def figure8d(provider_name):
"""Shows distribution of publications by discipline for the specified provider.
Publications are publications by any UVA affiliated author.
However if multiple UVA authors collaborate on one paper, this counts for only one publication.
'Disciplines' is a column we derived from the pre-existing 'fields' column in the 1figr data.
Disciplines has mapped those field categories into more UVA specific language
Chart Type: Line
Y-Axis: Discipline
Y-Axis Data Source: Original 1Figr Dataset, reusable_functions.py
X-Axis: Number of Papers
X-Axis Data Source: Original 1Figr Dataset, reusable_functions.py
"""
original_1figr_data_with_disciplines = rf.make_disciplines_column()
subset_by_provider = original_1figr_data_with_disciplines.loc[
original_1figr_data_with_disciplines['Provider'] == provider_name]
disciplines_data = subset_by_provider.groupby(
['Discipline'], as_index=False).sum().values.tolist()
disciplines = []
publication_totals = []
for i in disciplines_data:
discipline_name = i[0]
disciplines.append(discipline_name)
discipline_publications = i[7]
publication_totals.append(
discipline_publications) #int() to remove decimal points
mpl.rcParams['ytick.major.width'] = 1
mpl.rcParams['xtick.major.width'] = 1
plt.figure(num=None, figsize=(8, 8))
plt.suptitle(
f'Distribution of Publications by Discipline for Provider: {provider_name} \n (Disciplines are specific to UVA)'
)
plot = plt.barh(disciplines, publication_totals, height=.8, color='green')
for i in plot:
score = i.get_width()
plt.text(
i.get_width() + 90, #sets x axis position of labels
i.get_y() + .35,
score,
ha='center',
va='center')
def figure8b(provider_name):
"""Shows distribution of current year article downloads (JR5) by discipline for the specified provider.
'Disciplines' is a column we derived from the pre-existing 'fields' column in the 1figr data.
Disciplines has mapped those field categories into more UVA specific language
Chart Type: Line
Y-Axis: Discipline
Y-Axis Data Source: Original 1Figr Dataset, reusable_functions.py
X-Axis: Number of JR5 Downloads
X-Axis Data Source: Original 1Figr Dataset, reusable_functions.py
"""
original_1figr_data_with_disciplines = rf.make_disciplines_column()
subset_by_provider = original_1figr_data_with_disciplines.loc[
original_1figr_data_with_disciplines['Provider'] == provider_name]
disciplines_data = subset_by_provider.groupby(
['Discipline'], as_index=False).sum().values.tolist()
disciplines = []
citation_totals = []
for i in disciplines_data:
discipline_name = i[0]
disciplines.append(discipline_name)
jr5_downloads = i[5]
citation_totals.append(jr5_downloads) #int() to remove decimal points
mpl.rcParams['ytick.major.width'] = 1
mpl.rcParams['xtick.major.width'] = 1
plt.figure(num=None, figsize=(8, 8))
plt.suptitle(
f'Distribution of Citations by Discipline for Provider: {provider_name} \n (Disciplines are specific to UVA)'
)
plot = plt.barh(disciplines, citation_totals, height=.8, color='green')
for i in plot:
score = i.get_width()
plt.text(
i.get_width() + 2300, #sets x axis position of labels
i.get_y() + .35,
score,
ha='center',
va='center')
def figure8h():
"""First creates 'discipline' field for all providers in the Original 1figr dataset.
Then splits elsevier into elsevier freedom provider and elsevier subscribed titles provider
This is counting papers by discipline for the subscribed titles and freedom collection providers
Chart Type: Dot Plot/Scatter Plot
Y-Axis: Discipline
Y-Axis Data Source: Original 1Figr Dataset, Journals Per Provider, Provider
Elsevier_2019, Subscribed Journal List 2019
X-Axis: Number of Papers
X-Axis Data Source: Original 1Figr Dataset, Journals Per Provider, Provider
Elsevier_2019, Subscribed Journal List 2019
"""
original_1figr_data_with_disciplines = rf.make_disciplines_column()
subscribed_titles_provider = rf.make_elsevier_subscribed_titles_with_disciplines(
original_1figr_data_with_disciplines)
freedom_collection_provider = rf.make_freedom_collection_provider_with_disciplines(
original_1figr_data_with_disciplines)
unique_disciplines = original_1figr_data_with_disciplines[
'Discipline'].unique().tolist()
for i in unique_disciplines:
if type(i) == float:
unique_disciplines.remove(i)
unique_disciplines.sort()
stats_by_discipline = []
for discipline in unique_disciplines:
subscribed_subset_by_discipline = subscribed_titles_provider.loc[
subscribed_titles_provider['Discipline'] == discipline]
subscribed_jr5_downloads = subscribed_subset_by_discipline[
'Papers'].sum()
freedom_subset_by_discipline = freedom_collection_provider.loc[
freedom_collection_provider['Discipline'] == discipline]
freedom_jr5_downloads = freedom_subset_by_discipline['Papers'].sum()
stats_by_discipline.append(
(discipline, subscribed_jr5_downloads, freedom_jr5_downloads))
#sorts disciplines by sum of total # of jr5 downloads
arrangement = sorted(stats_by_discipline, key=lambda x: (x[1] + x[2]))
#splitting elements of tuples in arrangement into lists so it is easier to plot
disciplines_list = [i[0] for i in arrangement]
subscribed_total = [i[1] for i in arrangement]
freedom_total = [i[2] for i in arrangement]
mpl.rcParams['ytick.major.width'] = 1
mpl.rcParams['xtick.major.width'] = 1
plt.figure(num=None, figsize=(8, 8))
plt.suptitle(f'Papers (Published Articles) by Discipline')
plot = plt.scatter(subscribed_total, disciplines_list, color='blue')
plot2 = plt.scatter(freedom_total, disciplines_list, color='orange')
subscribed_legend_label = mpatches.Patch(color='blue',
label='Elsevier Subscribed')
freedom_legend_label = mpatches.Patch(color='orange',
label='Elsevier Freedom')
plt.xlabel('Number of Papers')
plt.legend(loc='lower right',
handles=[subscribed_legend_label, freedom_legend_label])