scholarpy module¶
Main module.
Dsl (Dsl)
¶
Source code in scholarpy/scholarpy.py
class Dsl(dimcli.Dsl):
def __init__(self, key=None, **kwargs):
"""Initialize the DSL."""
if key is None:
key = os.environ.get("DIM_TOKEN")
if key is None:
webbrowser.open("https://api-lab.dimensions.ai")
raise ValueError(
"No Dimensions API key can be found. Please go to https://www.dimensions.ai/contact-us to request an API key."
)
dimcli.login(key=key)
super().__init__(**kwargs)
def search_researcher_by_id(
self,
id,
fields=None,
iterative=False,
limit=1000,
return_df=False,
**kwargs,
):
"""Search a researcher by ID.
Args:
id (str): The ID of the researcher. For example, ur.010551261751.12
fields (str, optional): The fields to return. For example, [basics+extras]. Defaults to None.
iterative (bool, optional): If True, the query will be iterative. Defaults to False.
limit (int, optional): The number of results to return. Defaults to 1000.
return_df (bool, optional): If True, the results will be returned as a dataframe. Defaults to False.
Returns:
dimcli.DslDataset: JSON data of the results.
"""
"""Search a researcher by a Dimensions Research ID. For example, ur.010551261751.12"""
if fields is None:
fields = "[basics+extras]"
query = f'search researchers where id="{id}" return researchers{fields}'
if iterative:
result = self.query_iterative(query, limit=limit, **kwargs)
else:
query = f"{query} limit {limit}"
result = self.query(query)
if return_df:
df2 = result.as_dataframe().transpose()
df3 = pd.DataFrame(
{"index": df2.index.tolist(), "value": df2.values.tolist()}
)
df3["value"] = df3["value"]
print(type(df3["value"]))
return df3
else:
return result
def search_researcher_by_name(
self,
name,
fields=None,
iterative=False,
limit=1000,
return_list=False,
**kwargs,
):
"""Search a researcher by name.
Args:
name (str): The name of the researcher.
fields (str, optional): The fields to return. For example, [basics+extras]. Defaults to None.
iterative (bool, optional): If True, the query will be iterative. Defaults to False.
limit (int, optional): The number of results to return. Defaults to 1000.
return_list (bool, optional): If True, the results will be returned as a list. Defaults to False.
Returns:
dimcli.DslDataset: JSON data of the results.
"""
if fields is None:
fields = "[basics+extras]"
query = f'search researchers for "\\"{name}\\"" where obsolete=0 and total_publications>0 return researchers{fields}'
if iterative:
result = self.query_iterative(query, limit=limit)
else:
query = f"{query} limit {limit}"
result = self.query(query)
if return_list:
df = result.as_dataframe()
if not df.empty:
# df.sort_values(by=["id"], inplace=True)
df["current_research_org_name"] = df["current_research_org.name"]
df.sort_values("current_research_org_name", inplace=True)
if not df.empty:
items = []
for row in df.itertuples():
item = (
str(row.first_name)
+ " "
+ str(row.last_name)
+ " | "
+ str(row.id)
+ " | "
+ str(row.current_research_org_name)
)
items.append(item)
return result, items
else:
return result, None
else:
return result
def search_researcher_collaborators(self, id, pubs=None):
"""Search collaborators of a researcher.
Args:
id (str): The ID of the researcher. For example, ur.010551261751.12
pubs (dimcli.DslDataset, optional): The publications of the researcher. Defaults to None.
Returns:
pd.DataFrame: A dataframe of the collaborators.
"""
if pubs is None:
pubs = self.search_pubs_by_researcher_id(id)
df = pubs.as_dataframe_authors()
df = df[df["researcher_id"] != id]
df["Name"] = df["first_name"].str.split(
" ").str[0] + " " + df["last_name"]
names = df.drop_duplicates("Name").copy()
affiliations = names["affiliations"].values.tolist()
institutions = []
for a in enumerate(affiliations):
try:
institution = a[1][0]["name"]
institutions.append(institution)
except:
institutions.append("")
names["Institution"] = institutions
names = names[["Name", "Institution"]]
result = pd.DataFrame(df["Name"].value_counts())
result = pd.DataFrame(
{"Name": result.index, "Count": result["Name"].values})
return result.merge(names, on="Name")
def search_orcid_by_name(
self,
name,
fields=None,
iterative=False,
limit=1000,
return_list=False,
**kwargs,
):
"""Search a researcher orcid by name.
Args:
name (str): The name of the researcher.
fields (str, optional): The fields to return. For example, [basics+extras]. Defaults to None.
iterative (bool, optional): If True, the query will be iterative. Defaults to False.
limit (int, optional): The number of results to return. Defaults to 1000.
return_list (bool, optional): If True, the results will be returned as a list. Defaults to False.
Returns:
pd.DataFrame: A dataframe of the results.
"""
result = self.search_researcher_by_name(
name, fields=fields, iterative=iterative, limit=limit, return_list=False
)
df = result.as_dataframe()
if "orcid_id" in df.columns:
df = df[~df["orcid_id"].isnull()]
ids = [id[0] for id in df["orcid_id"].values.tolist()]
df["orcid_id"] = ids
# df.sort_values(by=["orcid_id"], inplace=True)
df["current_research_org_name"] = df["current_research_org.name"]
df.sort_values("current_research_org_name", inplace=True)
if return_list:
df["uid"] = (
df["first_name"]
+ " "
+ df["last_name"]
+ " | "
+ df["orcid_id"]
+ " | "
+ df["current_research_org.name"]
)
df = df[~df["uid"].isnull()]
return df["uid"].tolist()
else:
return df
else:
return None
def search_journal_by_id(self, id, fields=None, **kwargs):
"""Search a journal by ID.
Args:
id (str): The ID of the journal. For example, jour.1018957
fields (str, optional): The fields to return. For example, [basics+extras]. Defaults to None.
Returns:
dimcli.DslDataset: JSON data of the results.
"""
if fields is None:
fields = ""
query = f'search source_titles where id="{id}" return source_titles{fields}'
return self.query(query)
def search_journal_by_title(
self,
title,
exact_match=True,
fields=None,
iterative=False,
limit=1000,
**kwargs,
):
"""Search a journal by title.
Args:
title (str): The title of the journal.
exact_match (bool, optional): If True, the title must be an exact match. Defaults to True.
fields (str, optional): The fields to return. For example, [basics+extras]. Defaults to None.
iterative (bool, optional): If True, the query will be iterative. Defaults to False.
limit (int, optional): The number of results to return. Defaults to 1000.
Returns:
dimcli.DslDataset: JSON data of the results.
"""
if fields is None:
fields = ""
query = f'search source_titles for "{title}" return source_titles{fields}'
if iterative:
result = self.query_iterative(query, limit=limit)
else:
query = f"{query} limit {limit}"
result = self.query(query)
try:
if exact_match:
df = result.as_dataframe()
sub_df = df[df["title"].str.lower() == title.lower()]
journal_id = sub_df["id"].values.tolist()[0]
query = f'search source_titles where id="{journal_id}" return source_titles{fields}'
return self.query(query)
else:
return result
except Exception as e:
print("No journal can be found.")
return None
def search_org_by_id(self, id, fields=None, **kwargs):
"""Search an organization by ID. For example, grid.411461.7
Args:
id (str): The ID of the organization. For example, org.010551261751.12
fields (str, optional): The fields to return. For example, [basics+extras]. Defaults to None.
Returns:
dimcli.DslDataset: JSON data of the results.
"""
if fields is None:
fields = ""
query = f'search organizations where id="{id}" return organizations{fields}'
return self.query(query)
def search_org_by_name(
self, name, exact_match=True, fields=None, iterative=False, limit=1000, return_list=False, **kwargs
):
"""Search an organization by name.
Args:
name (str): The name of the organization.
exact_match (bool, optional): If True, the name must be an exact match. Defaults to True.
fields (str, optional): The fields to return. For example, [basics+extras]. Defaults to None.
iterative (bool, optional): If True, the query will be iterative. Defaults to False.
limit (int, optional): The number of results to return. Defaults to 1000.
return_list (bool, optional): If True, the results will be returned as a list. Defaults to False.
Returns:
dimcli.DslDataset: JSON data of the results.
"""
if fields is None:
fields = ""
query = f'search organizations for "\\"{name}\\"" return organizations{fields}'
if iterative:
result = self.query_iterative(query, limit=limit)
else:
query = f"{query} limit {limit}"
result = self.query(query)
try:
if exact_match:
df = result.as_dataframe()
sub_df = df[df["name"].str.lower() == name.lower()]
org_id = sub_df["id"].values.tolist()[0]
query = f'search organizations where id="{org_id}" return organizations{fields}'
result = self.query(query)
if return_list:
df = result.as_dataframe()
if not df.empty:
df.sort_values("name", inplace=True)
df["name_id"] = df["id"] + " | " + df["name"]
orgs = df["name_id"].values.tolist()
return orgs
else:
return None
else:
return result
except Exception as e:
print("No organization can be found.")
return None
def search_pubs_by_researcher_id(
self,
id,
start_year=None,
end_year=None,
fields=None,
iterative=False,
limit=1000,
**kwargs,
):
"""Search publications by researcher ID.
Args:
id (str): The ID of the researcher. For example, res.010551261751.12
start_year (int, optional): The start year of the publication. Defaults to None.
end_year (int, optional): The end year of the publication. Defaults to None.
fields (str, optional): The fields to return. For example, [basics+extras]. Defaults to None.
iterative (bool, optional): If True, the query will be iterative. Defaults to False.
limit (int, optional): The number of results to return. Defaults to 1000.
Returns:
dimcli.DslDataset: JSON data of the results.
