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import os |
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import scholarpy |
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import pandas as pd |
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import streamlit as st |
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import leafmap.foliumap as leafmap |
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import plotly.express as px |
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import datetime |
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current_year = datetime.datetime.now().year |
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if "dsl" not in st.session_state: |
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st.session_state["dsl"] = scholarpy.Dsl() |
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def app(): |
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st.title("Search Organizations") |
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dsl = st.session_state["dsl"] |
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row1_col1, row1_col2 = st.columns([1, 1]) |
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with row1_col1: |
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name = st.text_input("Enter an organization name:", "") |
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if name: |
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orgs = dsl.search_org_by_name(name, exact_match=False, return_list=True) |
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if orgs is not None: |
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with row1_col1: |
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selected_org = st.selectbox("Select a organization id:", orgs) |
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org_id = selected_org.split("|")[0].strip() |
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id_info = dsl.search_org_by_id(org_id) |
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info_df = scholarpy.json_to_df(id_info, transpose=True) |
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info_df.rename( |
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columns={info_df.columns[0]: "Type", info_df.columns[1]: "Value"}, |
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inplace=True, |
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) |
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with row1_col1: |
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st.header("Organization Information") |
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if not info_df.empty: |
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st.dataframe(info_df) |
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leafmap.st_download_button( |
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"Download data", info_df, csv_sep="\t" |
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) |
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else: |
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st.text("No information found") |
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with row1_col2: |
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years = st.slider( |
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"Select the start and end year:", |
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1950, |
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current_year + 6, |
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(1980, current_year), |
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) |
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st.header("Publications by year") |
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pubs, fig = dsl.org_pubs_annual_stats( |
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org_id, start_year=years[0], end_year=years[1], return_plot=True |
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) |
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st.text(f'Total number of publications: {pubs["count"].sum():,}') |
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if fig is not None: |
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st.plotly_chart(fig) |
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leafmap.st_download_button( |
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"Download data", |
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pubs, |
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file_name="data.csv", |
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csv_sep="\t", |
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) |
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else: |
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st.text("No publications found") |
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with row1_col1: |
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st.header("Top funders") |
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funder_count = st.slider( |
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"Select the number of funders:", 1, 100, 20 |
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) |
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funders, fig = dsl.org_grant_funders( |
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org_id, limit=funder_count, return_plot=True |
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) |
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st.text(f'Total funding amount: ${funders["funding"].sum():,}') |
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if fig is not None: |
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st.plotly_chart(fig) |
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leafmap.st_download_button( |
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"Download data", |
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funders, |
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file_name="data.csv", |
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csv_sep="\t", |
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) |
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else: |
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st.text("No funders found") |
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with row1_col2: |
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st.header("The number of grants by year") |
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grants, fig_count, fig_amount = dsl.org_grants_annual_stats( |
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org_id, start_year=years[0], end_year=years[1], return_plot=True |
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) |
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st.plotly_chart(fig_count) |
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st.plotly_chart(fig_amount) |
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leafmap.st_download_button( |
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"Download data", |
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grants, |
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file_name="data.csv", |
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csv_sep="\t", |
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) |
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with row1_col1: |
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st.header("List of grants") |
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st.text("Only the first 1000 grants are shown") |
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result = dsl.search_grants_by_org( |
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org_id, start_year=years[0], end_year=years[1] |
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) |
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df = result.as_dataframe() |
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if not df.empty: |
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st.dataframe(df) |
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leafmap.st_download_button( |
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"Download data", df, file_name="data.csv", csv_sep="\t" |
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) |
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with row1_col1: |
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st.header("Publications most cited in last 2 years") |
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result = dsl.org_pubs_most_cited(org_id, recent=True, limit=100) |
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df = scholarpy.json_to_df(result, transpose=False) |
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if not df.empty: |
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st.dataframe(df) |
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leafmap.st_download_button( |
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"Download data", df, file_name="data.csv", csv_sep="\t" |
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) |
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with row1_col2: |
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st.header("Publications most cited - all time") |
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result = dsl.org_pubs_most_cited(org_id, recent=False, limit=100) |
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df = scholarpy.json_to_df(result, transpose=False) |
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if not df.empty: |
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st.dataframe(df) |
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leafmap.st_download_button( |
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"Download data", df, file_name="data.csv", csv_sep="\t" |
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) |
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df, area_fig, journal_fig = dsl.org_pubs_top_areas( |
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org_id, return_plot=True |
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) |
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if not df.empty: |
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with row1_col1: |
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st.header("Research areas of most cited publications") |
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st.plotly_chart(area_fig) |
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with row1_col2: |
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st.header("Journals of most cited publications") |
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st.plotly_chart(journal_fig) |
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leafmap.st_download_button( |
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"Download data", df, file_name="data.csv", csv_sep="\t" |
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) |
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else: |
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st.text("No organizations found") |
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