rasmodev commited on
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d073764
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1 Parent(s): 28718e9

Update app.py

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  1. app.py +20 -0
app.py CHANGED
@@ -187,6 +187,26 @@ def power_bi():
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  """, unsafe_allow_html=True)
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  def prediction():
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  # Load the saved model and unique values:
 
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  """, unsafe_allow_html=True)
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+ # Add insights and recommendations
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+ st.subheader("Data Insights and Recommendations")
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+ st.write("""
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+ From the dashboard, you can now appreciate the serious income inequality problem. Explore key insights and actionable recommendations for stakeholders to fight income inequality.
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+ """)
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+
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+ # Table with insights and recommendations
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+ st.table([
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+ ["πŸŽ“ Higher education levels positively correlate with higher income.", "Invest in accessible and quality education, including scholarships and vocational training, for lower-income communities."],
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+ ["πŸ‘©β€πŸŽ“ Women are more likely below the income threshold than men.", "Support gender equality programs addressing wage disparities and encouraging women in STEM fields."],
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+ ["πŸ‘₯ Income inequality exists across all employment statuses.", "Implement policies and programs supporting stable employment, job training, and entrepreneurship."],
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+ ["🌍 Racial income disparities: Foster diversity and inclusion in workplaces.", "Promote equal opportunities, diversity training, and an inclusive work environment."],
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+ ["🌐 Foreigners concentrated below the income threshold.", "Review immigration policies to ensure fair treatment and integration into the workforce."],
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+ ["🏒 Majority below threshold in 'Unknown' occupations.", "Research challenges in different occupations and implement targeted support programs."],
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+ ["πŸ’Έ Nonfilers have higher representation below the threshold.", "Evaluate tax policies for fairness and consider incentives for low-income individuals."],
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+ ["πŸ“Š Data-driven insights are crucial for addressing income inequality.", "Continue investing in data collection and analysis to inform evolving policies."]
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+ ])
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+
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+
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+
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  def prediction():
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  # Load the saved model and unique values: