoUnit object>
class pylipd.classes.paleoproxy.PaleoProxy(id, label)[source]

Methods

from_synonym

getId

getLabel

to_data

to_json

classmethod from_synonym(synonym)[source]
getId()[source]
getLabel()[source]
synonyms = {'((( calcium carbonate ))) accumulation /// null': {'id': 'http://linked.earth/ontology/paleo_proxy#needsToBeChanged', 'label': 'needsToBeChanged'}, '15n/40ar fractionation': {'id': 'http://linked.earth/ontology/paleo_proxy#d15N_d40Ar', 'label': 'd15N/d40Ar'}, '3-oh-fatty acids': {'id': 'http://linked.earth/ontology/paleo_proxy#needsToBeChanged', 'label': 'needsToBeChanged'}, 'accumulation rate': {'id': 'http://linked.earth/ontology/paleo_proxy#accumulation_rate', 'label': 'accumulation rate'}, 'accumulation_rate': {'id': 'http://linked.earth/ontology/paleo_proxy#accumulation_rate', 'label': 'accumulation rate'}, 'acl': {'id': 'http://linked.earth/ontology/paleo_proxy#ACL', 'label': 'ACL'}, 'age': {'id': 'http://linked.earth/ontology/paleo_proxy#needsToBeChanged', 'label': 'needsToBeChanged'}, 'al2o3': {'id': 'http://linked.earth/ontology/paleo_proxy#Al2O3', 'label': 'Al2O3'}, 'alkenone': {'id': 'http://linked.earth/ontology/paleo_proxy#alkenone', 'label': 'alkenone'}, 'aluminum oxide': {'id': 'http://linked.earth/ontology/paleo_proxy#Al2O3', 'label': 'Al2O3'}, 'amoeba': {'id': 'http://linked.earth/ontology/paleo_proxy#amoeba', 'label': 'amoeba'}, 'aquatic palynomorphs': {'id': 'http://linked.earth/ontology/paleo_proxy#pollen', 'label': 'pollen'}, 'arm/irm': {'id': 'http://linked.earth/ontology/paleo_proxy#magnetic', 'label': 'magnetic'}, 'authigenic carbonate': {'id': 'http://linked.earth/ontology/paleo_proxy#carbonate', 'label': 'carbonate'}, 'average chain length': {'id': 'http://linked.earth/ontology/paleo_proxy#ACL', 'label': 'ACL'}, 'ba/al': {'id': 'http://linked.earth/ontology/paleo_proxy#Ba_Al', 'label': 'Ba/Al'}, 'ba/ca': {'id': 'http://linked.earth/ontology/paleo_proxy#Ba_Ca', 'label': 'Ba/Ca'}, 'ba_al': {'id': 'http://linked.earth/ontology/paleo_proxy#Ba_Al', 'label': 'Ba/Al'}, 'ba_ca': {'id': 'http://linked.earth/ontology/paleo_proxy#Ba_Ca', 'label': 'Ba/Ca'}, 'baca': {'id': 'http://linked.earth/ontology/paleo_proxy#Ba_Ca', 'label': 'Ba/Ca'}, 'barium/aluminum': {'id': 'http://linked.earth/ontology/paleo_proxy#Ba_Al', 'label': 'Ba/Al'}, 'barium/calcium': {'id': 'http://linked.earth/ontology/paleo_proxy#Ba_Ca', 'label': 'Ba/Ca'}, 'benthic foraminifers': {'id': 'http://linked.earth/ontology/paleo_proxy#foraminifera', 'label': 'foraminifera'}, 'biogenic silica': {'id': 'http://linked.earth/ontology/paleo_proxy#BSi', 'label': 'BSi'}, 'biomarker': {'id': 'http://linked.earth/ontology/paleo_proxy#biomarker', 'label': 'biomarker'}, 'bit': {'id': 'http://linked.earth/ontology/paleo_proxy#BIT', 'label': 'BIT'}, 'bitindex': {'id': 'http://linked.earth/ontology/paleo_proxy#BIT', 'label': 'BIT'}, 'borehole': {'id': 'http://linked.earth/ontology/paleo_proxy#borehole', 'label': 'borehole'}, 'branched and isoprenoid tetraether index': {'id': 'http://linked.earth/ontology/paleo_proxy#BIT', 'label': 'BIT'}, 'brgdgt': {'id': 'http://linked.earth/ontology/paleo_proxy#GDGT', 'label': 'GDGT'}, 'bsi': {'id': 'http://linked.earth/ontology/paleo_proxy#BSi', 'label': 'BSi'}, 'bubble frequency': {'id': 'http://linked.earth/ontology/paleo_proxy#bubble_frequency', 'label': 'bubble frequency'}, 'bubble_frequency': {'id': 'http://linked.earth/ontology/paleo_proxy#bubble_frequency', 'label': 'bubble frequency'}, 'bulk density': {'id': 'http://linked.earth/ontology/paleo_proxy#bulk_density', 'label': 'bulk density'}, 'bulk sediment': {'id': 'http://linked.earth/ontology/paleo_proxy#bulk_sediment', 'label': 'bulk sediment'}, 'bulk_density': {'id': 'http://linked.earth/ontology/paleo_proxy#bulk_density', 'label': 'bulk density'}, 'bulk_sediment': {'id': 'http://linked.earth/ontology/paleo_proxy#bulk_sediment', 'label': 'bulk sediment'}, 'bulksed': {'id': 'http://linked.earth/ontology/paleo_proxy#bulk_sediment', 'label': 'bulk sediment'}, 'c/n': {'id': 'http://linked.earth/ontology/paleo_proxy#C_N', 'label': 'C/N'}, 'c15 fatty alcohols': {'id': 'http://linked.earth/ontology/paleo_proxy#biomarker', 'label': 'biomarker'}, 'c37.concentration': {'id': 'http://linked.earth/ontology/paleo_proxy#biomarker', 'label': 'biomarker'}, 'c_n': {'id': 'http://linked.earth/ontology/paleo_proxy#C_N', 'label': 'C/N'}, 'ca': {'id': 'http://linked.earth/ontology/paleo_proxy#multiproxy', 'label': 'multiproxy'}, 'ca/k': {'id': 'http://linked.earth/ontology/paleo_proxy#Ca_K', 'label': 'Ca/K'}, 'ca/sr': {'id': 'http://linked.earth/ontology/paleo_proxy#Sr_Ca', 'label': 'Sr/Ca'}, 'ca/ti': {'id': 'http://linked.earth/ontology/paleo_proxy#Ca_Ti', 'label': 'Ca/Ti'}, 'ca_k': {'id': 'http://linked.earth/ontology/paleo_proxy#Ca_K', 'label': 'Ca/K'}, 'ca_ti': {'id': 'http://linked.earth/ontology/paleo_proxy#Ca_Ti', 'label': 'Ca/Ti'}, 'caco3': {'id': 'http://linked.earth/ontology/paleo_proxy#CaCO3', 'label': 'CaCO3'}, 'calcification': {'id': 'http://linked.earth/ontology/paleo_proxy#calcification_rate', 'label': 'calcification rate'}, 'calcification rate': {'id': 'http://linked.earth/ontology/paleo_proxy#calcification_rate', 'label': 'calcification rate'}, 'calcification_rate': {'id': 'http://linked.earth/ontology/paleo_proxy#calcification_rate', 'label': 'calcification rate'}, 'calcite': {'id': 'http://linked.earth/ontology/paleo_proxy#calcite', 'label': 'calcite'}, 'calcium carbonate': {'id': 'http://linked.earth/ontology/paleo_proxy#CaCO3', 'label': 'CaCO3'}, 'calcium/potassium': {'id': 'http://linked.earth/ontology/paleo_proxy#Ca_K', 'label': 'Ca/K'}, 'calcium/titanium': {'id': 'http://linked.earth/ontology/paleo_proxy#Ca_Ti', 'label': 'Ca/Ti'}, 'carbon/nitrogen': {'id': 'http://linked.earth/ontology/paleo_proxy#C_N', 'label': 'C/N'}, 'carbonate': {'id': 'http://linked.earth/ontology/paleo_proxy#carbonate', 'label': 'carbonate'}, 'carbonate content': {'id': 'http://linked.earth/ontology/paleo_proxy#carbonate', 'label': 'carbonate'}, 'cas': {'id': 'http://linked.earth/ontology/paleo_proxy#needsToBeChanged', 'label': 'needsToBeChanged'}, 'cellulose': {'id': 'http://linked.earth/ontology/paleo_proxy#cellulose', 'label': 'cellulose'}, 'cellulose d18o': {'id': 'http://linked.earth/ontology/paleo_proxy#d18O', 'label': 'd18O'}, 'charcoal': {'id': 'http://linked.earth/ontology/paleo_proxy#charcoal', 'label': 'charcoal'}, 'chironomid': {'id': 'http://linked.earth/ontology/paleo_proxy#chironomid', 'label': 'chironomid'}, 'chlorophyll': {'id': 'http://linked.earth/ontology/paleo_proxy#chlorophyll', 'label': 'chlorophyll'}, 'chrysophyte': {'id': 'http://linked.earth/ontology/paleo_proxy#chrysophyte_assemblage', 'label': 'chrysophyte assemblage'}, 'chrysophyte assemblage': {'id': 'http://linked.earth/ontology/paleo_proxy#chrysophyte_assemblage', 'label': 'chrysophyte assemblage'}, 'chrysophyte_assemblage': {'id': 'http://linked.earth/ontology/paleo_proxy#chrysophyte_assemblage', 'label': 'chrysophyte assemblage'}, 'cia': {'id': 'http://linked.earth/ontology/paleo_proxy#needsToBeChanged', 'label': 'needsToBeChanged'}, 'cladocera': {'id': 'http://linked.earth/ontology/paleo_proxy#cladoceran', 'label': 'cladoceran'}, 'cladoceran': {'id': 'http://linked.earth/ontology/paleo_proxy#cladoceran', 'label': 'cladoceran'}, 'coccolith': {'id': 'http://linked.earth/ontology/paleo_proxy#coccolithophore', 'label': 'coccolithophore'}, 'coccolithophore': {'id': 'http://linked.earth/ontology/paleo_proxy#coccolithophore', 'label': 'coccolithophore'}, 'coral': {'id': 'http://linked.earth/ontology/paleo_proxy#needsToBeChanged', 'label': 'needsToBeChanged'}, 'coral sr/ca': {'id': 'http://linked.earth/ontology/paleo_proxy#Sr_Ca', 'label': 'Sr/Ca'}, 'd13c': {'id': 'http://linked.earth/ontology/paleo_proxy#d13C', 'label': 'd13C'}, 'd13cwax': {'id': 'http://linked.earth/ontology/paleo_proxy#d13C', 'label': 'd13C'}, 'd15n': {'id': 'http://linked.earth/ontology/paleo_proxy#d15N', 'label': 'd15N'}, 'd15n/d40ar': {'id': 'http://linked.earth/ontology/paleo_proxy#d15N_d40Ar', 'label': 'd15N/d40Ar'}, 'd15n_d40ar': {'id': 'http://linked.earth/ontology/paleo_proxy#d15N_d40Ar', 'label': 'd15N/d40Ar'}, 'd15nd40ar': {'id': 'http://linked.earth/ontology/paleo_proxy#d15N_d40Ar', 'label': 'd15N/d40Ar'}, 'd18o': {'id': 'http://linked.earth/ontology/paleo_proxy#d18O', 'label': 'd18O'}, 'd2h': {'id': 'http://linked.earth/ontology/paleo_proxy#dD', 'label': 'dD'}, 'dbd': {'id': 'http://linked.earth/ontology/paleo_proxy#dry_bulk_density', 'label': 'dry bulk density'}, 'dd': {'id': 'http://linked.earth/ontology/paleo_proxy#dD', 'label': 'dD'}, 'ddwax': {'id': 'http://linked.earth/ontology/paleo_proxy#dD', 'label': 'dD'}, 'delta 13c': {'id': 'http://linked.earth/ontology/paleo_proxy#d13C', 'label': 'd13C'}, 'delta 15n': {'id': 'http://linked.earth/ontology/paleo_proxy#d15N', 'label': 'd15N'}, 'delta 18o': {'id': 'http://linked.earth/ontology/paleo_proxy#d18O', 'label': 'd18O'}, 'delta 2h': {'id': 'http://linked.earth/ontology/paleo_proxy#dD', 'label': 'dD'}, 'delta density': {'id': 'http://linked.earth/ontology/paleo_proxy#maximum_latewood_density', 'label': 'maximum latewood density'}, 'delta18o': {'id': 'http://linked.earth/ontology/paleo_proxy#d18O', 'label': 'd18O'}, 'deterium excess': {'id': 'http://linked.earth/ontology/paleo_proxy#deuterium_excess', 'label': 'deuterium excess'}, 'deuterium excess': {'id': 'http://linked.earth/ontology/paleo_proxy#deuterium_excess', 'label': 'deuterium excess'}, 'deuterium_excess': {'id': 'http://linked.earth/ontology/paleo_proxy#deuterium_excess', 'label': 'deuterium excess'}, 'diatom': {'id': 'http://linked.earth/ontology/paleo_proxy#diatom', 'label': 'diatom'}, 'dinocyst': {'id': 'http://linked.earth/ontology/paleo_proxy#dinocyst', 'label': 'dinocyst'}, 'dinoflagellate': {'id': 'http://linked.earth/ontology/paleo_proxy#dinocyst', 'label': 'dinocyst'}, 'documentary': {'id': 'http://linked.earth/ontology/paleo_proxy#historical', 'label': 'historical'}, 'dry bulk density': {'id': 'http://linked.earth/ontology/paleo_proxy#dry_bulk_density', 'label': 'dry bulk density'}, 'dry sediment': {'id': 'http://linked.earth/ontology/paleo_proxy#bulk_sediment', 'label': 'bulk sediment'}, 'dry_bulk_density': {'id': 'http://linked.earth/ontology/paleo_proxy#dry_bulk_density', 'label': 'dry bulk density'}, 'dx': {'id': 'http://linked.earth/ontology/paleo_proxy#deuterium_excess', 'label': 'deuterium excess'}, 'dynocist mat': {'id': 'http://linked.earth/ontology/paleo_proxy#dinocyst', 'label': 'dinocyst'}, 'element': {'id': 'http://linked.earth/ontology/paleo_proxy#needsToBeChanged', 'label': 'needsToBeChanged'}, 'element ratio': {'id': 'http://linked.earth/ontology/paleo_proxy#needsToBeChanged', 'label': 'needsToBeChanged'}, 'eu/zr': {'id': 'http://linked.earth/ontology/paleo_proxy#Eu_Zr', 'label': 'Eu/Zr'}, 'eu_zr': {'id': 'http://linked.earth/ontology/paleo_proxy#Eu_Zr', 'label': 'Eu/Zr'}, 'fe': {'id': 'http://linked.earth/ontology/paleo_proxy#Fe', 'label': 'Fe'}, 'fe/al': {'id': 'http://linked.earth/ontology/paleo_proxy#Fe_Al', 'label': 'Fe/Al'}, 'fe_al': {'id': 'http://linked.earth/ontology/paleo_proxy#Fe_Al', 'label': 'Fe/Al'}, 'foram