"""
if fields is None:
fields = "[basics+authors_count+times_cited+dimensions_url]"
if (start_year is not None) and (end_year is not None):
query = f'search publications where researchers.id="{id}" and year>={start_year} and year<={end_year} return publications{fields}'
elif start_year is not None:
query = f'search publications where researchers.id="{id}" and year>={start_year} return publications{fields}'
elif end_year is not None:
query = f'search publications where researchers.id="{id}" and year<={end_year} return publications{fields}'
else:
query = f'search publications where researchers.id="{id}" return publications{fields}'
if iterative:
result = self.query_iterative(query, limit=limit)
else:
query = f"{query} limit {limit}"
result = self.query(query)
return result
def search_pubs_by_journal_id(
self,
id,
start_year=None,
end_year=None,
fields=None,
iterative=False,
limit=1000,
**kwargs,
):
"""Search publications by journal ID.
Args:
id (str): The ID of the journal. For example, jour.1018957
start_year (int, optional): The start year of the publication. Defaults to None.
end_year (int, optional): The end year of the publication. Defaults to None.
fields (str, optional): The fields to return. For example, [basics+extras]. Defaults to None.
iterative (bool, optional): If True, the query will be iterative. Defaults to False.
limit (int, optional): The number of results to return. Defaults to 1000.
Returns:
dimcli.DslDataset: JSON data of the results.
"""
if fields is None:
fields = ""
if (start_year is not None) and (end_year is not None):
query = f'search publications where journal.id="{id}" and year>={start_year} and year<={end_year} return publications{fields}'
elif start_year is not None:
query = f'search publications where journal.id="{id}" and year>={start_year} return publications{fields}'
elif end_year is not None:
query = f'search publications where journal.id="{id}" and year<={end_year} return publications{fields}'
else:
query = f'search publications where journal.id="{id}" return publications{fields}'
if iterative:
result = self.query_iterative(query, limit=limit)
else:
query = f"{query} limit {limit}"
result = self.query(query)
return result
def search_pubs_by_org_id(
self,
id,
start_year=None,
end_year=None,
fields=None,
iterative=False,
limit=1000,
**kwargs,
):
"""Search publications by organization ID.
Args:
id (str): The ID of the organization. For example, grid.411461.7
start_year (int, optional): The start year of the publication. Defaults to None.
end_year (int, optional): The end year of the publication. Defaults to None.
fields (str, optional): The fields to return. For example, [basics+extras]. Defaults to None.
iterative (bool, optional): If True, the query will be iterative. Defaults to False.
limit (int, optional): The number of results to return. Defaults to 1000.
Returns:
dimcli.DslDataset: JSON data of the results.
"""
if fields is None:
fields = ""
if (start_year is not None) and (end_year is not None):
query = f'search publications where research_orgs="{id}" and year>={start_year} and year<={end_year} return publications{fields}'
elif start_year is not None:
query = f'search publications where research_orgs="{id}" and year>={start_year} return publications{fields}'
elif end_year is not None:
query = f'search publications where research_orgs="{id}" and year<={end_year} return publications{fields}'
else:
query = f'search publications where research_orgs="{id}" return publications{fields}'
if iterative:
result = self.query_iterative(query, limit=limit)
else:
query = f"{query} limit {limit}"
result = self.query(query)
return result
def search_pubs_by_keyword(
self,
keyword,
exact_match=True,
scope="title_abstract_only",
start_year=None,
end_year=None,
journal_id=None,
fields=None,
sorted_field="times_cited",
iterative=False,
limit=1000,
**kwargs,
):
"""Search publications by keyword.
Args:
keyword (str): The keyword to search.
exact_match (bool, optional): If True, the keyword will be matched exactly. Defaults to True.
scope (str, optional): The scope of the search. Defaults to "title_abstract_only".
start_year (int, optional): The start year of the publication. Defaults to None.
end_year (int, optional): The end year of the publication. Defaults to None.
fields (str, optional): The fields to return. For example, [basics+extras]. Defaults to None.
sorted_field (str, optional): The field to sort by. Defaults to "times_cited".
iterative (bool, optional): If True, the query will be iterative. Defaults to False.
limit (int, optional): The number of results to return. Defaults to 1000.
Raises:
ValueError: [description]
Returns:
dimcli.DslDataset: JSON data of the results.
"""
if exact_match:
exact = '\\"'
else:
exact = ""
if journal_id is not None:
journal = f'and journal.id="{journal_id}"'
else:
journal = ""
allowed_scopes = [
"authors",
"concepts",
"full_data",
"full_data_exact",
"title_abstract_only",
"title_only",
]
if scope not in allowed_scopes:
raise ValueError(f"scope must be one of {allowed_scopes}")
if fields is None:
fields = "[basics+altmetric+times_cited+field_citation_ratio+authors_count+doi+dimensions_url]"
if (start_year is not None) and (end_year is not None):
query = f'search publications in {scope} for "{exact}{keyword}{exact}" where year>={start_year} and year<={end_year} {journal} return publications{fields} sort by {sorted_field}'
elif start_year is not None:
query = f'search publications in {scope} for "{exact}{keyword}{exact}" where year>={start_year} {journal} return publications{fields} sort by {sorted_field}'
elif end_year is not None:
query = f'search publications in {scope} for "{exact}{keyword}{exact}" where year<={end_year} {journal} return publications{fields} sort by {sorted_field}'
else:
if journal_id is not None:
journal = f'where journal.id="{journal_id}"'
else:
journal = ""
query = f'search publications in {scope} for "{exact}{keyword}{exact}" {journal} return publications{fields} sort by {sorted_field}'
if iterative:
result = self.query_iterative(query, limit=limit)
else:
query = f"{query} limit {limit}"
result = self.query(query)
return result
def search_grants_by_keyword(
self,
keyword,
exact_match=True,
scope="title_only",
start_year=None,
end_year=None,
fields=None,
sorted_field="start_year",
iterative=False,
limit=1000,
**kwargs,
):
if exact_match:
exact = '\\"'
else:
exact = ""
allowed_scopes = [
"concepts",
"full_data",
"investigators",
"title_abstract_only",
"title_only",
]
if scope not in allowed_scopes:
raise ValueError(f"scope must be one of {allowed_scopes}")
if fields is None:
fields = "[basics+extras+dimensions_url]"
if end_year is not None:
end_year = str(end_year)
if len(str(end_year)) != 4:
raise ValueError("end_year must be a 4-digit number")
else:
end_year = str(end_year) + "-12-31"
if (start_year is not None) and (end_year is not None):
query = f'search grants in {scope} for "{exact}{keyword}{exact}" where start_year>={start_year} and end_date<="{end_year}" return grants{fields} sort by {sorted_field}'
elif start_year is not None:
query = f'search grants in {scope} for "{exact}{keyword}{exact}" where start_year>={start_year} return grants{fields} sort by {sorted_field}'
elif end_year is not None:
query = f'search grants in {scope} for "{exact}{keyword}{exact}" where end_date<="{end_year}" return grants{fields} sort by {sorted_field}'
else:
query = f'search grants in {scope} for "{exact}{keyword}{exact}" return grants{fields} sort by {sorted_field}'
if iterative:
result = self.query_iterative(query, limit=limit)
else:
query = f"{query} limit {limit}"
result = self.query(query)
return result
def h_index(self, id, iterative=False, limit=1000):
"""Get the h-index of a researcher.
Args:
id (str): The ID of the researcher. For example, res.010551261751.12
iterative (bool, optional): If True, the query will be iterative. Defaults to False.
limit (int, optional): The number of results to return. Defaults to 1000.
"""
def the_H_function(sorted_citations_list, n=1):
"""from a list of integers [n1, n2 ..] representing publications citations,
return the max list-position which is >= integer
eg
>>> the_H_function([10, 8, 5, 4, 3]) => 4
>>> the_H_function([25, 8, 5, 3, 3]) => 3
>>> the_H_function([1000, 20]) => 2
"""
if sorted_citations_list and sorted_citations_list[0] >= n:
return the_H_function(sorted_citations_list[1:], n + 1)
else:
return n - 1
def get_pubs_citations(researcher_id, iterative=False, limit=1000):
q = f'search publications where researchers.id = "{researcher_id}" return publications[times_cited] sort by times_cited'
if iterative:
result = self.query_iterative(q, limit=limit)
else:
q = f"{q} limit {limit}"
result = self.query(q)
return list(result.as_dataframe().fillna(0)["times_cited"])
return the_H_function(get_pubs_citations(id, iterative=iterative, limit=limit))
def researcher_pubs_stats(
self,
id,
start_year=None,
end_year=None,
iterative=False,
limit=1000,
return_plot=False,
**kwargs,
):
"""Get the publications stats of a researcher.
Args:
id (str): The ID of the researcher. For example, ur.010551261751.12
start_year (int, optional): The start year of the publication. Defaults to None.
end_year (int, optional): The end year of the publication. Defaults to None.
iterative (bool, optional): If True, the query will be iterative. Defaults to False.
limit (int, optional): The number of results to return. Defaults to 1000.
return_plot (bool, optional): If True, the plot will be returned. Defaults to False.
Returns:
pandas.DataFrame: The dataframe of the results.
"""
result = self.search_pubs_by_researcher_id(
id, start_year, end_year, iterative=iterative, limit=limit
)
pubs = result.as_dataframe()
df = pubs["year"].value_counts().sort_index()
df2 = pd.DataFrame({"year": df.index, "citations": df.values})
if return_plot:
return df.plot.bar(**kwargs)
else:
return df2
def researcher_pubs_authors(
self, id, start_year=None, end_year=None, iterative=False, limit=1000
):
"""Get the authors of a researcher's publications.
Args:
id (str): The ID of the researcher. For example, ur.010551261751.12
start_year (int, optional): The start year of the publication. Defaults to None.
end_year (int, optional): The end year of the publication. Defaults to None.
iterative (bool, optional): If True, the query will be iterative. Defaults to False.
limit (int, optional): The number of results to return. Defaults to 1000.
Returns:
pandas.DataFrame: The dataframe of the results.
