History of faculty_hiring_us
The changes to the source code of this entry in the repository, newest first, each with the differences it made to the entry's files. They are also listed on GitLab.
[entries] Add the date when each entry was added, and remove icon_hash beff7c9
The dates are those of the commits that first added the entries' files (2020-08-11 for the entries of the initial commit); renamed entries keep the date of their first name. Changed: none
diff --git a/entries/faculty_hiring_us/__init__.py b/entries/faculty_hiring_us/__init__.py
index 0e738b7..9e68595 100644
--- a/entries/faculty_hiring_us/__init__.py
+++ b/entries/faculty_hiring_us/__init__.py
@@ -31,7 +31,7 @@ The networks have the following properties:
tags = ['Economic', 'Employment', 'Weighted', 'Metadata']
url = 'https://github.com/LarremoreLab/us-faculty-hiring-networks'
citation = [('Wapman, K.H., Zhang, S., Clauset, A., Larremore, D. B., "Quantifying hierarchy and dynamics in US faculty hiring and retention." Nature (2022).', 'https://doi.org/10.1038/s41586-022-05222-x')]
-icon_hash = None
+date_added = '2022-11-17'
upstream_license = None
upstream_prefix = 'https://raw.githubusercontent.com/LarremoreLab/us-faculty-hiring-networks/main/data'
[entries] Prefix the properties in the descriptions with (Node), (Edge) or (Graph) bc3dbbd
The lists of properties at the end of the descriptions marked edge properties with "Edge" but left node properties unmarked, or grouped them in "Nodes: `a`, ...; `b`, ..." items, so the kind of a property was often unclear. Every item now starts with (Node), (Edge) or (Graph), followed by the property names, a colon and the explanation, one item per property or group of properties; qualifications (kinds of nodes, networks) follow the names in parentheses. Properties that were only named got a short explanation, and a few items that named the wrong kind of property were corrected.
diff --git a/entries/faculty_hiring_us/__init__.py b/entries/faculty_hiring_us/__init__.py
index 0662310..0e738b7 100644
--- a/entries/faculty_hiring_us/__init__.py
+++ b/entries/faculty_hiring_us/__init__.py
@@ -23,8 +23,11 @@ description = """Networks of faculty hiring for all PhD-granting US universities
The networks have the following properties:
-- Nodes: `id` and `name` of the institution; `ranked`, whether the institution is one of the US PhD-granting institutions ranked by the authors in this network (restricting to these nodes gives the network analyzed in the paper); `non_attrition` and `attrition`, the number of faculty-years (2011–2019) in which faculty trained at the institution and employed in this network did not leave, or left, the sample (-1 where not available, i.e. for institutions that are not ranked).
-- Edges: `total`, the number of faculty at institution j with a doctorate from institution i; `men` and `women`, the same count by gender (faculty whose gender could not be determined are counted only in `total`)."""
+- (Node) `id` and `name`: the id and name of the institution.
+- (Node) `ranked`: whether the institution is one of the US PhD-granting institutions ranked by the authors in this network (restricting to these nodes gives the network analyzed in the paper).
+- (Node) `non_attrition` and `attrition`: the number of faculty-years (2011–2019) in which faculty trained at the institution and employed in this network did not leave, or left, the sample (-1 where not available, i.e. for institutions that are not ranked).
+- (Edge) `total`: the number of faculty at institution j with a doctorate from institution i.
+- (Edge) `men` and `women`: the same count by gender (faculty whose gender could not be determined are counted only in `total`)."""
tags = ['Economic', 'Employment', 'Weighted', 'Metadata']
url = 'https://github.com/LarremoreLab/us-faculty-hiring-networks'
citation = [('Wapman, K.H., Zhang, S., Clauset, A., Larremore, D. B., "Quantifying hierarchy and dynamics in US faculty hiring and retention." Nature (2022).', 'https://doi.org/10.1038/s41586-022-05222-x')]
[entries] Remove unneeded code from the entries 2c69f19
Unneeded "global files" statements, unused imports and variables, f-strings without placeholders, duplicate keys in foodweb_little_rock (keeping the order and the values used), and the second definition of get_lines() in twitter_higgs. Nothing changes in the networks or descriptions. Changed: none
diff --git a/entries/faculty_hiring_us/__init__.py b/entries/faculty_hiring_us/__init__.py
index 42050d9..0662310 100644
--- a/entries/faculty_hiring_us/__init__.py
+++ b/entries/faculty_hiring_us/__init__.py
@@ -173,7 +173,6 @@ def fetch_upstream(force=False):
@coerce_props()
@annotate()
def parse(alts=None):
- global files
name = __name__.split(".")[-1]
for fnames, alt, fmt in files:
if alts is not None and alt not in alts:
[entries] Use American spelling in the descriptions 802d564
British spellings in the titles and descriptions of 69 entries (e.g. labelled, organisation, millimetres, centres, anonymised, neighbours, analysed, modelled, colour, licence) are replaced by the American ones. Proper names keep their spelling (Otago Harbour, the Centre for Water Systems, the Centre jeunesse de Montréal, the Dutch Ministry of Defence), as do quoted upstream terms, citations, and property names.
