Create 4 Sunburst.py

pages/4 Sunburst.py

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+#===import module===
+import streamlit as st
+import pandas as pd
+import plotly.express as px
+import numpy as np
+import matplotlib.pyplot as plt
+
+#===config===
+st.set_page_config(
+     page_title="Coconut",
+     page_icon="🥥",
+     layout="wide"
+)
+st.header("Data visualization")
+st.subheader('Put your CSV file and choose a visualization')
+
+#===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)
+    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("Choose a file", 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===
+        papers, MIN, MAX, GAP = get_minmax(extype)
+        
+        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/')