"""
result = self.search_pubs_by_researcher_id(
id, start_year, end_year, iterative=iterative, limit=limit
)
pubs = result.as_dataframe()
authors = result.as_dataframe_authors()["pub_id"].value_counts()
df2 = pd.DataFrame({"id": authors.index, "authors": authors.values})
df = pubs.join(df2.set_index("id"), on="id")
return df
def researcher_annual_stats(self, data, geonames_df=None):
"""Get the annual stats of a researcher, including publications, collaborators, collaborating institutions, and cities.
Args:
data (dimcli.DslDataset): JSON data of the input. It can be derived from search_pubs_by_researcher_id().
geonames_df (pd.DataFrame, optional): The geonames dataframe. Defaults to None.
Returns:
pd.DataFrame: The dataframe of the results.
"""
pubs = data.as_dataframe()
years_dict = pubs[["id", "year"]].set_index("id").to_dict()["year"]
df = data.as_dataframe_authors()
df["name"] = df["first_name"] + " " + df["last_name"]
affiliations = df["affiliations"].values.tolist()
institutions = []
city_ids = []
years = []
cities = []
countries = []
latitudes = []
longitudes = []
ids = df["pub_id"].values.tolist()
for index, a in enumerate(affiliations):
try:
institution = a[0]["name"]
institutions.append(institution)
except:
institutions.append("")
try:
city_id = a[0]["city_id"]
city_ids.append(city_id)
except:
city_ids.append(0)
try:
city = a[0]["city"]
cities.append(city)
except:
cities.append("")
try:
country = a[0]["country"]
countries.append(country)
except:
countries.append("")
if geonames_df is not None:
try:
latitude, longitude = geoname_latlon(
city_ids[-1], geonames_df)
latitudes.append(latitude)
longitudes.append(longitude)
except:
latitudes.append(0)
longitudes.append(0)
years.append((years_dict[ids[index]]))
df["year"] = years
df["institution"] = institutions
df["city"] = cities
df["country"] = countries
df["city_id"] = city_ids
if geonames_df is not None:
df["latitude"] = latitudes
df["longitude"] = longitudes
pubs_stats = pubs.groupby("year").size()
collaborators_stats = (
df.groupby(["year", "name"]).size().groupby(level=0).size()
)
institutions_stats = (
df.groupby(["year", "institution"]).size().groupby(level=0).size()
)
cities_stats = df.groupby(
["year", "city_id"]).size().groupby(level=0).size()
df2 = pd.DataFrame(
{
"year": cities_stats.index,
"pubs": pubs_stats,
"collaborators": collaborators_stats,
"institutions": institutions_stats,
"cities": cities_stats,
}
)
if geonames_df is None:
return df2
else:
return (
df2,
df[
[
"name",
"year",
"institution",
"city",
"country",
"latitude",
"longitude",
]
],
)
def org_pubs_annual_stats(self, org_id, start_year=None, end_year=None, iterative=False, limit=1000, return_plot=False, **kwargs):
"""Search publications by organization ID.
Args:
org_id (str): The ID of the organization. For example, grid.411461.7
start_year (int, optional): The start year of the publication. Defaults to None.
end_year (int, optional): The end year of the publication. Defaults to None.
iterative (bool, optional): If True, the query will be iterative. Defaults to False.
limit (int, optional): The number of results to return. Defaults to 1000.
return_plot (bool, optional): If True, the plot of the results will be returned. Defaults to False.
Returns:
dimcli.DslDataset: JSON data of the results.
"""
if (start_year is not None) and (end_year is not None):
query = f'search publications where research_orgs="{org_id}" and year>={start_year} and year<={end_year} return year'
elif start_year is not None:
query = f'search publications where research_orgs="{org_id}" and year>={start_year} return year'
elif end_year is not None:
query = f'search publications where research_orgs="{org_id}" and year<={end_year} return year'
else:
query = f'search publications where research_orgs="{org_id}" return year'
if iterative:
result = self.query_iterative(query, limit=limit)
else:
query = f"{query} limit {limit}"
result = self.query(query)
df = result.as_dataframe()
df.rename(columns={"id": "year"}, inplace=True)
if not return_plot:
return df
else:
if not df.empty:
org_name = self.search_org_by_id(
org_id).as_dataframe()["name"][0]
fig = px.bar(df, x="year", y="count",
title=f"Publications from {org_name} - by year")
return df, fig
else:
return df, None
def org_grants_annual_stats(self, org_id, start_year=None, end_year=None, iterative=False, limit=100, return_plot=False, **kwargs):
"""Search publications by organization ID.
Args:
org_id (str): The ID of the organization. For example, grid.411461.7
start_year (int, optional): The start year of the publication. Defaults to None.
end_year (int, optional): The end year of the publication. Defaults to None.
iterative (bool, optional): If True, the query will be iterative. Defaults to False.
limit (int, optional): The number of results to return. Defaults to 1000.
return_plot (bool, optional): If True, the plot of the results will be returned. Defaults to False.
Returns:
dimcli.DslDataset: JSON data of the results.
"""
if (start_year is not None) and (end_year is not None):
# query = f'search grants where research_orgs="{org_id}" and start_year>={start_year} and end_date<="{end_year}-12-31" return start_year aggregate funding'
query = f'search grants where research_orgs="{org_id}" and start_year>={start_year} return start_year aggregate funding'
elif start_year is not None:
query = f'search grants where research_orgs="{org_id}" and start_year>={start_year} return start_year aggregate funding'
elif end_year is not None:
query = f'search grants where research_orgs="{org_id}" return start_year aggregate funding'
else:
query = f'search grants where research_orgs="{org_id}" return start_year aggregate funding'
# if limit is None and start_year is not None and end_year is not None:
# limit = end_year - start_year + 1
# else:
# limit = 30
if iterative:
result = self.query_iterative(query, limit=limit)
else:
query = f"{query} limit {limit}"
result = self.query(query)
df = result.as_dataframe()
df.rename(columns={"id": "year"}, inplace=True)
if not return_plot:
return df
else:
if not df.empty:
org_name = self.search_org_by_id(
org_id).as_dataframe()["name"][0]
fig_count = px.bar(df, x="year", y="count",
title=f"The number of grants for {org_name} - by year")
fig_amount = px.bar(df, x="year", y="funding",
title=f"The funding amount for {org_name} - by year")
return df, fig_count, fig_amount
else:
return df, None, None
def org_grant_funders(self, org_id, start_year=None, end_year=None, iterative=False, limit=20, return_plot=False, **kwargs):
"""Top funders of an organization.
Args:
org_id (str): The ID of the organization. For example, grid.411461.7
start_year (int, optional): The start year of the publication. Defaults to None.
end_year (int, optional): The end year of the publication. Defaults to None.
iterative (bool, optional): If True, the query will be iterative. Defaults to False.
limit (int, optional): The number of results to return. Defaults to 20.
return_plot (bool, optional): If True, the plot of the results will be returned. Defaults to False.
Returns:
dimcli.DslDataset: JSON data of the results.
"""
if (start_year is not None) and (end_year is not None):
query = f'search grants where research_orgs="{org_id}" and year>={start_year} and year<={end_year} return funders aggregate funding sort by funding'
elif start_year is not None:
query = f'search grants where research_orgs="{org_id}" and year>={start_year} return funders aggregate funding sort by funding'
elif end_year is not None:
query = f'search grants where research_orgs="{org_id}" and year<={end_year} return funders aggregate funding sort by funding'
else:
query = f'search grants where research_orgs="{org_id}" return funders aggregate funding sort by funding'
if iterative:
result = self.query_iterative(query, limit=limit)
else:
query = f"{query} limit {limit}"
result = self.query(query)
df = result.as_dataframe()
if not return_plot:
return df
else:
if not df.empty:
org_name = self.search_org_by_id(
org_id).as_dataframe()["name"][0]
fig = px.bar(df,
x="name", y="funding",
title=f"Funding for {org_name} - by funder")
return df, fig
else:
return df, None
def search_grants_by_org(self, org_id, start_year=None, end_year=None, iterative=False, limit=1000, **kwargs):
"""Search grants by organization id.
Args:
org_id (str): The ID of the organization. For example, grid.411461.7
start_year (int, optional): The start year of the publication. Defaults to None.
end_year (int, optional): The end year of the publication. Defaults to None.
iterative (bool, optional): If True, the query will be iterative. Defaults to False.
limit (int, optional): The number of results to return. Defaults to 20.
Returns:
dimcli.DslDataset: JSON data of the results.
"""
if (start_year is not None) and (end_year is not None):
query = f'search grants where research_orgs="{org_id}" and start_year>={start_year} return grants[basics+extras]'
elif start_year is not None:
query = f'search grants where research_orgs="{org_id}" and start_year>={start_year} return grants[basics+extras]'
elif end_year is not None:
query = f'search grants where research_orgs="{org_id}" and start_year<={end_year} return grants[basics+extras]'
else:
query = f'search grants where research_orgs="{org_id}" return grants[basics+extras]'
if iterative:
result = self.query_iterative(query, limit=limit)
else:
query = f"{query} limit {limit}"
result = self.query(query)
return result
def search_grants_by_researcher(self, researcher_id, start_year=None, end_year=None, iterative=False, limit=1000, **kwargs):
"""Search grants by researcher id.
Args:
researcher_id (str): The ID of the research. For example, ur.01361677540.55
start_year (int, optional): The start year of the publication. Defaults to None.
end_year (int, optional): The end year of the publication. Defaults to None.
iterative (bool, optional): If True, the query will be iterative. Defaults to False.
limit (int, optional): The number of results to return. Defaults to 1000.
Returns:
dimcli.DslDataset: JSON data of the results.