diff --git a/entries/faculty_hiring_us/__init__.py b/entries/faculty_hiring_us/__init__.py
index beffbaa..42050d9 100644
--- a/entries/faculty_hiring_us/__init__.py
+++ b/entries/faculty_hiring_us/__init__.py
@@ -19,11 +19,11 @@
from .. import *
title = "Faculty hiring networks in the US (2022)"
-description = """Networks of faculty hiring for all PhD-granting US universities over the decade 2011–2020. A directed edge (i,j) indicates that people who received their doctorate from institution i were tenure-track faculty at institution j during the time of collection (2011–2020). Faculty with doctorates from anywhere are included, so the doctoral institutions (sources) also include non-US institutions and institutions outside the ranking, which appear only as sources; the US PhD-granting institutions that the authors analyse are marked by the `ranked` node property. This dataset is divided into separate networks for all 107 fields, as well as aggregate networks for 8 domains, and an overall network for all of academia.
+description = """Networks of faculty hiring for all PhD-granting US universities over the decade 2011–2020. A directed edge (i,j) indicates that people who received their doctorate from institution i were tenure-track faculty at institution j during the time of collection (2011–2020). Faculty with doctorates from anywhere are included, so the doctoral institutions (sources) also include non-US institutions and institutions outside the ranking, which appear only as sources; the US PhD-granting institutions that the authors analyze are marked by the `ranked` node property. This dataset is divided into separate networks for all 107 fields, as well as aggregate networks for 8 domains, and an overall network for all of academia.
The networks have the following properties:
-- Nodes: `id` and `name` of the institution; `ranked`, whether the institution is one of the US PhD-granting institutions ranked by the authors in this network (restricting to these nodes gives the network analysed in the paper); `non_attrition` and `attrition`, the number of faculty-years (2011–2019) in which faculty trained at the institution and employed in this network did not leave, or left, the sample (-1 where not available, i.e. for institutions that are not ranked).
+- Nodes: `id` and `name` of the institution; `ranked`, whether the institution is one of the US PhD-granting institutions ranked by the authors in this network (restricting to these nodes gives the network analyzed in the paper); `non_attrition` and `attrition`, the number of faculty-years (2011–2019) in which faculty trained at the institution and employed in this network did not leave, or left, the sample (-1 where not available, i.e. for institutions that are not ranked).
- Edges: `total`, the number of faculty at institution j with a doctorate from institution i; `men` and `women`, the same count by gender (faculty whose gender could not be determined are counted only in `total`)."""
