#===import module=== import streamlit as st import pandas as pd import plotly.express as px import numpy as np import sys #===config=== st.set_page_config( page_title="Coconut", page_icon="🥥", layout="wide", initial_sidebar_state="collapsed" ) hide_streamlit_style = """ """ st.markdown(hide_streamlit_style, unsafe_allow_html=True) with st.popover("🔗 Menu"): st.page_link("Home.py", label="Home", icon="🏠") st.page_link("pages/1 Scattertext.py", label="Scattertext", icon="1️⃣") st.page_link("pages/2 Topic Modeling.py", label="Topic Modeling", icon="2️⃣") st.page_link("pages/3 Bidirected Network.py", label="Bidirected Network", icon="3️⃣") st.page_link("pages/4 Sunburst.py", label="Sunburst", icon="4️⃣") st.page_link("pages/5 Burst Detection.py", label="Burst Detection", icon="5️⃣") st.page_link("pages/6 Keywords Stem.py", label="Keywords Stem", icon="6️⃣") st.header("Sunburst Visualization", anchor=False) st.subheader('Put your file here...', anchor=False) #===clear cache=== def reset_all(): st.cache_data.clear() #===check type=== @st.cache_data(ttl=3600) def get_ext(extype): extype = uploaded_file.name return extype @st.cache_data(ttl=3600) def upload(extype): papers = pd.read_csv(uploaded_file) #lens.org if 'Publication Year' in papers.columns: papers.rename(columns={'Publication Year': 'Year', 'Citing Works Count': 'Cited by', 'Publication Type': 'Document Type', 'Source Title': 'Source title'}, inplace=True) return papers @st.cache_data(ttl=3600) def conv_txt(extype): col_dict = {'TI': 'Title', 'SO': 'Source title', 'DT': 'Document Type', 'DE': 'Author Keywords', 'ID': 'Keywords Plus', 'AB': 'Abstract', 'TC': 'Cited by', 'PY': 'Year',} papers = pd.read_csv(uploaded_file, sep='\t', lineterminator='\r') papers.rename(columns=col_dict, inplace=True) return papers #===Read data=== uploaded_file = st.file_uploader('', type=['csv', 'txt'], on_change=reset_all) if uploaded_file is not None: extype = get_ext(uploaded_file) if extype.endswith('.csv'): papers = upload(extype) elif extype.endswith('.txt'): papers = conv_txt(extype) @st.cache_data(ttl=3600) def get_minmax(extype): extype = extype MIN = int(papers['Year'].min()) MAX = int(papers['Year'].max()) GAP = MAX - MIN return papers, MIN, MAX, GAP tab1, tab2 = st.tabs(["📈 Generate visualization", "📓 Recommended Reading"]) with tab1: #===sunburst=== try: papers, MIN, MAX, GAP = get_minmax(extype) except KeyError: st.error('Error: Please check again your columns.') sys.exit(1) if (GAP != 0): YEAR = st.slider('Year', min_value=MIN, max_value=MAX, value=(MIN, MAX), on_change=reset_all) else: st.write('You only have data in ', (MAX)) YEAR = (MIN, MAX) @st.cache_data(ttl=3600) def listyear(extype): global papers years = list(range(YEAR[0],YEAR[1]+1)) papers = papers.loc[papers['Year'].isin(years)] return years, papers @st.cache_data(ttl=3600) def vis_sunbrust(extype): papers['Cited by'] = papers['Cited by'].fillna(0) vis = pd.DataFrame() vis[['doctype','source','citby','year']] = papers[['Document Type','Source title','Cited by','Year']] viz=vis.groupby(['doctype', 'source', 'year'])['citby'].agg(['sum','count']).reset_index() viz.rename(columns={'sum': 'cited by', 'count': 'total docs'}, inplace=True) fig = px.sunburst(viz, path=['doctype', 'source', 'year'], values='total docs', color='cited by', color_continuous_scale='RdBu', color_continuous_midpoint=np.average(viz['cited by'], weights=viz['total docs'])) fig.update_layout(height=800, width=1200) return fig years, papers = listyear(extype) if {'Document Type','Source title','Cited by','Year'}.issubset(papers.columns): fig = vis_sunbrust(extype) st.plotly_chart(fig, height=800, width=1200) #use_container_width=True) else: st.error('We require these columns: Document Type, Source title, Cited by, Year', icon="🚨") with tab2: st.markdown('**numpy.average — NumPy v1.24 Manual. (n.d.). Numpy.Average — NumPy v1.24 Manual.** https://numpy.org/doc/stable/reference/generated/numpy.average.html') st.markdown('**Sunburst. (n.d.). Sunburst Charts in Python.** https://plotly.com/python/sunburst-charts/')