| import os | |
| from collections import Counter | |
| import streamlit as st | |
| import pandas as pd | |
| import plotly.express as px | |
| # Streamlit app title | |
| # st.title('Interactive Tag Frequency Visualization') | |
| # File uploader to select folder | |
| folder_path = "/home/caimera-prod/eye_tagged_data" | |
| if folder_path: | |
| # Initialize a Counter to count tag frequency | |
| tag_counter = Counter() | |
| # Iterate through each .txt file in the folder | |
| for file_name in os.listdir(folder_path): | |
| if file_name.endswith('.txt'): | |
| file_path = os.path.join(folder_path, file_name) | |
| with open(file_path, 'r') as file: | |
| tags = file.read().strip().split(',') | |
| # Clean and count each tag | |
| tags = [tag.strip().lower() for tag in tags] | |
| tag_counter.update(tags) | |
| # Convert the Counter to a DataFrame for better display | |
| tag_data = pd.DataFrame(tag_counter.items(), columns=['Tag', 'Count']) | |
| tag_data = tag_data.sort_values(by='Count', ascending=False).reset_index(drop=True) | |
| # Display the DataFrame as a table in Streamlit | |
| st.subheader('Tag Frequency Table') | |
| st.dataframe(tag_data) | |
| # Create an interactive bar chart using Plotly | |
| st.subheader('Interactive Tag Frequency Bar Chart') | |
| fig = px.bar(tag_data, x='Tag', y='Count', title='Tag Frequency', labels={'Count': 'Frequency'}, height=600) | |
| fig.update_layout(xaxis_title='Tags', yaxis_title='Frequency') | |
| st.plotly_chart(fig) | |