tags = ['Economic', 'Employment', 'Weighted', 'Metadata']
url = 'https://github.com/LarremoreLab/us-faculty-hiring-networks'
[entries] Fix parse bugs and improve the metadata of existing entries c996a0e
From a review of the dataset descriptions against the upstream sources and papers, and from user reports: - parse fixes (wrong edge direction or directedness, shifted or misnamed properties, merged node identities, duplicated or missing edges and nodes, wrong types), e.g. arxiv_citation (the HepTh dates were a copy of the HepPh ones; now from the KDD Cup 2003 data), eu_procurements, foursquare_global, hiv_transmission, genetic_multiplex, gnutella (adds the 05 snapshot), roadnet, macaque_neural, python_dependency - descriptions rewritten from the upstream sources, documenting every property - corrected titles, citations and DOIs, licences (ustream_license typo, the data's own terms), tags and ICON ids - url lists for entries with several sources or dataset pages - SocioPatterns entries moved to the site's new data location, with the daily networks of sp_infectious and sp_primary_school - the Michael Fire entries marked as orphans (served from the mirror) - redundant type forcings removed after the graph-tool coercion fixes
diff --git a/entries/faculty_hiring_us/__init__.py b/entries/faculty_hiring_us/__init__.py
index 3543cfe..beffbaa 100644
--- a/entries/faculty_hiring_us/__init__.py
+++ b/entries/faculty_hiring_us/__init__.py
@@ -29,7 +29,7 @@ tags = ['Economic', 'Employment', 'Weighted', 'Metadata']
url = 'https://github.com/LarremoreLab/us-faculty-hiring-networks'
citation = [('Wapman, K.H., Zhang, S., Clauset, A., Larremore, D. B., "Quantifying hierarchy and dynamics in US faculty hiring and retention." Nature (2022).', 'https://doi.org/10.1038/s41586-022-05222-x')]
icon_hash = None
-ustream_license = None
+upstream_license = None
upstream_prefix = 'https://raw.githubusercontent.com/LarremoreLab/us-faculty-hiring-networks/main/data'
fields = [
[entries] Fix faculty_hiring_us networks d67c7f4
- Each network contained every institution of the whole dataset, mostly as isolated nodes, because nodes were created for all rows before selecting the network's own rows; now only the institutions in its edges are included. - The attrition counts of each institution were taken from an arbitrary network's row; now they come from the network's own rows, and are -1 where not available. - The upstream files are read by column name, since the current version (August 2026) added columns. - New `ranked` node property, marking the US PhD-granting institutions ranked by the authors in each network (the network analysed in the paper). - The description explains that the doctoral institutions include non-US and unranked institutions, and documents all properties. Fixes #17
diff --git a/entries/faculty_hiring_us/__init__.py b/entries/faculty_hiring_us/__init__.py
index f6f2bf1..3543cfe 100644
--- a/entries/faculty_hiring_us/__init__.py
+++ b/entries/faculty_hiring_us/__init__.py
@@ -19,7 +19,12 @@
from .. import *
title = "Faculty hiring networks in the US (2022)"
-description = """Networks of faculty hiring for all PhD-granting US universities over the decade 2011–2020. Each node is a PhD-granting institution, and a directed edge (i,j) indicates that a person received their PhD from node i and was tenure-track faculty at node j during time of collection (2011-2020). This dataset is divided into separate networks for all 107 fields, as well as aggregate networks for 8 domains, and an overall network for all of academia. Edge properties include the total count of hires, as well as separate counts for men and women."""
+description = """Networks of faculty hiring for all PhD-granting US universities over the decade 2011–2020. A directed edge (i,j) indicates that people who received their doctorate from institution i were tenure-track faculty at institution j during the time of collection (2011–2020). Faculty with doctorates from anywhere are included, so the doctoral institutions (sources) also include non-US institutions and institutions outside the ranking, which appear only as sources; the US PhD-granting institutions that the authors analyse are marked by the `ranked` node property. This dataset is divided into separate networks for all 107 fields, as well as aggregate networks for 8 domains, and an overall network for all of academia.
+
+The networks have the following properties:
+
+- Nodes: `id` and `name` of the institution; `ranked`, whether the institution is one of the US PhD-granting institutions ranked by the authors in this network (restricting to these nodes gives the network analysed in the paper); `non_attrition` and `attrition`, the number of faculty-years (2011–2019) in which faculty trained at the institution and employed in this network did not leave, or left, the sample (-1 where not available, i.e. for institutions that are not ranked).
+- Edges: `total`, the number of faculty at institution j with a doctorate from institution i; `men` and `women`, the same count by gender (faculty whose gender could not be determined are counted only in `total`)."""