"""
if (start_year is not None) and (end_year is not None):
query = f'search grants where researchers="{researcher_id}" and start_year>={start_year} return grants[basics+extras]'
elif start_year is not None:
query = f'search grants where researchers="{researcher_id}" and start_year>={start_year} return grants[basics+extras]'
elif end_year is not None:
query = f'search grants where researchers="{researcher_id}" and start_year<={end_year} return grants[basics+extras]'
else:
query = f'search grants where researchers="{researcher_id}" return grants[basics+extras]'
if iterative:
result = self.query_iterative(query, limit=limit)
else:
query = f"{query} limit {limit}"
result = self.query(query)
return result
def org_pubs_most_cited(self, org_id, recent=False, iterative=False, limit=100, **kwargs):
if recent:
query = f"""search publications where research_orgs.id="{org_id}"
return publications[basics+recent_citations]
sort by recent_citations"""
else:
query = f"""search publications where research_orgs.id="{org_id}"
return publications[basics+times_cited]
sort by times_cited"""
if iterative:
result = self.query_iterative(query, limit=limit)
else:
query = f"{query} limit {limit}"
result = self.query(query)
return result
def org_pubs_top_areas(self, org_id, iterative=False, limit=1000, return_plot=False, **kwargs):
query = f"""search publications where research_orgs.id="{org_id}"
return publications[doi+title+times_cited+category_for+journal]
sort by times_cited"""
if iterative:
result = self.query_iterative(query, limit=limit)
else:
query = f"{query} limit {limit}"
result = self.query(query)
raw_df = result.as_dataframe()
dimcli.utils.normalize_key("category_for", result.publications, [])
df = pd.json_normalize(result.publications, record_path='category_for', meta=['doi', 'title', 'times_cited', ], errors='ignore' )
org_name = self.search_org_by_id(org_id).as_dataframe()["name"][0]
if return_plot:
area_fig = px.scatter(df,
x="times_cited", y="name",
marginal_x="histogram",
marginal_y="histogram",
hover_data=["doi", "title"],
height=600,
title=f"Publications from {org_name} - Research Areas vs. Citations")
# return df, area_fig
journal_fig = px.scatter(raw_df,
x="times_cited", y="journal.title",
marginal_x="histogram",
marginal_y="histogram",
height=600,
title=f"Publications from {org_name} - Journals vs. Citations")
return df, area_fig, journal_fig
else:
return df
__init__(self, key=None, **kwargs)
special
¶
Initialize the DSL.
Source code in scholarpy/scholarpy.py
def __init__(self, key=None, **kwargs):
"""Initialize the DSL."""
if key is None:
key = os.environ.get("DIM_TOKEN")
if key is None:
webbrowser.open("https://api-lab.dimensions.ai")
raise ValueError(
"No Dimensions API key can be found. Please go to https://www.dimensions.ai/contact-us to request an API key."
)
dimcli.login(key=key)
super().__init__(**kwargs)
h_index(self, id, iterative=False, limit=1000)
¶
Get the h-index of a researcher.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
id |
str |
The ID of the researcher. For example, res.010551261751.12 |
required |
iterative |
bool |
If True, the query will be iterative. Defaults to False. |
False |
limit |
int |
The number of results to return. Defaults to 1000. |
1000 |
Source code in scholarpy/scholarpy.py
def h_index(self, id, iterative=False, limit=1000):
"""Get the h-index of a researcher.
Args:
id (str): The ID of the researcher. For example, res.010551261751.12
iterative (bool, optional): If True, the query will be iterative. Defaults to False.
limit (int, optional): The number of results to return. Defaults to 1000.
"""
def the_H_function(sorted_citations_list, n=1):
"""from a list of integers [n1, n2 ..] representing publications citations,
return the max list-position which is >= integer
eg
>>> the_H_function([10, 8, 5, 4, 3]) => 4
>>> the_H_function([25, 8, 5, 3, 3]) => 3
>>> the_H_function([1000, 20]) => 2
"""
if sorted_citations_list and sorted_citations_list[0] >= n:
return the_H_function(sorted_citations_list[1:], n + 1)
else:
return n - 1
def get_pubs_citations(researcher_id, iterative=False, limit=1000):
q = f'search publications where researchers.id = "{researcher_id}" return publications[times_cited] sort by times_cited'
if iterative:
result = self.query_iterative(q, limit=limit)
else:
q = f"{q} limit {limit}"
result = self.query(q)
return list(result.as_dataframe().fillna(0)["times_cited"])
return the_H_function(get_pubs_citations(id, iterative=iterative, limit=limit))
org_grant_funders(self, org_id, start_year=None, end_year=None, iterative=False, limit=20, return_plot=False, **kwargs)
¶
Top funders of an organization.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
org_id |
str |
The ID of the organization. For example, grid.411461.7 |
required |
start_year |
int |
The start year of the publication. Defaults to None. |
None |
end_year |
int |
The end year of the publication. Defaults to None. |
None |
iterative |
bool |
If True, the query will be iterative. Defaults to False. |
False |
limit |
int |
The number of results to return. Defaults to 20. |
20 |
return_plot |
bool |
If True, the plot of the results will be returned. Defaults to False. |
False |
Returns:
| Type | Description |
|---|---|
dimcli.DslDataset |
JSON data of the results. |
Source code in scholarpy/scholarpy.py
def org_grant_funders(self, org_id, start_year=None, end_year=None, iterative=False, limit=20, return_plot=False, **kwargs):
"""Top funders of an organization.
Args:
org_id (str): The ID of the organization. For example, grid.411461.7
start_year (int, optional): The start year of the publication. Defaults to None.
end_year (int, optional): The end year of the publication. Defaults to None.
iterative (bool, optional): If True, the query will be iterative. Defaults to False.
limit (int, optional): The number of results to return. Defaults to 20.
return_plot (bool, optional): If True, the plot of the results will be returned. Defaults to False.
Returns:
dimcli.DslDataset: JSON data of the results.
"""
if (start_year is not None) and (end_year is not None):
query = f'search grants where research_orgs="{org_id}" and year>={start_year} and year<={end_year} return funders aggregate funding sort by funding'
elif start_year is not None:
query = f'search grants where research_orgs="{org_id}" and year>={start_year} return funders aggregate funding sort by funding'
elif end_year is not None:
query = f'search grants where research_orgs="{org_id}" and year<={end_year} return funders aggregate funding sort by funding'
else:
query = f'search grants where research_orgs="{org_id}" return funders aggregate funding sort by funding'
if iterative:
result = self.query_iterative(query, limit=limit)
else:
query = f"{query} limit {limit}"
result = self.query(query)
df = result.as_dataframe()
if not return_plot:
return df
else:
if not df.empty:
org_name = self.search_org_by_id(
org_id).as_dataframe()["name"][0]
fig = px.bar(df,
x="name", y="funding",
title=f"Funding for {org_name} - by funder")
return df, fig
else:
return df, None
org_grants_annual_stats(self, org_id, start_year=None, end_year=None, iterative=False, limit=100, return_plot=False, **kwargs)
¶
Search publications by organization ID.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
org_id |
str |
The ID of the organization. For example, grid.411461.7 |
required |
start_year |
int |
The start year of the publication. Defaults to None. |
None |
end_year |
int |
The end year of the publication. Defaults to None. |
None |
iterative |
bool |
If True, the query will be iterative. Defaults to False. |
False |
limit |
int |
The number of results to return. Defaults to 1000. |
100 |
return_plot |
bool |
If True, the plot of the results will be returned. Defaults to False. |
False |
Returns:
| Type | Description |
|---|---|
dimcli.DslDataset |
JSON data of the results. |
Source code in scholarpy/scholarpy.py
def org_grants_annual_stats(self, org_id, start_year=None, end_year=None, iterative=False, limit=100, return_plot=False, **kwargs):
"""Search publications by organization ID.
Args:
org_id (str): The ID of the organization. For example, grid.411461.7
start_year (int, optional): The start year of the publication. Defaults to None.
end_year (int, optional): The end year of the publication. Defaults to None.
iterative (bool, optional): If True, the query will be iterative. Defaults to False.
limit (int, optional): The number of results to return. Defaults to 1000.
return_plot (bool, optional): If True, the plot of the results will be returned. Defaults to False.
Returns:
dimcli.DslDataset: JSON data of the results.
"""
if (start_year is not None) and (end_year is not None):
# query = f'search grants where research_orgs="{org_id}" and start_year>={start_year} and end_date<="{end_year}-12-31" return start_year aggregate funding'
query = f'search grants where research_orgs="{org_id}" and start_year>={start_year} return start_year aggregate funding'
elif start_year is not None:
query = f'search grants where research_orgs="{org_id}" and start_year>={start_year} return start_year aggregate funding'
elif end_year is not None:
query = f'search grants where research_orgs="{org_id}" return start_year aggregate funding'
else:
query = f'search grants where research_orgs="{org_id}" return start_year aggregate funding'
# if limit is None and start_year is not None and end_year is not None:
# limit = end_year - start_year + 1
# else:
# limit = 30
if iterative:
result = self.query_iterative(query, limit=limit)
else:
query = f"{query} limit {limit}"
result = self.query(query)
df = result.as_dataframe()
df.rename(columns={"id": "year"}, inplace=True)
if not return_plot:
return df
else:
if not df.empty:
org_name = self.search_org_by_id(
org_id).as_dataframe()["name"][0]
fig_count = px.bar(df, x="year", y="count",
title=f"The number of grants for {org_name} - by year")
fig_amount = px.bar(df, x="year", y="funding",
title=f"The funding amount for {org_name} - by year")
return df, fig_count, fig_amount
else:
return df, None, None
org_pubs_annual_stats(self, org_id, start_year=None, end_year=None, iterative=False, limit=1000, return_plot=False, **kwargs)
¶
Search publications by organization ID.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
org_id |
str |
The ID of the organization. For example, grid.411461.7 |
required |
start_year |
int |
The start year of the publication. Defaults to None. |
None |
end_year |
int |
The end year of the publication. Defaults to None. |
None |
iterative |
bool |
If True, the query will be iterative. Defaults to False. |
False |
limit |
int |
The number of results to return. Defaults to 1000. |
1000 |
return_plot |
bool |
If True, the plot of the results will be returned. Defaults to False. |
False |
Returns:
| Type | Description |
|---|---|
dimcli.DslDataset |
JSON data of the results. |
Source code in scholarpy/scholarpy.py
def org_pubs_annual_stats(self, org_id, start_year=None, end_year=None, iterative=False, limit=1000, return_plot=False, **kwargs):
"""Search publications by organization ID.