d18o': {'id': 'http://linked.earth/ontology/paleo_proxy#d18O', 'label': 'd18O'}, 'foram mg/ca': {'id': 'http://linked.earth/ontology/paleo_proxy#Mg_Ca', 'label': 'Mg/Ca'}, 'foraminifer': {'id': 'http://linked.earth/ontology/paleo_proxy#foraminifera', 'label': 'foraminifera'}, 'foraminifera': {'id': 'http://linked.earth/ontology/paleo_proxy#foraminifera', 'label': 'foraminifera'}, 'gamma': {'id': 'http://linked.earth/ontology/paleo_proxy#bulk_density', 'label': 'bulk density'}, 'gdgt': {'id': 'http://linked.earth/ontology/paleo_proxy#GDGT', 'label': 'GDGT'}, 'glycerol dialkyl glycerol tetraether': {'id': 'http://linked.earth/ontology/paleo_proxy#GDGT', 'label': 'GDGT'}, 'grain size': {'id': 'http://linked.earth/ontology/paleo_proxy#grain_size', 'label': 'grain size'}, 'grain_size': {'id': 'http://linked.earth/ontology/paleo_proxy#grain_size', 'label': 'grain size'}, 'hbi': {'id': 'http://linked.earth/ontology/paleo_proxy#HBI', 'label': 'HBI'}, 'highly-branched isoprenoid alkene': {'id': 'http://linked.earth/ontology/paleo_proxy#HBI', 'label': 'HBI'}, 'historic': {'id': 'http://linked.earth/ontology/paleo_proxy#historical', 'label': 'historical'}, 'historical': {'id': 'http://linked.earth/ontology/paleo_proxy#historical', 'label': 'historical'}, 'humification': {'id': 'http://linked.earth/ontology/paleo_proxy#humification', 'label': 'humification'}, 'humification index': {'id': 'http://linked.earth/ontology/paleo_proxy#humification', 'label': 'humification'}, 'hybrid': {'id': 'http://linked.earth/ontology/paleo_proxy#multiproxy', 'label': 'multiproxy'}, 'hybrid grain size': {'id': 'http://linked.earth/ontology/paleo_proxy#multiproxy', 'label': 'multiproxy'}, 'hybrid-ice': {'id': 'http://linked.earth/ontology/paleo_proxy#multiproxy', 'label': 'multiproxy'}, 'hybrid-lake': {'id': 'http://linked.earth/ontology/paleo_proxy#multiproxy', 'label': 'multiproxy'}, 'ice': {'id': 'http://linked.earth/ontology/paleo_proxy#needsToBeChanged', 'label': 'needsToBeChanged'}, 'ice accumulation': {'id': 'http://linked.earth/ontology/paleo_proxy#ice_accumulation', 'label': 'ice accumulation'}, 'ice melt': {'id': 'http://linked.earth/ontology/paleo_proxy#ice_melt', 'label': 'ice melt'}, 'ice proxy with 25 carbon atoms': {'id': 'http://linked.earth/ontology/paleo_proxy#IP25', 'label': 'IP25'}, 'ice_accumulation': {'id': 'http://linked.earth/ontology/paleo_proxy#ice_accumulation', 'label': 'ice accumulation'}, 'ice_melt': {'id': 'http://linked.earth/ontology/paleo_proxy#ice_melt', 'label': 'ice melt'}, 'inorganic carbon': {'id': 'http://linked.earth/ontology/paleo_proxy#inorganic_carbon', 'label': 'inorganic carbon'}, 'inorganic_carbon': {'id': 'http://linked.earth/ontology/paleo_proxy#inorganic_carbon', 'label': 'inorganic carbon'}, 'ip25': {'id': 'http://linked.earth/ontology/paleo_proxy#IP25', 'label': 'IP25'}, 'irm': {'id': 'http://linked.earth/ontology/paleo_proxy#magnetic', 'label': 'magnetic'}, 'iron': {'id': 'http://linked.earth/ontology/paleo_proxy#Fe', 'label': 'Fe'}, 'iron/aluminum': {'id': 'http://linked.earth/ontology/paleo_proxy#Fe_Al', 'label': 'Fe/Al'}, 'isotope': {'id': 'http://linked.earth/ontology/paleo_proxy#needsToBeChanged', 'label': 'needsToBeChanged'}, 'isotope diffusion': {'id': 'http://linked.earth/ontology/paleo_proxy#needsToBeChanged', 'label': 'needsToBeChanged'}, 'k': {'id': 'http://linked.earth/ontology/paleo_proxy#multiproxy', 'label': 'multiproxy'}, 'lake level': {'id': 'http://linked.earth/ontology/paleo_proxy#lake_level', 'label': 'lake level'}, 'lake stratigraphy and radiocarbon dating of macrofossils': {'id': 'http://linked.earth/ontology/paleo_proxy#lake_level', 'label': 'lake level'}, 'lake_level': {'id': 'http://linked.earth/ontology/paleo_proxy#lake_level', 