tags = ['Economic', 'Employment', 'Weighted', 'Metadata']
url = 'https://github.com/LarremoreLab/us-faculty-hiring-networks'
citation = [('Wapman, K.H., Zhang, S., Clauset, A., Larremore, D. B., "Quantifying hierarchy and dynamics in US faculty hiring and retention." Nature (2022).', 'https://doi.org/10.1038/s41586-022-05222-x')]
@@ -184,6 +189,7 @@ def parse(alts=None):
g.ep.men = g.new_ep("int")
g.ep.women = g.new_ep("int")
+ # Only the institutions that occur in this network's edges
vs = {}
def get_v(vid, vname):
if vid in vs:
@@ -205,30 +211,36 @@ def parse(alts=None):
else:
selector = "Academia"
- reader = csv.reader(fs[0], delimiter=",", quotechar='"')
- for i, row in enumerate(reader):
- if i == 0:
- continue
- tl, tv, tid, tname, sid, sname, tot, m, w = row
- if sid == "":
- assert(tot == '' or float(tot) == 0)
+ def selected(row):
+ return (row["TaxonomyLevel"] == selector and
+ row["TaxonomyValue"] == sel_val)
+
+ def num(x):
+ return int(float(x)) if x != "" else 0
+
+ for row in csv.DictReader(fs[0]):
+ if not selected(row) or row["DegreeInstitutionId"] == "":
continue
- s = get_v(int(float(sid)), sname)
- t = get_v(int(float(tid)), tname)
- if row[0] == selector and row[1] == sel_val:
- e = g.add_edge(s, t)
- g.ep.total[e] = float(tot)
- g.ep.men[e] = float(m)
- g.ep.women[e] = float(w)
-
- g.vp.non_attrition = g.new_vp("int")
- g.vp.attrition = g.new_vp("int")
- reader = csv.reader(fs[1], delimiter=",", quotechar='"')
- for i, row in enumerate(reader):
- if i == 0:
+ s = get_v(num(row["DegreeInstitutionId"]),
+ row["DegreeInstitutionName"])
+ t = get_v(num(row["InstitutionId"]), row["InstitutionName"])
+ e = g.add_edge(s, t)
+ g.ep.total[e] = num(row["Total"])
+ g.ep.men[e] = num(row["Men"])
+ g.ep.women[e] = num(row["Women"])
+
+ # Institutions ranked in this network (the US PhD-granting
+ # institutions that make up the network analysed by the
+ # authors), and their attrition counts; -1 where not available.
+ g.vp.ranked = g.new_vp("bool")
+ g.vp.non_attrition = g.new_vp("int", val=-1)
+ g.vp.attrition = g.new_vp("int", val=-1)
+ for row in csv.DictReader(fs[1]):
+ if not selected(row):
continue
- v = get_v(int(float(row[0])), row[1])
- g.vp.non_attrition[v] = int(float(row[4]))
- g.vp.attrition[v] = int(float(row[5]))
+ v = get_v(num(row["InstitutionId"]), row["InstitutionName"])
+ g.vp.ranked[v] = True
+ g.vp.non_attrition[v] = num(row["NonAttritionEvents"])
+ g.vp.attrition[v] = num(row["AttritionEvents"])
yield alt, g
Update copyright information 73a4f0d
diff --git a/entries/faculty_hiring_us/__init__.py b/entries/faculty_hiring_us/__init__.py
index d0e008f..f6f2bf1 100644
--- a/entries/faculty_hiring_us/__init__.py
+++ b/entries/faculty_hiring_us/__init__.py
@@ -1,7 +1,7 @@
#! /usr/bin/env python
# -*- coding: utf-8 -*-
#
-# Copyright (C) 2020-2024 Tiago de Paula Peixoto <tiago@skewed.de>
+# Copyright (C) 2020-2026 Tiago de Paula Peixoto <tiago@skewed.de>
#
# This program is free software: you can redistribute it and/or modify it under
# the terms of the GNU Affero General Public License as published by the Free
Update copyright information 3d288ea
diff --git a/entries/faculty_hiring_us/__init__.py b/entries/faculty_hiring_us/__init__.py
index 0763aee..d0e008f 100644
--- a/entries/faculty_hiring_us/__init__.py
+++ b/entries/faculty_hiring_us/__init__.py
@@ -1,7 +1,7 @@
#! /usr/bin/env python
# -*- coding: utf-8 -*-
#
-# Copyright (C) 2020-2023 Tiago de Paula Peixoto <tiago@skewed.de>
+# Copyright (C) 2020-2024 Tiago de Paula Peixoto <tiago@skewed.de>
#
# This program is free software: you can redistribute it and/or modify it under
# the terms of the GNU Affero General Public License as published by the Free
Update copyright information 8d005ae
diff --git a/entries/faculty_hiring_us/__init__.py b/entries/faculty_hiring_us/__init__.py
index c4d5c76..0763aee 100644
--- a/entries/faculty_hiring_us/__init__.py
+++ b/entries/faculty_hiring_us/__init__.py
@@ -1,7 +1,7 @@
#! /usr/bin/env python
# -*- coding: utf-8 -*-
#
-# Copyright (C) 2021 Tiago de Paula Peixoto <tiago@skewed.de>
+# Copyright (C) 2020-2023 Tiago de Paula Peixoto <tiago@skewed.de>
#
# This program is free software: you can redistribute it and/or modify it under
# the terms of the GNU Affero General Public License as published by the Free
Add faculty_hiring_us 09ae740
diff --git a/entries/faculty_hiring_us/__init__.py b/entries/faculty_hiring_us/__init__.py
new file mode 100644
index 0000000..c4d5c76
--- /dev/null
+++ b/entries/faculty_hiring_us/__init__.py
@@ -0,0 +1,234 @@
+#! /usr/bin/env python
+# -*- coding: utf-8 -*-
+#
+# Copyright (C) 2021 Tiago de Paula Peixoto <tiago@skewed.de>
+#
+# This program is free software: you can redistribute it and/or modify it under
+# the terms of the GNU Affero General Public License as published by the Free
+# Software Foundation, either version 3 of the License, or (at your option) any
+# later version.
