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| import pandas as pd | |
| import json | |
| import streamlit as st | |
| import matplotlib.pyplot as plt | |
| import seaborn as sns | |
| from wordcloud import WordCloud | |
| st.set_option('deprecation.showPyplotGlobalUse', False) | |
| # Define the Streamlit app | |
| st.title("Aspected-Based Sentiment Analysis with MVP") | |
| palette_color = sns.color_palette('Set1') | |
| # File upload and processing | |
| uploaded_file = st.file_uploader("Upload JSON File", type=["json"]) | |
| if uploaded_file: | |
| loaded_dict = json.load(uploaded_file) | |
| df = pd.DataFrame(loaded_dict) | |
| st.subheader(f"{len(df)}+ sentiment tuples was detected") | |
| st.write(df) | |
| # Sentiment Distribution Chart | |
| sentiment_distribution_perc = df["S"].value_counts(normalize=True) * 100 | |
| sentiment_distribution = df["S"].value_counts() | |
| st.subheader("Sentiment Distribution") | |
| fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(10, 6)) | |
| ax1.pie(sentiment_distribution_perc, labels=sentiment_distribution_perc.index, autopct='%1.1f%%', startangle=140,colors=palette_color) | |
| ax1.axis('equal') | |
| ax1.set_title("Sentiment Distribution %") | |
| # sns.countplot(x="S", data=df, palette=palette_color, ax=ax2) | |
| ax2.set_title("Sentiment Distribution Counts") | |
| ax2.bar(sentiment_distribution.index, sentiment_distribution.values, color=palette_color) | |
| # ax2.xlabel("Sentiment") | |
| # ax2.ylabel("Times") | |
| # ax2.xticks(rotation=0) # Rotate x-axis labels if needed | |
| st.pyplot(fig) | |
| # Group by and aggregate data | |
| grouped = df.groupby('A').agg({'S': ['count', lambda x: (x == 'great').sum(), lambda x: (x == 'ok').sum(), lambda x: (x == 'bad').sum()]}) | |
| grouped.columns = grouped.columns.map('_'.join) | |
| grouped = grouped.reset_index() | |
| grouped = grouped.rename(columns={'A': 'Aspect', 'S_count': 'Freq', 'S_<lambda_0>': 'Great', 'S_<lambda_1>': 'Ok', 'S_<lambda_2>': 'Bad'}) | |
| st.subheader("Top 5 Most Mentioned Product Apsects") | |
| st.write(grouped.sort_values(by="Freq", ascending=False).head(5)) | |
| # Word Cloud | |
| aspect_terms = " ".join(df["A"]) | |
| wordcloud = WordCloud( | |
| width=800, | |
| height=400, | |
| background_color='white', | |
| max_words=100, | |
| colormap='inferno', | |
| contour_width=3, | |
| contour_color='red', | |
| ).generate(aspect_terms) | |
| st.subheader("Word Cloud for Most Mentioned Aspects") | |
| plt.figure(figsize=(10, 5)) | |
| plt.imshow(wordcloud, interpolation='bilinear') | |
| plt.title("Most mentioned aspect terms") | |
| plt.axis("off") | |
| st.pyplot() | |
| st.sidebar.markdown("**Upload a JSON file to get started.**") |