Args:
org_id (str): The ID of the organization. For example, grid.411461.7
start_year (int, optional): The start year of the publication. Defaults to None.
end_year (int, optional): The end year of the publication. Defaults to None.
iterative (bool, optional): If True, the query will be iterative. Defaults to False.
limit (int, optional): The number of results to return. Defaults to 1000.
return_plot (bool, optional): If True, the plot of the results will be returned. Defaults to False.
Returns:
dimcli.DslDataset: JSON data of the results.
"""
if (start_year is not None) and (end_year is not None):
query = f'search publications where research_orgs="{org_id}" and year>={start_year} and year<={end_year} return year'
elif start_year is not None:
query = f'search publications where research_orgs="{org_id}" and year>={start_year} return year'
elif end_year is not None:
query = f'search publications where research_orgs="{org_id}" and year<={end_year} return year'
else:
query = f'search publications where research_orgs="{org_id}" return year'
if iterative:
result = self.query_iterative(query, limit=limit)
else:
query = f"{query} limit {limit}"
result = self.query(query)
df = result.as_dataframe()
df.rename(columns={"id": "year"}, inplace=True)
if not return_plot:
return df
else:
if not df.empty:
org_name = self.search_org_by_id(
org_id).as_dataframe()["name"][0]
fig = px.bar(df, x="year", y="count",
title=f"Publications from {org_name} - by year")
return df, fig
else:
return df, None
researcher_annual_stats(self, data, geonames_df=None)
¶
Get the annual stats of a researcher, including publications, collaborators, collaborating institutions, and cities.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
data |
dimcli.DslDataset |
JSON data of the input. It can be derived from search_pubs_by_researcher_id(). |
required |
geonames_df |
pd.DataFrame |
The geonames dataframe. Defaults to None. |
None |
Returns:
| Type | Description |
|---|---|
pd.DataFrame |
The dataframe of the results. |
Source code in scholarpy/scholarpy.py
def researcher_annual_stats(self, data, geonames_df=None):
"""Get the annual stats of a researcher, including publications, collaborators, collaborating institutions, and cities.
Args:
data (dimcli.DslDataset): JSON data of the input. It can be derived from search_pubs_by_researcher_id().
geonames_df (pd.DataFrame, optional): The geonames dataframe. Defaults to None.
Returns:
pd.DataFrame: The dataframe of the results.
"""
pubs = data.as_dataframe()
years_dict = pubs[["id", "year"]].set_index("id").to_dict()["year"]
df = data.as_dataframe_authors()
df["name"] = df["first_name"] + " " + df["last_name"]
affiliations = df["affiliations"].values.tolist()
institutions = []
city_ids = []
years = []
cities = []
countries = []
latitudes = []
longitudes = []
ids = df["pub_id"].values.tolist()
for index, a in enumerate(affiliations):
try:
institution = a[0]["name"]
institutions.append(institution)
except:
institutions.append("")
try:
city_id = a[0]["city_id"]
city_ids.append(city_id)
except:
city_ids.append(0)
try:
city = a[0]["city"]
cities.append(city)
except:
cities.append("")
try:
country = a[0]["country"]
countries.append(country)
except:
countries.append("")
if geonames_df is not None:
try:
latitude, longitude = geoname_latlon(
city_ids[-1], geonames_df)
latitudes.append(latitude)
longitudes.append(longitude)
except:
latitudes.append(0)
longitudes.append(0)
years.append((years_dict[ids[index]]))
df["year"] = years
df["institution"] = institutions
df["city"] = cities
df["country"] = countries
df["city_id"] = city_ids
if geonames_df is not None:
df["latitude"] = latitudes
df["longitude"] = longitudes
pubs_stats = pubs.groupby("year").size()
collaborators_stats = (
df.groupby(["year", "name"]).size().groupby(level=0).size()
)
institutions_stats = (
df.groupby(["year", "institution"]).size().groupby(level=0).size()
)
cities_stats = df.groupby(
["year", "city_id"]).size().groupby(level=0).size()
df2 = pd.DataFrame(
{
"year": cities_stats.index,
"pubs": pubs_stats,
"collaborators": collaborators_stats,
"institutions": institutions_stats,
"cities": cities_stats,
}
)
if geonames_df is None:
return df2
else:
return (
df2,
df[
[
"name",
"year",
"institution",
"city",
"country",
"latitude",
"longitude",
]
],
)
researcher_pubs_authors(self, id, start_year=None, end_year=None, iterative=False, limit=1000)
¶
Get the authors of a researcher's publications.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
id |
str |
The ID of the researcher. For example, ur.010551261751.12 |
required |
start_year |
int |
The start year of the publication. Defaults to None. |
None |
end_year |
int |
The end year of the publication. Defaults to None. |
None |
iterative |
bool |
If True, the query will be iterative. Defaults to False. |
False |
limit |
int |
The number of results to return. Defaults to 1000. |
1000 |
Returns:
| Type | Description |
|---|---|
pandas.DataFrame |
The dataframe of the results. |
Source code in scholarpy/scholarpy.py
def researcher_pubs_authors(
self, id, start_year=None, end_year=None, iterative=False, limit=1000
):
"""Get the authors of a researcher's publications.
Args:
id (str): The ID of the researcher. For example, ur.010551261751.12
start_year (int, optional): The start year of the publication. Defaults to None.
end_year (int, optional): The end year of the publication. Defaults to None.
iterative (bool, optional): If True, the query will be iterative. Defaults to False.
limit (int, optional): The number of results to return. Defaults to 1000.
Returns:
pandas.DataFrame: The dataframe of the results.
"""
result = self.search_pubs_by_researcher_id(
id, start_year, end_year, iterative=iterative, limit=limit
)
pubs = result.as_dataframe()
authors = result.as_dataframe_authors()["pub_id"].value_counts()
df2 = pd.DataFrame({"id": authors.index, "authors": authors.values})
df = pubs.join(df2.set_index("id"), on="id")
return df
researcher_pubs_stats(self, id, start_year=None, end_year=None, iterative=False, limit=1000, return_plot=False, **kwargs)
¶
Get the publications stats of a researcher.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
id |
str |
The ID of the researcher. For example, ur.010551261751.12 |
required |
start_year |
int |
The start year of the publication. Defaults to None. |
None |
end_year |
int |
The end year of the publication. Defaults to None. |
None |
iterative |
bool |
If True, the query will be iterative. Defaults to False. |
False |
limit |
int |
The number of results to return. Defaults to 1000. |
1000 |
return_plot |
bool |
If True, the plot will be returned. Defaults to False. |
False |
Returns:
| Type | Description |
|---|---|
pandas.DataFrame |
The dataframe of the results. |
Source code in scholarpy/scholarpy.py
def researcher_pubs_stats(
self,
id,
start_year=None,
end_year=None,
iterative=False,
limit=1000,
return_plot=False,
**kwargs,
):
"""Get the publications stats of a researcher.
Args:
id (str): The ID of the researcher. For example, ur.010551261751.12
start_year (int, optional): The start year of the publication. Defaults to None.
end_year (int, optional): The end year of the publication. Defaults to None.
iterative (bool, optional): If True, the query will be iterative. Defaults to False.
limit (int, optional): The number of results to return. Defaults to 1000.
return_plot (bool, optional): If True, the plot will be returned. Defaults to False.
Returns:
pandas.DataFrame: The dataframe of the results.
"""
result = self.search_pubs_by_researcher_id(
id, start_year, end_year, iterative=iterative, limit=limit
)
pubs = result.as_dataframe()
df = pubs["year"].value_counts().sort_index()
df2 = pd.DataFrame({"year": df.index, "citations": df.values})
if return_plot:
return df.plot.bar(**kwargs)
else:
return df2
search_grants_by_org(self, org_id, start_year=None, end_year=None, iterative=False, limit=1000, **kwargs)
¶
Search grants by organization id.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
org_id |
str |
The ID of the organization. For example, grid.411461.7 |
required |
start_year |
int |
The start year of the publication. Defaults to None. |
None |
end_year |
int |
The end year of the publication. Defaults to None. |
None |
iterative |
bool |
If True, the query will be iterative. Defaults to False. |
False |
limit |
int |
The number of results to return. Defaults to 20. |
1000 |
Returns:
| Type | Description |
|---|---|
dimcli.DslDataset |
JSON data of the results. |
Source code in scholarpy/scholarpy.py
def search_grants_by_org(self, org_id, start_year=None, end_year=None, iterative=False, limit=1000, **kwargs):
"""Search grants by organization id.
Args:
org_id (str): The ID of the organization. For example, grid.411461.7
start_year (int, optional): The start year of the publication. Defaults to None.
end_year (int, optional): The end year of the publication. Defaults to None.
iterative (bool, optional): If True, the query will be iterative. Defaults to False.
limit (int, optional): The number of results to return. Defaults to 20.
Returns:
dimcli.DslDataset: JSON data of the results.