+#
+# This program is distributed in the hope that it will be useful, but WITHOUT
+# ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
+# FOR A PARTICULAR PURPOSE. See the GNU Affero General Public License for more
+# details.
+#
+# You should have received a copy of the GNU Affero General Public License along
+# with this program. If not, see <http://www.gnu.org/licenses/>.
+
+from .. import *
+
+title = "Faculty hiring networks in the US (2022)"
+description = """Networks of faculty hiring for all PhD-granting US universities over the decade 2011–2020. Each node is a PhD-granting institution, and a directed edge (i,j) indicates that a person received their PhD from node i and was tenure-track faculty at node j during time of collection (2011-2020). This dataset is divided into separate networks for all 107 fields, as well as aggregate networks for 8 domains, and an overall network for all of academia. Edge properties include the total count of hires, as well as separate counts for men and women."""
+tags = ['Economic', 'Employment', 'Weighted', 'Metadata']
+url = 'https://github.com/LarremoreLab/us-faculty-hiring-networks'
+citation = [('Wapman, K.H., Zhang, S., Clauset, A., Larremore, D. B., "Quantifying hierarchy and dynamics in US faculty hiring and retention." Nature (2022).', 'https://doi.org/10.1038/s41586-022-05222-x')]
+icon_hash = None
+ustream_license = None
+upstream_prefix = 'https://raw.githubusercontent.com/LarremoreLab/us-faculty-hiring-networks/main/data'
+
+fields = [
+ 'Accounting',
+ 'Aerospace Engineering',
+ 'Agricultural Economics',
+ 'Agricultural Engineering',
+ 'Agronomy',
+ 'Anatomy',
+ 'Animal Sciences',
+ 'Anthropology',
+ 'Architecture',
+ 'Art History and Criticism',
+ 'Asian Languages',
+ 'Asian Studies',
+ 'Astronomy',
+ 'Atmospheric Sciences and Meteorology',
+ 'Biochemistry',
+ 'Biological Sciences',
+ 'Biomedical Engineering',
+ 'Biophysics',
+ 'Biostatistics',
+ 'Business Administration',
+ 'Cell Biology',
+ 'Chemical Engineering',
+ 'Chemistry',
+ 'Civil Engineering',
+ 'Classics and Classical Languages',
+ 'Communication Disorders and Sciences',
+ 'Comparative Literature',
+ 'Computer Engineering',
+ 'Computer Science',
+ 'Counselor Education',
+ 'Criminal Justice and Criminology',
+ 'Curriculum and Instruction',
+ 'Ecology',
+ 'Economics',
+ 'Education',
+ 'Education Administration',
+ 'Educational Psychology',
+ 'Electrical Engineering',
+ 'English Language and Literature',
+ 'Entomology',
+ 'Environmental Engineering',
+ 'Environmental Health Sciences',
+ 'Environmental Sciences',
+ 'Epidemiology',
+ 'Evolutionary Biology',
+ 'Exercise Science, Kinesiology, Rehab, Health',
+ 'Finance',
+ 'Food Science',
+ 'Forestry and Forest Resources',
+ 'French Language and Literature',
+ 'Gender Studies',
+ 'Genetics',
+ 'Geography',
+ 'Geology',
+ 'Germanic Languages and Literatures',
+ 'Health, Physical Education, Recreation',
+ 'History',
+ 'Horticulture',
+ 'Human Development and Family Sciences',
+ 'Immunology',
+ 'Industrial Engineering',
+ 'Information Science',
+ 'Information Technology',
+ 'International Affairs',
+ 'Linguistics',
+ 'Management',
+ 'Management Information Systems',
+ 'Marine Sciences',
+ 'Marketing',
+ 'Materials Engineering',
