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Display ABCD equivalence in list of terms document

This commit is contained in:
Steve Baskauf 2021-02-11 08:36:27 -06:00
parent 03bc7e182f
commit 6fad0e8911
2 changed files with 1349 additions and 2 deletions
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11
build/build-termlist.py
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@ -1,5 +1,6 @@
# Script to build Markdown pages that provide term metadata for complex vocabularies # Script to build Markdown pages that provide term metadata for complex vocabularies
# Steve Baskauf 2020-08-12 CC0 # Steve Baskauf 2020-08-12 CC0
# updated 2021-02-11
# This script merges static Markdown header and footer documents with term information tables (in Markdown) generated from data in the rs.tdwg.org repo from the TDWG Github site # This script merges static Markdown header and footer documents with term information tables (in Markdown) generated from data in the rs.tdwg.org repo from the TDWG Github site
import re import re
@ -92,7 +93,7 @@ print()
# --------------- # ---------------
# Create column list # Create column list
column_list = ['pref_ns_prefix', 'pref_ns_uri', 'term_localName', 'label', 'rdfs_comment', 'dcterms_description', 'examples', 'term_modified', 'term_deprecated', 'rdf_type', 'replaces_term', 'replaces1_term'] column_list = ['pref_ns_prefix', 'pref_ns_uri', 'term_localName', 'label', 'rdfs_comment', 'dcterms_description', 'examples', 'term_modified', 'term_deprecated', 'rdf_type', 'tdwgutility_abcdEquivalence', 'replaces_term', 'replaces1_term']
#column_list = ['pref_ns_prefix', 'pref_ns_uri', 'term_localName', 'label', 'definition', 'usage', 'notes', 'term_modified', 'term_deprecated', 'type'] #column_list = ['pref_ns_prefix', 'pref_ns_uri', 'term_localName', 'label', 'definition', 'usage', 'notes', 'term_modified', 'term_deprecated', 'type']
if vocab_type == 2: if vocab_type == 2:
column_list += ['controlled_value_string'] column_list += ['controlled_value_string']
@ -114,7 +115,7 @@ for term_list in term_lists_info:
data_url = githubBaseUri + term_list['database'] + '/' + term_list['database'] + '.csv' data_url = githubBaseUri + term_list['database'] + '/' + term_list['database'] + '.csv'
frame = pd.read_csv(data_url, na_filter=False) frame = pd.read_csv(data_url, na_filter=False)
for index,row in frame.iterrows(): for index,row in frame.iterrows():
row_list = [term_list['pref_ns_prefix'], term_list['pref_ns_uri'], row['term_localName'], row['label'], row['rdfs_comment'], row['dcterms_description'], row['examples'], row['term_modified'], row['term_deprecated'], row['rdf_type'], row['replaces_term'], row['replaces1_term']] row_list = [term_list['pref_ns_prefix'], term_list['pref_ns_uri'], row['term_localName'], row['label'], row['rdfs_comment'], row['dcterms_description'], row['examples'], row['term_modified'], row['term_deprecated'], row['rdf_type'], row['tdwgutility_abcdEquivalence'], row['replaces_term'], row['replaces1_term']]
#row_list = [term_list['pref_ns_prefix'], term_list['pref_ns_uri'], row['term_localName'], row['label'], row['definition'], row['usage'], row['notes'], row['term_modified'], row['term_deprecated'], row['type']] #row_list = [term_list['pref_ns_prefix'], term_list['pref_ns_uri'], row['term_localName'], row['label'], row['definition'], row['usage'], row['notes'], row['term_modified'], row['term_deprecated'], row['type']]
if vocab_type == 2: if vocab_type == 2:
row_list += [row['controlled_value_string']] row_list += [row['controlled_value_string']]
@ -329,6 +330,12 @@ if True:
#text += '\t\t\t<td>' + createLinks(row['usage']) + '</td>\n' #text += '\t\t\t<td>' + createLinks(row['usage']) + '</td>\n'
text += '\t\t</tr>\n' text += '\t\t</tr>\n'
if row['tdwgutility_abcdEquivalence'] != '':
text += '\t\t<tr>\n'
text += '\t\t\t<td>ABCD equivalence</td>\n'
text += '\t\t\t<td>' + createLinks(row['tdwgutility_abcdEquivalence']) + '</td>\n'
text += '\t\t</tr>\n'
if vocab_type == 2 or vocab_type ==3: # controlled vocabulary if vocab_type == 2 or vocab_type ==3: # controlled vocabulary
text += '\t\t<tr>\n' text += '\t\t<tr>\n'
text += '\t\t\t<td>Controlled value</td>\n' text += '\t\t\t<td>Controlled value</td>\n'

1340
docs/list/index.md
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