Niharmahesh commited on
Commit
a1438ea
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1 Parent(s): bceed2a

Update app.py

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Files changed (1) hide show
  1. app.py +55 -1
app.py CHANGED
@@ -183,7 +183,59 @@ def display_data_explorer(df):
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  filtered_df['company_url'] = filtered_df['company_url'].apply(make_clickable)
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  st.write(filtered_df.to_html(escape=False, index=False), unsafe_allow_html=True)
 
 
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  def main():
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  st.title("Job Listings Dashboard")
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@@ -195,12 +247,14 @@ def main():
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  # Sidebar for navigation
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  st.sidebar.title("Navigation")
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- page = st.sidebar.radio("Go to", ["Dashboard", "Data Explorer"])
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  if page == "Dashboard":
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  display_dashboard(df)
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  elif page == "Data Explorer":
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  display_data_explorer(df)
 
 
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  if __name__ == "__main__":
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  main()
 
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  filtered_df['company_url'] = filtered_df['company_url'].apply(make_clickable)
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  st.write(filtered_df.to_html(escape=False, index=False), unsafe_allow_html=True)
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+ def display_about_page():
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+ st.title("About Job Listings Dashboard")
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+ st.markdown("""
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+ ## What is this application?
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+
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+ The Job Listings Dashboard is a powerful tool designed to provide insights into the job market. It offers a comprehensive view of job postings, allowing users to explore trends, top companies, locations, and job titles.
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+
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+ ### Key Features:
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+ - **Interactive Dashboard**: Visualize job market trends with dynamic charts and graphs.
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+ - **Data Explorer**: Dive deep into individual job listings with advanced filtering options.
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+ - **Real-time Data**: Fetch the latest job data from our Hugging Face dataset.
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+
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+ ## How to use this application
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+
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+ ### Dashboard
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+ 1. Navigate to the Dashboard using the sidebar.
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+ 2. View overall statistics such as total job postings, unique companies, and today's postings.
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+ 3. Explore interactive charts showing:
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+ - Top companies hiring
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+ - Job postings over time
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+ - Top locations for job opportunities
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+ - Most common job titles
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+
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+ ### Data Explorer
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+ 1. Switch to the Data Explorer using the sidebar.
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+ 2. Choose between viewing all data or applying filters.
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+ 3. Use the multi-select dropdowns to filter by:
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+ - Companies
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+ - Locations
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+ - Job Types
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+ 4. Browse the filtered job listings table.
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+ 5. Click on job or company links to view more details on the original posting site.
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+
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+ ## Data Source
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+ This application fetches data from a Hugging Face dataset. The data is regularly updated to provide the most current job market insights.
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+
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+ ## Feedback and Contributions
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+ We welcome your feedback and contributions to improve this dashboard. Please feel free to reach out or submit pull requests to our GitHub repository.
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+
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+ ## Contact
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+ For questions, feedback, or collaboration opportunities, feel free to reach out:
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+
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+ - LinkedIn: [Nihar Palem](https://www.linkedin.com/in/nihar-palem-1b955a183/)
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+ """)
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+
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+ # Add a clickable LinkedIn button
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+ linkedin_url = "https://www.linkedin.com/in/nihar-palem-1b955a183/"
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+ st.markdown(f"""
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+ <a href="{linkedin_url}" target="_blank">
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+ <img src="https://content.linkedin.com/content/dam/me/business/en-us/amp/brand-site/v2/bg/LI-Logo.svg.original.svg" width="100">
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+ </a>
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+ """, unsafe_allow_html=True)
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  def main():
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  st.title("Job Listings Dashboard")
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  # Sidebar for navigation
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  st.sidebar.title("Navigation")
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+ page = st.sidebar.radio("Go to", ["Dashboard", "Data Explorer","About"])
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  if page == "Dashboard":
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  display_dashboard(df)
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  elif page == "Data Explorer":
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  display_data_explorer(df)
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+ elif page == "About":
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+ display_about_page()
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  if __name__ == "__main__":
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  main()