'label': 'lake level'}, 'lakelevel': {'id': 'http://linked.earth/ontology/paleo_proxy#lake_level', 'label': 'lake level'}, 'lakestatus': {'id': 'http://linked.earth/ontology/paleo_proxy#lake_level', 'label': 'lake level'}, 'late-wood cellulose': {'id': 'http://linked.earth/ontology/paleo_proxy#latewood_cellulose', 'label': 'latewood cellulose'}, 'latewood cellulose': {'id': 'http://linked.earth/ontology/paleo_proxy#latewood_cellulose', 'label': 'latewood cellulose'}, 'latewood density': {'id': 'http://linked.earth/ontology/paleo_proxy#maximum_latewood_density', 'label': 'maximum latewood density'}, 'latewood_cellulose': {'id': 'http://linked.earth/ontology/paleo_proxy#latewood_cellulose', 'label': 'latewood cellulose'}, 'ldi': {'id': 'http://linked.earth/ontology/paleo_proxy#LDI', 'label': 'LDI'}, 'leaf wax': {'id': 'http://linked.earth/ontology/paleo_proxy#dD', 'label': 'dD'}, 'leafwax': {'id': 'http://linked.earth/ontology/paleo_proxy#dD', 'label': 'dD'}, 'ln(ti/ca)': {'id': 'http://linked.earth/ontology/paleo_proxy#Ti_Ca', 'label': 'Ti/Ca'}, 'long chain diol': {'id': 'http://linked.earth/ontology/paleo_proxy#LDI', 'label': 'LDI'}, 'long-chain diol index': {'id': 'http://linked.earth/ontology/paleo_proxy#LDI', 'label': 'LDI'}, 'macrofossils': {'id': 'http://linked.earth/ontology/paleo_proxy#macrofossils', 'label': 'macrofossils'}, 'magnesium': {'id': 'http://linked.earth/ontology/paleo_proxy#Mg', 'label': 'Mg'}, 'magnesium/calcium': {'id': 'http://linked.earth/ontology/paleo_proxy#Mg_Ca', 'label': 'Mg/Ca'}, 'magnetic': {'id': 'http://linked.earth/ontology/paleo_proxy#magnetic', 'label': 'magnetic'}, 'magnetic susceptibility': {'id': 'http://linked.earth/ontology/paleo_proxy#magnetic_susceptibility', 'label': 'magnetic susceptibility'}, 'magnetic_susceptibility': {'id': 'http://linked.earth/ontology/paleo_proxy#magnetic_susceptibility', 'label': 'magnetic susceptibility'}, 'mar': {'id': 'http://linked.earth/ontology/paleo_proxy#mass_accumulation_rate', 'label': 'mass accumulation rate'}, 'mass accumulation rate': {'id': 'http://linked.earth/ontology/paleo_proxy#mass_accumulation_rate', 'label': 'mass accumulation rate'}, 'mass per area per time unit': {'id': 'http://linked.earth/ontology/paleo_proxy#mass_accumulation_rate', 'label': 'mass accumulation rate'}, 'mass_accumulation_rate': {'id': 'http://linked.earth/ontology/paleo_proxy#mass_accumulation_rate', 'label': 'mass accumulation rate'}, 'maximum latewood density': {'id': 'http://linked.earth/ontology/paleo_proxy#maximum_latewood_density', 'label': 'maximum latewood density'}, 'maximum_latewood_density': {'id': 'http://linked.earth/ontology/paleo_proxy#maximum_latewood_density', 'label': 'maximum latewood density'}, 'melt': {'id': 'http://linked.earth/ontology/paleo_proxy#ice_melt', 'label': 'ice melt'}, 'melt layer': {'id': 'http://linked.earth/ontology/paleo_proxy#ice_melt', 'label': 'ice melt'}, 'mg': {'id': 'http://linked.earth/ontology/paleo_proxy#Mg', 'label': 'Mg'}, 'mg/ca': {'id': 'http://linked.earth/ontology/paleo_proxy#Mg_Ca', 'label': 'Mg/Ca'}, 'mg0': {'id': 'http://linked.earth/ontology/paleo_proxy#needsToBeChanged', 'label': 'needsToBeChanged'}, 'mg_ca': {'id': 'http://linked.earth/ontology/paleo_proxy#Mg_Ca', 'label': 'Mg/Ca'}, 'mgca': {'id': 'http://linked.earth/ontology/paleo_proxy#Mg_Ca', 'label': 'Mg/Ca'}, 'middle-wood cellulose': {'id': 'http://linked.earth/ontology/paleo_proxy#needsToBeChanged', 'label': 'needsToBeChanged'}, 'midge': {'id': 'http://linked.earth/ontology/paleo_proxy#chironomid', 'label': 'chironomid'}, 'mineral': {'id': 'http://linked.earth/ontology/paleo_proxy#needsToBeChanged', 'label': 'needsToBeChanged'}, 'mineralogy': {'id': 