Spaces:
Runtime error
Runtime error
File size: 4,996 Bytes
53dc0ac cb8d566 53dc0ac |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 |
import streamlit as st
import pandas as pd
import plotly.express as px
from src.st_helpers import st_setup
from src.datatypes import *
if st_setup('LLM Arch'):
if not DataLoader.loaded:
DataLoader.load_data()
summary = st.container()
with summary:
st.write("# Data Browser")
sumcol1, sumcol2 = st.columns([1, 3])
with sumcol1:
dbs = DataLoader.available_dbs()
if len(dbs) > 1:
st.write(f'**:1234: Database Selector**')
idx = dbs.index(DataLoader.active_db)
DataLoader.set_db_name(st.selectbox("Connected to:", dbs, index=idx, label_visibility="collapsed"))
st.write(f'**:1234: Summary Statistics**')
summary = f'- **{len(Category.all):,}** categories'
summary += f'\n- **{len(Product.all):,}** products'
summary += f'\n- **{len(Feature.all):,}** features'
summary += f'\n- **{len(Review.all):,}** reviews'
st.markdown(summary)
if st.button('Force data reload'):
DataLoader.load_data(True)
st.rerun()
with sumcol2:
cats = Category.all_sorted()
with st.expander("**Review Counts**"):
category_names = [c.name for c in cats]
category_review_counts = [sum([p.review_count for p in c.products]) for c in cats]
data = zip(category_names, category_review_counts)
df = pd.DataFrame(data, columns=["Category", "Review Count"])
st.bar_chart(df, x="Category", y="Review Count")
with st.expander("**Product Ratings**"):
data = []
for c in cats:
for p in c.products:
data.append([c.name, p.average_rating])
df = pd.DataFrame(data, columns=['Category', 'Mean Product Rating'])
fig = px.box(df, x="Category", y="Mean Product Rating")
fig.update_xaxes(tickangle=-90)
st.plotly_chart(fig, use_container_width=True)
with st.expander("**Product Prices**"):
data = []
for c in cats:
for p in c.products:
data.append([c.name, p.price])
df = pd.DataFrame(data, columns=['Category', 'Price'])
fig = px.box(df, x="Category", y="Price")
fig.update_xaxes(tickangle=-90)
st.plotly_chart(fig, use_container_width=True)
subhead = st.container()
col1, col2 = st.columns([1, 3])
with col1:
st.write('**Category**')
cats = Category.all_sorted()
options = [f"{c.name}" for c in cats]
selection = st.radio("**Category**", options, label_visibility="collapsed")
selected_category = Category.by_name(selection)
with subhead:
st.write(f'### {selection}')
with col2:
features = [f.name for f in selected_category.features]
features.sort()
st.write(f"**{selection[:-1]} Features ({len(features)}):**")
st.write('; '.join(features))
prod_index = [p.id for p in selected_category.products]
prod_data = [[p.name, p.price, p.feature_count, ', '.join([str(f) for f in p.features]), p.review_count,
p.average_rating, False, p.description] for p in selected_category.products]
prod_columns = ['Name', 'Price', 'Feature Count', 'Features', 'Review Count', 'Average Rating', 'Show Reviews?',
'Description']
prod_df = pd.DataFrame(prod_data, index=prod_index, columns=prod_columns)
total_reviews = sum([p.review_count for p in selected_category.products])
st.write(f"**{selection} ({len(prod_index)}). Having {total_reviews} reviews in total:**")
edited_df = st.data_editor(prod_df, disabled=(
'Name', 'Price', 'Feature Count', 'Features', 'Review Count', 'Average Rating', 'Description'))
selected_product_count = edited_df['Show Reviews?'].sum()
selected_review_count = edited_df[edited_df['Show Reviews?']]['Review Count'].sum()
st.write(f"**{selection[:-1]} Reviews ({selected_review_count} from {selected_product_count} products):**")
if selected_review_count > 0:
selected_products = list(edited_df[edited_df['Show Reviews?']].index)
products = Product.for_ids(selected_products)
rev_data = []
rev_index = []
for p in products:
for r in p.reviews:
rev_index.append(r.id)
rev_data.append([p.name, r.rating, r.review_text])
rev_columns = ['Product', 'Review Rating', 'Review Text']
rev_df = pd.DataFrame(rev_data, index=rev_index, columns=rev_columns)
st.dataframe(rev_df, width=10000)
else:
st.write("Check boxes in the table above to see reviews for products.") |