зеркало из https://github.com/microsoft/torchgeo.git
66 строки
2.1 KiB
Python
Executable File
66 строки
2.1 KiB
Python
Executable File
#!/usr/bin/env python3
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# Copyright (c) Microsoft Corporation. All rights reserved.
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# Licensed under the MIT License.
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import pandas as pd
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filename = '0123456-012345678901234.csv'
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size = 6
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data = {
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'gbifID': [''] * size,
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'datasetKey': [''] * size,
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'occurrenceID': [''] * size,
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'kingdom': ['Animalia'] * size,
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'phylum': ['Chordata'] * size,
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'class': ['Mammalia'] * size,
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'order': ['Primates'] * size,
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'family': ['Hominidae'] * size,
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'genus': ['Homo'] * size,
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'species': ['Homo sapiens'] * size,
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'infraspecificEpithet': [''] * size,
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'taxonRank': ['SPECIES'] * size,
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'scientificName': ['Homo sapiens Linnaeus, 1758'] * size,
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'verbatimScientificName': ['Homo sapiens Linnaeus, 1758'] * size,
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'verbatimScientificNameAuthorship': ['Linnaeus, 1758'] * size,
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'countryCode': ['US'] * size,
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'locality': ['Chicago'] * size,
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'stateProvince': ['Illinois'] * size,
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'occurrenceStatus': ['PRESENT'] * size,
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'individualCount': [1] * size,
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'publishingOrgKey': [''] * size,
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'decimalLatitude': [41.881832] * size,
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'decimalLongitude': [''] + [-87.623177] * (size - 1),
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'coordinateUncertaintyInMeters': [5] * size,
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'coordinatePrecision': [''] * size,
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'elevation': [''] * size,
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'elevationAccuracy': [''] * size,
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'depth': [''] * size,
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'depthAccuracy': [''] * size,
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'eventDate': ['', '', '', '', -450, '2022-04-16T10:13:35.123Z'],
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'day': [16, '', '', '', '', 16],
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'month': [4, '', '', 12, 4, 4],
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'year': [2022, '', 2022, 2022, 2022, 2022],
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'taxonKey': [1] * size,
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'speciesKey': [1] * size,
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'basisOfRecord': ['HUMAN_OBSERVATION'] * size,
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'institutionCode': [''] * size,
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'collectionCode': [''] * size,
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'catalogNumber': [''] * size,
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'recordNumber': [''] * size,
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'identifiedBy': [''] * size,
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'dateIdentified': [''] * size,
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'license': [''] * size,
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'rightsHolder': [''] * size,
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'recordedBy': [''] * size,
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'typeStatus': [''] * size,
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'establishmentMeans': [''] * size,
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'lastInterpreted': [''] * size,
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'mediaType': [''] * size,
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'issue': [''] * size,
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}
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df = pd.DataFrame(data)
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df.to_csv(filename, sep='\t', index=False)
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