'http://linked.earth/ontology/paleo_proxy#needsToBeChanged', 'label': 'needsToBeChanged'}, 'minerogenic layers': {'id': 'http://linked.earth/ontology/paleo_proxy#stratigraphy', 'label': 'stratigraphy'}, 'ms': {'id': 'http://linked.earth/ontology/paleo_proxy#magnetic_susceptibility', 'label': 'magnetic susceptibility'}, 'multiple proxies': {'id': 'http://linked.earth/ontology/paleo_proxy#multiproxy', 'label': 'multiproxy'}, 'multiproxy': {'id': 'http://linked.earth/ontology/paleo_proxy#multiproxy', 'label': 'multiproxy'}, 'mxd': {'id': 'http://linked.earth/ontology/paleo_proxy#maximum_latewood_density', 'label': 'maximum latewood density'}, 'n. dutertrei': {'id': 'http://linked.earth/ontology/paleo_proxy#foraminifera', 'label': 'foraminifera'}, 'needs to be changed': {'id': 'http://linked.earth/ontology/paleo_proxy#needs_to_be_changed', 'label': 'needs to be changed'}, 'needs_to_be_changed': {'id': 'http://linked.earth/ontology/paleo_proxy#needs_to_be_changed', 'label': 'needs to be changed'}, 'needstobechanged': {'id': 'http://linked.earth/ontology/paleo_proxy#needsToBeChanged', 'label': 'needsToBeChanged'}, 'organic carbon': {'id': 'http://linked.earth/ontology/paleo_proxy#TOC', 'label': 'TOC'}, 'organic compound': {'id': 'http://linked.earth/ontology/paleo_proxy#biomarker', 'label': 'biomarker'}, 'ostracod': {'id': 'http://linked.earth/ontology/paleo_proxy#ostracod', 'label': 'ostracod'}, 'p-aqueous': {'id': 'http://linked.earth/ontology/paleo_proxy#P-aqueous', 'label': 'P-aqueous'}, 'paq': {'id': 'http://linked.earth/ontology/paleo_proxy#P-aqueous', 'label': 'P-aqueous'}, 'particle size': {'id': 'http://linked.earth/ontology/paleo_proxy#grain_size', 'label': 'grain size'}, 'pca': {'id': 'http://linked.earth/ontology/paleo_proxy#needs_to_be_changed', 'label': 'needs to be changed'}, 'peat ash': {'id': 'http://linked.earth/ontology/paleo_proxy#peat_ash', 'label': 'peat ash'}, 'peat_ash': {'id': 'http://linked.earth/ontology/paleo_proxy#peat_ash', 'label': 'peat ash'}, 'percent': {'id': 'http://linked.earth/ontology/paleo_proxy#needsToBeChanged', 'label': 'needsToBeChanged'}, 'ph': {'id': 'http://linked.earth/ontology/paleo_proxy#pH', 'label': 'pH'}, 'planktonic foraminifera': {'id': 'http://linked.earth/ontology/paleo_proxy#foraminifera', 'label': 'foraminifera'}, 'plant detrital layers': {'id': 'http://linked.earth/ontology/paleo_proxy#stratigraphy', 'label': 'stratigraphy'}, 'plant macrofossils': {'id': 'http://linked.earth/ontology/paleo_proxy#macrofossils', 'label': 'macrofossils'}, 'pollen': {'id': 'http://linked.earth/ontology/paleo_proxy#pollen', 'label': 'pollen'}, 'pore ice d2h and d18o': {'id': 'http://linked.earth/ontology/paleo_proxy#multiproxy', 'label': 'multiproxy'}, 'radiolaria': {'id': 'http://linked.earth/ontology/paleo_proxy#radiolaria', 'label': 'radiolaria'}, 'radiolarian': {'id': 'http://linked.earth/ontology/paleo_proxy#radiolaria', 'label': 'radiolaria'}, 'rb': {'id': 'http://linked.earth/ontology/paleo_proxy#Rb', 'label': 'Rb'}, 'rb/sr': {'id': 'http://linked.earth/ontology/paleo_proxy#Rb_Sr', 'label': 'Rb/Sr'}, 'rb_sr': {'id': 'http://linked.earth/ontology/paleo_proxy#Rb_Sr', 'label': 'Rb/Sr'}, 'reflectance': {'id': 'http://linked.earth/ontology/paleo_proxy#reflectance', 'label': 'reflectance'}, 'ring width': {'id': 'http://linked.earth/ontology/paleo_proxy#ring_width', 'label': 'ring width'}, 'ring_width': {'id': 'http://linked.earth/ontology/paleo_proxy#ring_width', 'label': 'ring width'}, 'rubidium': {'id': 'http://linked.earth/ontology/paleo_proxy#Rb', 'label': 'Rb'}, 's': {'id': 'http://linked.earth/ontology/paleo_proxy#sulfur', 'label': 'sulfur'}, 'sed accumulation': {'id': 'http://linked.earth/ontology/paleo_proxy#accumulation_rate', 'label': 'accumulation