"""
if (start_year is not None) and (end_year is not None):
query = f'search grants where research_orgs="{org_id}" and start_year>={start_year} return grants[basics+extras]'
elif start_year is not None:
query = f'search grants where research_orgs="{org_id}" and start_year>={start_year} return grants[basics+extras]'
elif end_year is not None:
query = f'search grants where research_orgs="{org_id}" and start_year<={end_year} return grants[basics+extras]'
else:
query = f'search grants where research_orgs="{org_id}" return grants[basics+extras]'
if iterative:
result = self.query_iterative(query, limit=limit)
else:
query = f"{query} limit {limit}"
result = self.query(query)
return result
search_grants_by_researcher(self, researcher_id, start_year=None, end_year=None, iterative=False, limit=1000, **kwargs)
¶
Search grants by researcher id.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
researcher_id |
str |
The ID of the research. For example, ur.01361677540.55 |
required |
start_year |
int |
The start year of the publication. Defaults to None. |
None |
end_year |
int |
The end year of the publication. Defaults to None. |
None |
iterative |
bool |
If True, the query will be iterative. Defaults to False. |
False |
limit |
int |
The number of results to return. Defaults to 1000. |
1000 |
Returns:
| Type | Description |
|---|---|
dimcli.DslDataset |
JSON data of the results. |
Source code in scholarpy/scholarpy.py
def search_grants_by_researcher(self, researcher_id, start_year=None, end_year=None, iterative=False, limit=1000, **kwargs):
"""Search grants by researcher id.
Args:
researcher_id (str): The ID of the research. For example, ur.01361677540.55
start_year (int, optional): The start year of the publication. Defaults to None.
end_year (int, optional): The end year of the publication. Defaults to None.
iterative (bool, optional): If True, the query will be iterative. Defaults to False.
limit (int, optional): The number of results to return. Defaults to 1000.
Returns:
dimcli.DslDataset: JSON data of the results.
"""
if (start_year is not None) and (end_year is not None):
query = f'search grants where researchers="{researcher_id}" and start_year>={start_year} return grants[basics+extras]'
elif start_year is not None:
query = f'search grants where researchers="{researcher_id}" and start_year>={start_year} return grants[basics+extras]'
elif end_year is not None:
query = f'search grants where researchers="{researcher_id}" and start_year<={end_year} return grants[basics+extras]'
else:
query = f'search grants where researchers="{researcher_id}" return grants[basics+extras]'
if iterative:
result = self.query_iterative(query, limit=limit)
else:
query = f"{query} limit {limit}"
result = self.query(query)
return result
search_journal_by_id(self, id, fields=None, **kwargs)
¶
Search a journal by ID.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
id |
str |
The ID of the journal. For example, jour.1018957 |
required |
fields |
str |
The fields to return. For example, [basics+extras]. Defaults to None. |
None |
Returns:
| Type | Description |
|---|---|
dimcli.DslDataset |
JSON data of the results. |
Source code in scholarpy/scholarpy.py
def search_journal_by_id(self, id, fields=None, **kwargs):
"""Search a journal by ID.
Args:
id (str): The ID of the journal. For example, jour.1018957
fields (str, optional): The fields to return. For example, [basics+extras]. Defaults to None.
Returns:
dimcli.DslDataset: JSON data of the results.
"""
if fields is None:
fields = ""
query = f'search source_titles where id="{id}" return source_titles{fields}'
return self.query(query)
search_journal_by_title(self, title, exact_match=True, fields=None, iterative=False, limit=1000, **kwargs)
¶
Search a journal by title.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
title |
str |
The title of the journal. |
required |
exact_match |
bool |
If True, the title must be an exact match. Defaults to True. |
True |
fields |
str |
The fields to return. For example, [basics+extras]. Defaults to None. |
None |
iterative |
bool |
If True, the query will be iterative. Defaults to False. |
False |
limit |
int |
The number of results to return. Defaults to 1000. |
1000 |
Returns:
| Type | Description |
|---|---|
dimcli.DslDataset |
JSON data of the results. |
Source code in scholarpy/scholarpy.py
def search_journal_by_title(
self,
title,
exact_match=True,
fields=None,
iterative=False,
limit=1000,
**kwargs,
):
"""Search a journal by title.
Args:
title (str): The title of the journal.
exact_match (bool, optional): If True, the title must be an exact match. Defaults to True.
fields (str, optional): The fields to return. For example, [basics+extras]. Defaults to None.
iterative (bool, optional): If True, the query will be iterative. Defaults to False.
limit (int, optional): The number of results to return. Defaults to 1000.
Returns:
dimcli.DslDataset: JSON data of the results.
"""
if fields is None:
fields = ""
query = f'search source_titles for "{title}" return source_titles{fields}'
if iterative:
result = self.query_iterative(query, limit=limit)
else:
query = f"{query} limit {limit}"
result = self.query(query)
try:
if exact_match:
df = result.as_dataframe()
sub_df = df[df["title"].str.lower() == title.lower()]
journal_id = sub_df["id"].values.tolist()[0]
query = f'search source_titles where id="{journal_id}" return source_titles{fields}'
return self.query(query)
else:
return result
except Exception as e:
print("No journal can be found.")
return None
search_orcid_by_name(self, name, fields=None, iterative=False, limit=1000, return_list=False, **kwargs)
¶
Search a researcher orcid by name.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
name |
str |
The name of the researcher. |
required |
fields |
str |
The fields to return. For example, [basics+extras]. Defaults to None. |
None |
iterative |
bool |
If True, the query will be iterative. Defaults to False. |
False |
limit |
int |
The number of results to return. Defaults to 1000. |
1000 |
return_list |
bool |
If True, the results will be returned as a list. Defaults to False. |
False |
Returns:
| Type | Description |
|---|---|
pd.DataFrame |
A dataframe of the results. |
Source code in scholarpy/scholarpy.py
def search_orcid_by_name(
self,
name,
fields=None,
iterative=False,
limit=1000,
return_list=False,
**kwargs,
):
"""Search a researcher orcid by name.
Args:
name (str): The name of the researcher.
fields (str, optional): The fields to return. For example, [basics+extras]. Defaults to None.
iterative (bool, optional): If True, the query will be iterative. Defaults to False.
limit (int, optional): The number of results to return. Defaults to 1000.
return_list (bool, optional): If True, the results will be returned as a list. Defaults to False.
Returns:
pd.DataFrame: A dataframe of the results.
"""
result = self.search_researcher_by_name(
name, fields=fields, iterative=iterative, limit=limit, return_list=False
)
df = result.as_dataframe()
if "orcid_id" in df.columns:
df = df[~df["orcid_id"].isnull()]
ids = [id[0] for id in df["orcid_id"].values.tolist()]
df["orcid_id"] = ids
# df.sort_values(by=["orcid_id"], inplace=True)
df["current_research_org_name"] = df["current_research_org.name"]
df.sort_values("current_research_org_name", inplace=True)
if return_list:
df["uid"] = (
df["first_name"]
+ " "
+ df["last_name"]
+ " | "
+ df["orcid_id"]
+ " | "
+ df["current_research_org.name"]
)
df = df[~df["uid"].isnull()]
return df["uid"].tolist()
else:
return df
else:
return None
search_org_by_id(self, id, fields=None, **kwargs)
¶
Search an organization by ID. For example, grid.411461.7
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
id |
str |
The ID of the organization. For example, org.010551261751.12 |
required |
fields |
str |
The fields to return. For example, [basics+extras]. Defaults to None. |
None |
Returns:
| Type | Description |
|---|---|
dimcli.DslDataset |
JSON data of the results. |
Source code in scholarpy/scholarpy.py
def search_org_by_id(self, id, fields=None, **kwargs):
"""Search an organization by ID. For example, grid.411461.7
Args:
id (str): The ID of the organization. For example, org.010551261751.12
fields (str, optional): The fields to return. For example, [basics+extras]. Defaults to None.
Returns:
dimcli.DslDataset: JSON data of the results.
"""
if fields is None:
fields = ""
query = f'search organizations where id="{id}" return organizations{fields}'
return self.query(query)
search_org_by_name(self, name, exact_match=True, fields=None, iterative=False, limit=1000, return_list=False, **kwargs)
¶
Search an organization by name.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
name |
str |
The name of the organization. |
required |
exact_match |
bool |
If True, the name must be an exact match. Defaults to True. |
True |
fields |
str |
The fields to return. For example, [basics+extras]. Defaults to None. |
None |
iterative |
bool |
If True, the query will be iterative. Defaults to False. |
False |
limit |
int |
The number of results to return. Defaults to 1000. |
1000 |
return_list |
bool |
If True, the results will be returned as a list. Defaults to False. |
False |
Returns:
| Type | Description |
|---|---|
dimcli.DslDataset |
JSON data of the results. |
Source code in scholarpy/scholarpy.py
def search_org_by_name(
self, name, exact_match=True, fields=None, iterative=False, limit=1000, return_list=False, **kwargs
):
"""Search an organization by name.
Args:
name (str): The name of the organization.
exact_match (bool, optional): If True, the name must be an exact match. Defaults to True.
fields (str, optional): The fields to return. For example, [basics+extras]. Defaults to None.
iterative (bool, optional): If True, the query will be iterative. Defaults to False.
limit (int, optional): The number of results to return. Defaults to 1000.
return_list (bool, optional): If True, the results will be returned as a list. Defaults to False.
Returns:
dimcli.DslDataset: JSON data of the results.
"""
if fields is None:
fields = ""
query = f'search organizations for "\\"{name}\\"" return organizations{fields}'
if iterative:
result = self.query_iterative(query, limit=limit)
else:
query = f"{query} limit {limit}"
result = self.query(query)
try:
if exact_match:
df = result.as_dataframe()
sub_df = df[df["name"].str.lower() == name.lower()]
org_id = sub_df["id"].values.tolist()[0]
query = f'search organizations where id="{org_id}" return organizations{fields}'
result = self.query(query)
if return_list:
df = result.as_dataframe()
if not df.empty:
df.sort_values("name", inplace=True)
df["name_id"] = df["id"] + " | " + df["name"]
orgs = df["name_id"].values.tolist()
return orgs
else:
return None
else:
return result
except Exception as e:
print("No organization can be found.")
return None
search_pubs_by_journal_id(self, id, start_year=None, end_year=None, fields=None, iterative=False, limit=1000, **kwargs)
¶
Search publications by journal ID.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
id |
str |
The ID of the journal. For example, jour.1018957 |
required |
start_year |
int |
The start year of the publication. Defaults to None. |
None |
end_year |
int |
The end year of the publication. Defaults to None. |
None |
fields |
str |
The fields to return. For example, [basics+extras]. Defaults to None. |
None |
iterative |
bool |
If True, the query will be iterative. Defaults to False. |
False |
limit |
int |
The number of results to return. Defaults to 1000. |
1000 |
Returns:
| Type | Description |
|---|---|
dimcli.DslDataset |
JSON data of the results. |
Source code in scholarpy/scholarpy.py
def search_pubs_by_journal_id(
self,
id,
start_year=None,
end_year=None,
fields=None,
iterative=False,
limit=1000,
**kwargs,
):
"""Search publications by journal ID.
