Update app.py
Browse files
app.py
CHANGED
@@ -154,8 +154,28 @@ def perform_eda():
|
|
154 |
# Show the Power BI dashboard
|
155 |
power_bi()
|
156 |
|
157 |
-
# Add insights and recommendations
|
158 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
159 |
|
160 |
def display_insights_and_recommendations():
|
161 |
st.subheader("Data Insights and Recommendations")
|
|
|
154 |
# Show the Power BI dashboard
|
155 |
power_bi()
|
156 |
|
157 |
+
# Add insights and recommendations button
|
158 |
+
if st.button("Show Insights and Recommendations"):
|
159 |
+
display_insights_and_recommendations()
|
160 |
+
|
161 |
+
def display_insights_and_recommendations():
|
162 |
+
st.subheader("Data Insights and Recommendations")
|
163 |
+
st.write("""
|
164 |
+
From the dashboard, you can now appreciate the serious income inequality problem. Explore key insights and actionable recommendations for stakeholders to fight income inequality.
|
165 |
+
""")
|
166 |
+
|
167 |
+
# Table with insights and recommendations
|
168 |
+
st.table([
|
169 |
+
["π Higher education levels positively correlate with higher income.", "Invest in accessible and quality education, including scholarships and vocational training, for lower-income communities."],
|
170 |
+
["π©βπ Women are more likely below the income threshold than men.", "Support gender equality programs addressing wage disparities and encouraging women in STEM fields."],
|
171 |
+
["π₯ Income inequality exists across all employment statuses.", "Implement policies and programs supporting stable employment, job training, and entrepreneurship."],
|
172 |
+
["π Racial income disparities: Foster diversity and inclusion in workplaces.", "Promote equal opportunities, diversity training, and an inclusive work environment."],
|
173 |
+
["π Foreigners concentrated below the income threshold.", "Review immigration policies to ensure fair treatment and integration into the workforce."],
|
174 |
+
["π’ Majority below threshold in 'Unknown' occupations.", "Research challenges in different occupations and implement targeted support programs."],
|
175 |
+
["πΈ Nonfilers have higher representation below the threshold.", "Evaluate tax policies for fairness and consider incentives for low-income individuals."],
|
176 |
+
["π Data-driven insights are crucial for addressing income inequality.", "Continue investing in data collection and analysis to inform evolving policies."]
|
177 |
+
])
|
178 |
+
|
179 |
|
180 |
def display_insights_and_recommendations():
|
181 |
st.subheader("Data Insights and Recommendations")
|