rate'}, 'sediment': {'id': 'http://linked.earth/ontology/paleo_proxy#needsToBeChanged', 'label': 'needsToBeChanged'}, 'sr': {'id': 'http://linked.earth/ontology/paleo_proxy#Sr', 'label': 'Sr'}, 'sr/ca': {'id': 'http://linked.earth/ontology/paleo_proxy#Sr_Ca', 'label': 'Sr/Ca'}, 'sr_ca': {'id': 'http://linked.earth/ontology/paleo_proxy#Sr_Ca', 'label': 'Sr/Ca'}, 'srca': {'id': 'http://linked.earth/ontology/paleo_proxy#Sr_Ca', 'label': 'Sr/Ca'}, 'stratigraphy': {'id': 'http://linked.earth/ontology/paleo_proxy#stratigraphy', 'label': 'stratigraphy'}, 'strontium': {'id': 'http://linked.earth/ontology/paleo_proxy#Sr', 'label': 'Sr'}, 'strontium/calcium': {'id': 'http://linked.earth/ontology/paleo_proxy#Sr_Ca', 'label': 'Sr/Ca'}, 'sulfur': {'id': 'http://linked.earth/ontology/paleo_proxy#sulfur', 'label': 'sulfur'}, 'tds': {'id': 'http://linked.earth/ontology/paleo_proxy#needsToBeChanged', 'label': 'needsToBeChanged'}, 'testate amoeba': {'id': 'http://linked.earth/ontology/paleo_proxy#amoeba', 'label': 'amoeba'}, 'tetraether index of 86 carbon atoms': {'id': 'http://linked.earth/ontology/paleo_proxy#TEX86', 'label': 'TEX86'}, 'tex86': {'id': 'http://linked.earth/ontology/paleo_proxy#TEX86', 'label': 'TEX86'}, 'ti': {'id': 'http://linked.earth/ontology/paleo_proxy#Ti', 'label': 'Ti'}, 'ti/al': {'id': 'http://linked.earth/ontology/paleo_proxy#Ti_Al', 'label': 'Ti/Al'}, 'ti/ca': {'id': 'http://linked.earth/ontology/paleo_proxy#Ti_Ca', 'label': 'Ti/Ca'}, 'ti_al': {'id': 'http://linked.earth/ontology/paleo_proxy#Ti_Al', 'label': 'Ti/Al'}, 'ti_ca': {'id': 'http://linked.earth/ontology/paleo_proxy#Ti_Ca', 'label': 'Ti/Ca'}, 'tic': {'id': 'http://linked.earth/ontology/paleo_proxy#inorganic_carbon', 'label': 'inorganic carbon'}, 'titanium': {'id': 'http://linked.earth/ontology/paleo_proxy#Ti', 'label': 'Ti'}, 'titanium/aluminum': {'id': 'http://linked.earth/ontology/paleo_proxy#Ti_Al', 'label': 'Ti/Al'}, 'titanium/calcium': {'id': 'http://linked.earth/ontology/paleo_proxy#Ti_Ca', 'label': 'Ti/Ca'}, 'tn': {'id': 'http://linked.earth/ontology/paleo_proxy#total_nitrogen', 'label': 'total nitrogen'}, 'toc': {'id': 'http://linked.earth/ontology/paleo_proxy#TOC', 'label': 'TOC'}, 'total nitrogen': {'id': 'http://linked.earth/ontology/paleo_proxy#total_nitrogen', 'label': 'total nitrogen'}, 'total_nitrogen': {'id': 'http://linked.earth/ontology/paleo_proxy#total_nitrogen', 'label': 'total nitrogen'}, 'trace element / ca': {'id': 'http://linked.earth/ontology/paleo_proxy#needsToBeChanged', 'label': 'needsToBeChanged'}, 'traceelement': {'id': 'http://linked.earth/ontology/paleo_proxy#needsToBeChanged', 'label': 'needsToBeChanged'}, 'transfer function': {'id': 'http://linked.earth/ontology/paleo_proxy#foraminifera', 'label': 'foraminifera'}, 'trw': {'id': 'http://linked.earth/ontology/paleo_proxy#ring_width', 'label': 'ring width'}, 'u cluster 2': {'id': 'http://linked.earth/ontology/paleo_proxy#needsToBeChanged', 'label': 'needsToBeChanged'}, 'uvigerina mediterranea': {'id': 'http://linked.earth/ontology/paleo_proxy#foraminifera', 'label': 'foraminifera'}, 'varve': {'id': 'http://linked.earth/ontology/paleo_proxy#varve_thickness', 'label': 'varve thickness'}, 'varve property': {'id': 'http://linked.earth/ontology/paleo_proxy#varve_thickness', 'label': 'varve thickness'}, 'varve thickness': {'id': 'http://linked.earth/ontology/paleo_proxy#varve_thickness', 'label': 'varve thickness'}, 'varve_thickness': {'id': 'http://linked.earth/ontology/paleo_proxy#varve_thickness', 'label': 'varve thickness'}, 'varves': {'id': 'http://linked.earth/ontology/paleo_proxy#varve_thickness', 'label': 'varve thickness'}}
to_data(data={})[source]
to_json()[source]
class pylipd.classes.paleoproxy.PaleoProxyConstants[source]