Args:
id (str): The ID of the journal. For example, jour.1018957
start_year (int, optional): The start year of the publication. Defaults to None.
end_year (int, optional): The end year of the publication. Defaults to None.
fields (str, optional): The fields to return. For example, [basics+extras]. Defaults to None.
iterative (bool, optional): If True, the query will be iterative. Defaults to False.
limit (int, optional): The number of results to return. Defaults to 1000.
Returns:
dimcli.DslDataset: JSON data of the results.
"""
if fields is None:
fields = ""
if (start_year is not None) and (end_year is not None):
query = f'search publications where journal.id="{id}" and year>={start_year} and year<={end_year} return publications{fields}'
elif start_year is not None:
query = f'search publications where journal.id="{id}" and year>={start_year} return publications{fields}'
elif end_year is not None:
query = f'search publications where journal.id="{id}" and year<={end_year} return publications{fields}'
else:
query = f'search publications where journal.id="{id}" return publications{fields}'
if iterative:
result = self.query_iterative(query, limit=limit)
else:
query = f"{query} limit {limit}"
result = self.query(query)
return result
search_pubs_by_keyword(self, keyword, exact_match=True, scope='title_abstract_only', start_year=None, end_year=None, journal_id=None, fields=None, sorted_field='times_cited', iterative=False, limit=1000, **kwargs)
¶
Search publications by keyword.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
keyword |
str |
The keyword to search. |
required |
exact_match |
bool |
If True, the keyword will be matched exactly. Defaults to True. |
True |
scope |
str |
The scope of the search. Defaults to "title_abstract_only". |
'title_abstract_only' |
start_year |
int |
The start year of the publication. Defaults to None. |
None |
end_year |
int |
The end year of the publication. Defaults to None. |
None |
fields |
str |
The fields to return. For example, [basics+extras]. Defaults to None. |
None |
sorted_field |
str |
The field to sort by. Defaults to "times_cited". |
'times_cited' |
iterative |
bool |
If True, the query will be iterative. Defaults to False. |
False |
limit |
int |
The number of results to return. Defaults to 1000. |
1000 |
Exceptions:
| Type | Description |
|---|---|
ValueError |
[description] |
Returns:
| Type | Description |
|---|---|
dimcli.DslDataset |
JSON data of the results. |
Source code in scholarpy/scholarpy.py
def search_pubs_by_keyword(
self,
keyword,
exact_match=True,
scope="title_abstract_only",
start_year=None,
end_year=None,
journal_id=None,
fields=None,
sorted_field="times_cited",
iterative=False,
limit=1000,
**kwargs,
):
"""Search publications by keyword.
Args:
keyword (str): The keyword to search.
exact_match (bool, optional): If True, the keyword will be matched exactly. Defaults to True.
scope (str, optional): The scope of the search. Defaults to "title_abstract_only".
start_year (int, optional): The start year of the publication. Defaults to None.
end_year (int, optional): The end year of the publication. Defaults to None.
fields (str, optional): The fields to return. For example, [basics+extras]. Defaults to None.
sorted_field (str, optional): The field to sort by. Defaults to "times_cited".
iterative (bool, optional): If True, the query will be iterative. Defaults to False.
limit (int, optional): The number of results to return. Defaults to 1000.
Raises:
ValueError: [description]
Returns:
dimcli.DslDataset: JSON data of the results.
"""
if exact_match:
exact = '\\"'
else:
exact = ""
if journal_id is not None:
journal = f'and journal.id="{journal_id}"'
else:
journal = ""
allowed_scopes = [
"authors",
"concepts",
"full_data",
"full_data_exact",
"title_abstract_only",
"title_only",
]
if scope not in allowed_scopes:
raise ValueError(f"scope must be one of {allowed_scopes}")
if fields is None:
fields = "[basics+altmetric+times_cited+field_citation_ratio+authors_count+doi+dimensions_url]"
if (start_year is not None) and (end_year is not None):
query = f'search publications in {scope} for "{exact}{keyword}{exact}" where year>={start_year} and year<={end_year} {journal} return publications{fields} sort by {sorted_field}'
elif start_year is not None:
query = f'search publications in {scope} for "{exact}{keyword}{exact}" where year>={start_year} {journal} return publications{fields} sort by {sorted_field}'
elif end_year is not None:
query = f'search publications in {scope} for "{exact}{keyword}{exact}" where year<={end_year} {journal} return publications{fields} sort by {sorted_field}'
else:
if journal_id is not None:
journal = f'where journal.id="{journal_id}"'
else:
journal = ""
query = f'search publications in {scope} for "{exact}{keyword}{exact}" {journal} return publications{fields} sort by {sorted_field}'
if iterative:
result = self.query_iterative(query, limit=limit)
else:
query = f"{query} limit {limit}"
result = self.query(query)
return result
search_pubs_by_org_id(self, id, start_year=None, end_year=None, fields=None, iterative=False, limit=1000, **kwargs)
¶
Search publications by organization ID.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
id |
str |
The ID of the organization. For example, grid.411461.7 |
required |
start_year |
int |
The start year of the publication. Defaults to None. |
None |
end_year |
int |
The end year of the publication. Defaults to None. |
None |
fields |
str |
The fields to return. For example, [basics+extras]. Defaults to None. |
None |
iterative |
bool |
If True, the query will be iterative. Defaults to False. |
False |
limit |
int |
The number of results to return. Defaults to 1000. |
1000 |
Returns:
| Type | Description |
|---|---|
dimcli.DslDataset |
JSON data of the results. |
Source code in scholarpy/scholarpy.py
def search_pubs_by_org_id(
self,
id,
start_year=None,
end_year=None,
fields=None,
iterative=False,
limit=1000,
**kwargs,
):
"""Search publications by organization ID.
Args:
id (str): The ID of the organization. For example, grid.411461.7
start_year (int, optional): The start year of the publication. Defaults to None.
end_year (int, optional): The end year of the publication. Defaults to None.
fields (str, optional): The fields to return. For example, [basics+extras]. Defaults to None.
iterative (bool, optional): If True, the query will be iterative. Defaults to False.
limit (int, optional): The number of results to return. Defaults to 1000.
Returns:
dimcli.DslDataset: JSON data of the results.
"""
if fields is None:
fields = ""
if (start_year is not None) and (end_year is not None):
query = f'search publications where research_orgs="{id}" and year>={start_year} and year<={end_year} return publications{fields}'
elif start_year is not None:
query = f'search publications where research_orgs="{id}" and year>={start_year} return publications{fields}'
elif end_year is not None:
query = f'search publications where research_orgs="{id}" and year<={end_year} return publications{fields}'
else:
query = f'search publications where research_orgs="{id}" return publications{fields}'
if iterative:
result = self.query_iterative(query, limit=limit)
else:
query = f"{query} limit {limit}"
result = self.query(query)
return result
search_pubs_by_researcher_id(self, id, start_year=None, end_year=None, fields=None, iterative=False, limit=1000, **kwargs)
¶
Search publications by researcher ID.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
id |
str |
The ID of the researcher. For example, res.010551261751.12 |
required |
start_year |
int |
The start year of the publication. Defaults to None. |
None |
end_year |
int |
The end year of the publication. Defaults to None. |
None |
fields |
str |
The fields to return. For example, [basics+extras]. Defaults to None. |
None |
iterative |
bool |
If True, the query will be iterative. Defaults to False. |
False |
limit |
int |
The number of results to return. Defaults to 1000. |
1000 |
Returns:
| Type | Description |
|---|---|
dimcli.DslDataset |
JSON data of the results. |
Source code in scholarpy/scholarpy.py
def search_pubs_by_researcher_id(
self,
id,
start_year=None,
end_year=None,
fields=None,
iterative=False,
limit=1000,
**kwargs,
):
"""Search publications by researcher ID.
Args:
id (str): The ID of the researcher. For example, res.010551261751.12
start_year (int, optional): The start year of the publication. Defaults to None.
end_year (int, optional): The end year of the publication. Defaults to None.
fields (str, optional): The fields to return. For example, [basics+extras]. Defaults to None.
iterative (bool, optional): If True, the query will be iterative. Defaults to False.
limit (int, optional): The number of results to return. Defaults to 1000.
Returns:
dimcli.DslDataset: JSON data of the results.
"""
if fields is None:
fields = "[basics+authors_count+times_cited+dimensions_url]"
if (start_year is not None) and (end_year is not None):
query = f'search publications where researchers.id="{id}" and year>={start_year} and year<={end_year} return publications{fields}'
elif start_year is not None:
query = f'search publications where researchers.id="{id}" and year>={start_year} return publications{fields}'
elif end_year is not None:
query = f'search publications where researchers.id="{id}" and year<={end_year} return publications{fields}'
else:
query = f'search publications where researchers.id="{id}" return publications{fields}'
if iterative:
result = self.query_iterative(query, limit=limit)
else:
query = f"{query} limit {limit}"
result = self.query(query)
return result
search_researcher_by_id(self, id, fields=None, iterative=False, limit=1000, return_df=False, **kwargs)
¶
Search a researcher by ID.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
id |
str |
The ID of the researcher. For example, ur.010551261751.12 |
required |
fields |
str |
The fields to return. For example, [basics+extras]. Defaults to None. |
None |
iterative |
bool |
If True, the query will be iterative. Defaults to False. |
False |
limit |
int |
The number of results to return. Defaults to 1000. |
1000 |
return_df |
bool |
If True, the results will be returned as a dataframe. Defaults to False. |
False |
Returns:
| Type | Description |
|---|---|
dimcli.DslDataset |
JSON data of the results. |
Source code in scholarpy/scholarpy.py
def search_researcher_by_id(
self,
id,
fields=None,
iterative=False,
limit=1000,
return_df=False,
**kwargs,
):
"""Search a researcher by ID.
