Update app.py

app.py

@@ -10,6 +10,10 @@ import pandas as pd
 from huggingface_hub import login, InferenceClient
 from sklearn.metrics.pairwise import cosine_similarity
 import streamlit as st
+import wordcloud
+import matplotlib.pyplot as plt
+from pygwalker.api.streamlit import StreamlitRenderer
+import plotly.express as px
 
 st.set_page_config(layout="wide")
 
@@ -363,3 +367,61 @@ if not mode:
                     show_recipe(filtered_recipes[0])
                 else:
                     st.write("No recipe found.")
+else:
+    st.markdown("# :eyes: PEOPLE SEARCHING FOR...")
+    print(st.session_state.ind)
+    flattened_indices = list(set(index for sublist in st.session_state.ind for index in sublist))
+    df = items_dict.iloc[flattened_indices]
+    if st.session_state.ind != []:
+        with st.spinner("LET'S SEE, WHAT PEOPLE WANT..."):
+            cont1 = st.container(border=True, height=500)
+            with cont1:
+                wc = wordcloud.WordCloud(width=1000, height=320, background_color='white').generate(
+                    ' '.join(df['CATEGORY']))
+
+                # Display word cloud
+                fig, ax = plt.subplots()
+                ax.imshow(wc, interpolation='bilinear')
+                ax.axis('off')
+
+                st.pyplot(fig, use_container_width=True)
+
+            with st.container(border=True, height=500):
+                col1, col2 = st.columns(2)
+                with col1:
+                    st.markdown('## DEMAND AS PER CATEGORY')
+                    with plt.style.context('Solarize_Light2'):
+                        fig0 = px.pie(df, names='CATEGORY', hole=0.5)
+                        fig0.update_traces(text=df['CATEGORY'], textposition='outside')
+                        st.plotly_chart(fig0, use_container_width=True)
+
+                with col2:
+                    st.markdown('## DEMAND AS PER AVAILABILITY')
+                    with plt.style.context('Solarize_Light2'):
+                        fig1 = px.pie(df, names='AVAILABILITY', hole=0.5)
+                        fig1.update_traces(text=df['AVAILABILITY'], textposition='outside')
+                        st.plotly_chart(fig1, use_container_width=True)
+
+            with st.container(border=True, height=620):
+                st.markdown('## :deciduous_tree: Hierarchical view of Sales using TreeMap')
+                fig4 = px.treemap(df, path=['CATEGORY', 'AVAILABILITY','PRODUCT'],color='AVAILABILITY')
+                fig4.update_layout(height=550)
+                st.plotly_chart(fig4, use_container_width=True,scrolling=False)
+
+            with st.container(border=True, height=500):
+                fig = px.bar(df,
+                             y='CATEGORY',
+                             x='BREADCRUMBS',
+                             color='BRAND',
+                             # title='Gross Sales of Every Segment Country-wise',
+                             barmode='relative',
+                             title="Segment Vs. Gross Sales"
+                             )
+                st.plotly_chart(fig, use_container_width=True)
+
+            @st.cache_resource
+            def pygwalerapp(df):
+                return StreamlitRenderer(df)
+            # st.markdown("## :desktop_computer: DO YOUR OWN RESEARCH...")
+            with st.expander("## :desktop_computer: LOOKING FOR SOMETHING ELSE..."):
+                pygwalerapp(df).explorer()