+ 'Mathematics',
+ 'Mechanical Engineering',
+ 'Microbiology',
+ 'Molecular Biology',
+ 'Music',
+ 'Natural Resources',
+ 'Near and Middle Eastern Languages and Cultures',
+ 'Neuroscience',
+ 'Nursing',
+ 'Nutrition Sciences',
+ 'Operations Research',
+ 'Pathology',
+ 'Pharmaceutical Sciences',
+ 'Pharmacology',
+ 'Pharmacy',
+ 'Philosophy',
+ 'Physics',
+ 'Physiology',
+ 'Plant Pathology',
+ 'Plant Sciences',
+ 'Political Science',
+ 'Psychology',
+ 'Public Health',
+ 'Religious Studies',
+ 'Slavic Languages and Literatures',
+ 'Social Work',
+ 'Sociology',
+ 'Soil Science',
+ 'Spanish Language and Literature',
+ 'Special Education',
+ 'Speech and Hearing Sciences',
+ 'Statistics',
+ 'Systems Engineering',
+ 'Theatre Literature, History and Criticism',
+ 'Theological Studies',
+ 'Urban and Regional Planning',
+ 'Veterinary Medical Sciences'
+]
+
+domains = [
+ 'Applied Sciences',
+ 'Education',
+ 'Engineering',
+ 'Humanities',
+ 'Mathematics and Computing',
+ 'Medicine and Health',
+ 'Natural Sciences',
+ 'Social Sciences'
+]
+
+alt_names = {"academia" : "Academia"}
+
+for domain in domains:
+ alt_names["domain_" + domain.lower().replace(" ", "_")] = domain
+
+for field in fields:
+ alt_names["field_" + field.lower().replace(" ", "_").replace(",", "")] = field
+
+files = []
+for alt in alt_names.keys():
+ files += [(('edge-lists.csv', 'institution-stats.csv'), alt, None)]
+
+def fetch_upstream(force=False):
+ return fetch_upstream_files(__name__.split(".")[-1], upstream_prefix, files,
+ force)
+
+@cache_network()
+@coerce_props()
+@annotate()
+def parse(alts=None):
+ global files
+ name = __name__.split(".")[-1]
+ for fnames, alt, fmt in files:
+ if alts is not None and alt not in alts:
+ continue
+ if isinstance(fnames, str):
+ fnames = [fnames]
+ with ExitStack() as stack:
+ fs = [stack.enter_context(open_upstream_file(name, fn, "r")) for fn in fnames]
+ g = Graph()
+ g.vp.id = g.new_vp("int")
+ g.vp.name = g.new_vp("string")
+ g.ep.total = g.new_ep("int")
+ g.ep.men = g.new_ep("int")
+ g.ep.women = g.new_ep("int")
+
+ vs = {}
+ def get_v(vid, vname):
+ if vid in vs:
+ return vs[vid]
+ v = g.add_vertex()
+ vs[vid] = v
+ g.vp.name[v] = vname
+ g.vp.id[v] = vid
+ return v
+
+ sel_val = alt_names[alt]
+ g.gp.selector = g.new_gp("string")
+ g.gp.selector = sel_val
+
+ if alt.startswith("domain"):
+ selector = "Domain"
+ elif alt.startswith("field"):
+ selector = "Field"
+ else:
+ selector = "Academia"
+
+ reader = csv.reader(fs[0], delimiter=",", quotechar='"')
+ for i, row in enumerate(reader):
+ if i == 0:
+ continue
+ tl, tv, tid, tname, sid, sname, tot, m, w = row
+ if sid == "":
+ assert(tot == '' or float(tot) == 0)
+ continue
+ s = get_v(int(float(sid)), sname)
+ t = get_v(int(float(tid)), tname)
+ if row[0] == selector and row[1] == sel_val:
+ e = g.add_edge(s, t)
+ g.ep.total[e] = float(tot)
+ g.ep.men[e] = float(m)
+ g.ep.women[e] = float(w)
+
+ g.vp.non_attrition = g.new_vp("int")
+ g.vp.attrition = g.new_vp("int")
+ reader = csv.reader(fs[1], delimiter=",", quotechar='"')
+ for i, row in enumerate(reader):
+ if i == 0:
+ continue
+ v = get_v(int(float(row[0])), row[1])
+ g.vp.non_attrition[v] = int(float(row[4]))
+ g.vp.attrition[v] = int(float(row[5]))
+
+ yield alt, g