Args:
id (str): The ID of the researcher. For example, ur.010551261751.12
fields (str, optional): The fields to return. For example, [basics+extras]. Defaults to None.
iterative (bool, optional): If True, the query will be iterative. Defaults to False.
limit (int, optional): The number of results to return. Defaults to 1000.
return_df (bool, optional): If True, the results will be returned as a dataframe. Defaults to False.
Returns:
dimcli.DslDataset: JSON data of the results.
"""
"""Search a researcher by a Dimensions Research ID. For example, ur.010551261751.12"""
if fields is None:
fields = "[basics+extras]"
query = f'search researchers where id="{id}" return researchers{fields}'
if iterative:
result = self.query_iterative(query, limit=limit, **kwargs)
else:
query = f"{query} limit {limit}"
result = self.query(query)
if return_df:
df2 = result.as_dataframe().transpose()
df3 = pd.DataFrame(
{"index": df2.index.tolist(), "value": df2.values.tolist()}
)
df3["value"] = df3["value"]
print(type(df3["value"]))
return df3
else:
return result
search_researcher_by_name(self, name, fields=None, iterative=False, limit=1000, return_list=False, **kwargs)
¶
Search a researcher by name.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
name |
str |
The name of the researcher. |
required |
fields |
str |
The fields to return. For example, [basics+extras]. Defaults to None. |
None |
iterative |
bool |
If True, the query will be iterative. Defaults to False. |
False |
limit |
int |
The number of results to return. Defaults to 1000. |
1000 |
return_list |
bool |
If True, the results will be returned as a list. Defaults to False. |
False |
Returns:
| Type | Description |
|---|---|
dimcli.DslDataset |
JSON data of the results. |
Source code in scholarpy/scholarpy.py
def search_researcher_by_name(
self,
name,
fields=None,
iterative=False,
limit=1000,
return_list=False,
**kwargs,
):
"""Search a researcher by name.
Args:
name (str): The name of the researcher.
fields (str, optional): The fields to return. For example, [basics+extras]. Defaults to None.
iterative (bool, optional): If True, the query will be iterative. Defaults to False.
limit (int, optional): The number of results to return. Defaults to 1000.
return_list (bool, optional): If True, the results will be returned as a list. Defaults to False.
Returns:
dimcli.DslDataset: JSON data of the results.
"""
if fields is None:
fields = "[basics+extras]"
query = f'search researchers for "\\"{name}\\"" where obsolete=0 and total_publications>0 return researchers{fields}'
if iterative:
result = self.query_iterative(query, limit=limit)
else:
query = f"{query} limit {limit}"
result = self.query(query)
if return_list:
df = result.as_dataframe()
if not df.empty:
# df.sort_values(by=["id"], inplace=True)
df["current_research_org_name"] = df["current_research_org.name"]
df.sort_values("current_research_org_name", inplace=True)
if not df.empty:
items = []
for row in df.itertuples():
item = (
str(row.first_name)
+ " "
+ str(row.last_name)
+ " | "
+ str(row.id)
+ " | "
+ str(row.current_research_org_name)
)
items.append(item)
return result, items
else:
return result, None
else:
return result
search_researcher_collaborators(self, id, pubs=None)
¶
Search collaborators of a researcher.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
id |
str |
The ID of the researcher. For example, ur.010551261751.12 |
required |
pubs |
dimcli.DslDataset |
The publications of the researcher. Defaults to None. |
None |
Returns:
| Type | Description |
|---|---|
pd.DataFrame |
A dataframe of the collaborators. |
Source code in scholarpy/scholarpy.py
def search_researcher_collaborators(self, id, pubs=None):
"""Search collaborators of a researcher.
Args:
id (str): The ID of the researcher. For example, ur.010551261751.12
pubs (dimcli.DslDataset, optional): The publications of the researcher. Defaults to None.
Returns:
pd.DataFrame: A dataframe of the collaborators.
"""
if pubs is None:
pubs = self.search_pubs_by_researcher_id(id)
df = pubs.as_dataframe_authors()
df = df[df["researcher_id"] != id]
df["Name"] = df["first_name"].str.split(
" ").str[0] + " " + df["last_name"]
names = df.drop_duplicates("Name").copy()
affiliations = names["affiliations"].values.tolist()
institutions = []
for a in enumerate(affiliations):
try:
institution = a[1][0]["name"]
institutions.append(institution)
except:
institutions.append("")
names["Institution"] = institutions
names = names[["Name", "Institution"]]
result = pd.DataFrame(df["Name"].value_counts())
result = pd.DataFrame(
{"Name": result.index, "Count": result["Name"].values})
return result.merge(names, on="Name")
annual_stats_barplot(df, columns=None, **kwargs)
¶
Get a barplot of the annual stats.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
df |
pd.DataFrame |
The dataframe of the results. Can be derived from df, _ = dsl.researcher_annual_stats(). |
required |
columns |
list |
The columns to plot. Defaults to None. |
None |
Returns:
| Type | Description |
|---|---|
px.Bar |
The barplot. |
Source code in scholarpy/scholarpy.py
def annual_stats_barplot(df, columns=None, **kwargs):
"""Get a barplot of the annual stats.
Args:
df (pd.DataFrame): The dataframe of the results. Can be derived from df, _ = dsl.researcher_annual_stats().
columns (list, optional): The columns to plot. Defaults to None.
Returns:
px.Bar: The barplot.
"""
if columns is None:
columns = ["pubs", "collaborators", "institutions", "cities"]
fig = px.bar(
df,
x="year",
y=columns,
barmode="group",
)
return fig
collaborator_locations(df)
¶
Get the locations of collaborators.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
df |
pd.DataFrame |
The dataframe of collaborators, can be derived from _, df = dsl.researcher_annual_stats(). |
required |
Returns:
| Type | Description |
|---|---|
pd.DataFrame |
The dataframe of the results. |
Source code in scholarpy/scholarpy.py
def collaborator_locations(df):
"""Get the locations of collaborators.
Args:
df (pd.DataFrame): The dataframe of collaborators, can be derived from _, df = dsl.researcher_annual_stats().
Returns:
pd.DataFrame: The dataframe of the results.
"""
if "name" in df.columns:
df.drop(columns=["name"], axis=1, inplace=True)
if "year" in df.columns:
df.drop(columns=["year"], axis=1, inplace=True)
if "index" in df.columns:
df.drop(columns=["index"], axis=1, inplace=True)
df.drop_duplicates(inplace=True)
df = df[df["latitude"] != 0].reset_index()
df.drop(columns=["index"], axis=1, inplace=True)
return df
geoname_latlon(id, df=None)
¶
Get the latitude and longitude of a city based on a GeoNmae city id.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
id |
str |
The GeoName city id. |
required |
df |
pd.DataFrame |
The geonames dataframe. Defaults to None. |
None |
Returns:
| Type | Description |
|---|---|
tuple |
The latitude and longitude of the city. |
Source code in scholarpy/scholarpy.py
def geoname_latlon(id, df=None):
"""Get the latitude and longitude of a city based on a GeoNmae city id.
Args:
id (str): The GeoName city id.
df (pd.DataFrame, optional): The geonames dataframe. Defaults to None.
Returns:
tuple: The latitude and longitude of the city.
"""
if not isinstance(id, int):
try:
id = int(id)
except:
raise ValueError("id must be an integer")
if df is None:
df = get_geonames()
row = df[df["geonameid"] == id]
lat = 0
lon = 0
if not row.empty:
lat = row.iloc[0]["latitude"]
lon = row.iloc[0]["longitude"]
return lat, lon
get_geonames(**kwargs)
¶
Get the geonames dataframe.
Returns:
| Type | Description |
|---|---|
pd.DataFrame |
The dataframe of the results. |
Source code in scholarpy/scholarpy.py
def get_geonames(**kwargs):
"""Get the geonames dataframe.
Returns:
pd.DataFrame: The dataframe of the results.
"""
url = "https://raw.githubusercontent.com/giswqs/data/main/world/cities5000.csv"
# columns = ['geonameid', 'name', 'asciiname', 'alternatenames', 'latitude', 'longitude', 'feature_class', 'feature_code', 'country_code',
# 'cc2', 'admin1_code', 'admin2_code', 'admin3_code', 'admin4_code', 'population', 'elevation', 'dem', 'timezone', 'modification_date']
df = pd.read_csv(url, sep="\t", encoding="utf-8")
if "columns" in kwargs and isinstance(kwargs["columns"], list):
df = df[kwargs["columns"]]
else:
df = df[
["geonameid", "name", "country_code",
"population", "latitude", "longitude"]
]
return df
json_to_df(json_data, transpose=False)
¶
Convert a json file to a dataframe.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
json_data |
json |
The json data. |
required |
transpose |
bool |
If True, transpose the dataframe. Defaults to False. |
False |
Returns:
| Type | Description |
|---|---|
pd.DataFrame |
The dataframe of the results. |
Source code in scholarpy/scholarpy.py
def json_to_df(json_data, transpose=False):
"""Convert a json file to a dataframe.
Args:
json_data (json): The json data.
transpose (bool, optional): If True, transpose the dataframe. Defaults to False.
Returns:
pd.DataFrame: The dataframe of the results.
"""
df = json_data.as_dataframe()
if not df.empty:
if transpose:
df = df.transpose()
out_csv = leafmap.temp_file_path(".csv")
df.to_csv(out_csv, index=transpose)
df = pd.read_csv(out_csv)
os.remove(out_csv)
return df
else:
return None
Last update:
2022-02-09