ACL = <pylipd.classes.paleoproxy.PaleoProxy object>
Al2O3 = <pylipd.classes.paleoproxy.PaleoProxy object>
BIT = <pylipd.classes.paleoproxy.PaleoProxy object>
BSi = <pylipd.classes.paleoproxy.PaleoProxy object>
Ba_Al = <pylipd.classes.paleoproxy.PaleoProxy object>
Ba_Ca = <pylipd.classes.paleoproxy.PaleoProxy object>
C_N = <pylipd.classes.paleoproxy.PaleoProxy object>
CaCO3 = <pylipd.classes.paleoproxy.PaleoProxy object>
Ca_K = <pylipd.classes.paleoproxy.PaleoProxy object>
Ca_Ti = <pylipd.classes.paleoproxy.PaleoProxy object>
Eu_Zr = <pylipd.classes.paleoproxy.PaleoProxy object>
Fe = <pylipd.classes.paleoproxy.PaleoProxy object>
Fe_Al = <pylipd.classes.paleoproxy.PaleoProxy object>
GDGT = <pylipd.classes.paleoproxy.PaleoProxy object>
HBI = <pylipd.classes.paleoproxy.PaleoProxy object>
IP25 = <pylipd.classes.paleoproxy.PaleoProxy object>
LDI = <pylipd.classes.paleoproxy.PaleoProxy object>
Mg = <pylipd.classes.paleoproxy.PaleoProxy object>
Mg_Ca = <pylipd.classes.paleoproxy.PaleoProxy object>
P_aqueous = <pylipd.classes.paleoproxy.PaleoProxy object>
Rb = <pylipd.classes.paleoproxy.PaleoProxy object>
Rb_Sr = <pylipd.classes.paleoproxy.PaleoProxy object>
Sr = <pylipd.classes.paleoproxy.PaleoProxy object>
Sr_Ca = <pylipd.classes.paleoproxy.PaleoProxy object>
TEX86 = <pylipd.classes.paleoproxy.PaleoProxy object>
TOC = <pylipd.classes.paleoproxy.PaleoProxy object>
Ti = <pylipd.classes.paleoproxy.PaleoProxy object>
Ti_Al = <pylipd.classes.paleoproxy.PaleoProxy object>
Ti_Ca = <pylipd.classes.paleoproxy.PaleoProxy object>
accumulation_rate = <pylipd.classes.paleoproxy.PaleoProxy object>
alkenone = <pylipd.classes.paleoproxy.PaleoProxy object>
amoeba = <pylipd.classes.paleoproxy.PaleoProxy object>
biomarker = <pylipd.classes.paleoproxy.PaleoProxy object>
borehole = <pylipd.classes.paleoproxy.PaleoProxy object>
bubble_frequency = <pylipd.classes.paleoproxy.PaleoProxy object>
bulk_density = <pylipd.classes.paleoproxy.PaleoProxy object>
bulk_sediment = <pylipd.classes.paleoproxy.PaleoProxy object>
calcification_rate = <pylipd.classes.paleoproxy.PaleoProxy object>
calcite = <pylipd.classes.paleoproxy.PaleoProxy object>
carbonate = <pylipd.classes.paleoproxy.PaleoProxy object>
cellulose = <pylipd.classes.paleoproxy.PaleoProxy object>
charcoal = <pylipd.classes.paleoproxy.PaleoProxy object>
chironomid = <pylipd.classes.paleoproxy.PaleoProxy object>
chlorophyll = <pylipd.classes.paleoproxy.PaleoProxy object>
chrysophyte_assemblage = <pylipd.classes.paleoproxy.PaleoProxy object>
cladoceran = <pylipd.classes.paleoproxy.PaleoProxy object>
coccolithophore = <pylipd.classes.paleoproxy.PaleoProxy object>
d13C = <pylipd.classes.paleoproxy.PaleoProxy object>
d15N = <pylipd.classes.paleoproxy.PaleoProxy object>
d15N_d40Ar = <pylipd.classes.paleoproxy.PaleoProxy object>
d18O = <pylipd.classes.paleoproxy.PaleoProxy object>
dD = <pylipd.classes.paleoproxy.PaleoProxy object>
deuterium_excess = <pylipd.classes.paleoproxy.PaleoProxy object>
diatom = <pylipd.classes.paleoproxy.PaleoProxy object>
dinocyst = <pylipd.classes.paleoproxy.PaleoProxy object>
dry_bulk_density = <pylipd.classes.paleoproxy.PaleoProxy object>
foraminifera = <pylipd.classes.paleoproxy.PaleoProxy object>
grain_size = <pylipd.classes.paleoproxy.PaleoProxy object>
historical = <pylipd.classes.paleoproxy.PaleoProxy object>
humification = <pylipd.classes.paleoproxy.PaleoProxy object>
ice_accumulation = <pylipd.classes.paleoproxy.PaleoProxy object>
ice_melt = <pylipd.classes.paleoproxy.PaleoProxy object>
inorganic_carbon = <pylipd.classes.paleoproxy.PaleoProxy object>
lake_level = <pylipd.classes.paleoproxy.PaleoProxy object>
latewood_cellulose = <pylipd.classes.paleoproxy.PaleoProxy object>
macrofossils