Update app.py
Browse files
app.py
CHANGED
@@ -139,13 +139,14 @@ def solution():
|
|
139 |
Overall, this tool has the potential to make a meaningful contribution to the fight against income inequality and promote a more just and equitable society. βοΈ
|
140 |
""")
|
141 |
|
|
|
142 |
|
143 |
def perform_eda():
|
144 |
-
st.title("
|
145 |
st.write("""
|
146 |
-
ππ Welcome to the Exploratory Data Analysis for the
|
147 |
-
Gain a comprehensive understanding of income distribution and explore the factors
|
148 |
-
Dive into the wealth of data and uncover insights about income prediction. Explore the data and understand the factors
|
149 |
""")
|
150 |
|
151 |
# Show the Power BI dashboard
|
@@ -161,7 +162,16 @@ def display_insights_and_recommendations():
|
|
161 |
From the dashboard, you can now appreciate the serious income inequality problem. Explore key insights and actionable recommendations for stakeholders to fight income inequality.
|
162 |
""")
|
163 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
164 |
# Table with insights and recommendations
|
|
|
165 |
st.table([
|
166 |
["π Higher education levels positively correlate with higher income.", "Invest in accessible and quality education, including scholarships and vocational training, for lower-income communities."],
|
167 |
["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."],
|
@@ -173,40 +183,19 @@ def display_insights_and_recommendations():
|
|
173 |
["π Data-driven insights are crucial for addressing income inequality.", "Continue investing in data collection and analysis to inform evolving policies."]
|
174 |
])
|
175 |
|
176 |
-
# Define the Power BI display
|
177 |
def power_bi():
|
178 |
"""
|
179 |
-
|
180 |
"""
|
181 |
|
182 |
st.subheader("Exploring Income Data")
|
183 |
st.write("Let's dive deeper into the data to understand income distribution and relationships between variables.")
|
184 |
|
185 |
-
#
|
186 |
-
|
187 |
-
<iframe title="Report Section" width="600" height="373.5" src="https://app.powerbi.com/view?r=eyJrIjoiZDNjMmExZjYtMWU2NS00NTBjLTk4Y2EtYmQ2MWU2OWMwODMyIiwidCI6IjQ0ODdiNTJmLWYxMTgtNDgzMC1iNDlkLTNjMjk4Y2I3MTA3NSJ9" frameborder="0" allowFullScreen="true"></iframe>
|
188 |
-
"""
|
189 |
-
|
190 |
-
st.components.v1.html(power_bi_html)
|
191 |
-
|
192 |
-
# Ensure full-screen height using CSS
|
193 |
-
with st.empty():
|
194 |
-
st.write("""
|
195 |
-
<style>
|
196 |
-
html, body {
|
197 |
-
height: 100%;
|
198 |
-
margin: 0;
|
199 |
-
padding: 0;
|
200 |
-
}
|
201 |
-
|
202 |
-
iframe {
|
203 |
-
width: 100%;
|
204 |
-
height: 100vh;
|
205 |
-
}
|
206 |
-
</style>
|
207 |
-
""", unsafe_allow_html=True)
|
208 |
-
|
209 |
|
|
|
|
|
210 |
|
211 |
def prediction():
|
212 |
|
|
|
139 |
Overall, this tool has the potential to make a meaningful contribution to the fight against income inequality and promote a more just and equitable society. βοΈ
|
140 |
""")
|
141 |
|
142 |
+
import streamlit as st
|
143 |
|
144 |
def perform_eda():
|
145 |
+
st.title("Data Insights and Recommendations")
|
146 |
st.write("""
|
147 |
+
ππ Welcome to the Exploratory Data Analysis for the Income Prediction Project! ππ
|
148 |
+
Gain a comprehensive understanding of income distribution and explore the factors contributing to an individual's income level based on the census data used to build this prediction tool.
|
149 |
+
Dive into the wealth of data and uncover insights about income prediction. Explore the data and understand the factors contributing to an individual's income level. Let's begin our data-driven journey! π°π
|
150 |
""")
|
151 |
|
152 |
# Show the Power BI dashboard
|
|
|
162 |
From the dashboard, you can now appreciate the serious income inequality problem. Explore key insights and actionable recommendations for stakeholders to fight income inequality.
|
163 |
""")
|
164 |
|
165 |
+
# Add a screenshot of the Power BI dashboard
|
166 |
+
st.subheader("Exploring Income Data")
|
167 |
+
st.write("Let's dive deeper into the data to understand income distribution and relationships between variables.")
|
168 |
+
st.image("path_to_your_screenshot_image.png", use_column_width=True)
|
169 |
+
|
170 |
+
# Provide a link to the full Power BI dashboard
|
171 |
+
st.write("Explore the full Power BI dashboard [here](https://app.powerbi.com/view?r=eyJrIjoiZDNjMmExZjYtMWU2NS00NTBjLTk4Y2EtYmQ2MWU2OWMwODMyIiwidCI6IjQ0ODdiNTJmLWYxMTgtNDgzMC1iNDlkLTNjMjk4Y2I3MTA3NSJ9).")
|
172 |
+
|
173 |
# Table with insights and recommendations
|
174 |
+
st.subheader("Insights and Recommendations")
|
175 |
st.table([
|
176 |
["π Higher education levels positively correlate with higher income.", "Invest in accessible and quality education, including scholarships and vocational training, for lower-income communities."],
|
177 |
["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."],
|
|
|
183 |
["π Data-driven insights are crucial for addressing income inequality.", "Continue investing in data collection and analysis to inform evolving policies."]
|
184 |
])
|
185 |
|
|
|
186 |
def power_bi():
|
187 |
"""
|
188 |
+
Display a screenshot of the Power BI dashboard with a link to the full dashboard.
|
189 |
"""
|
190 |
|
191 |
st.subheader("Exploring Income Data")
|
192 |
st.write("Let's dive deeper into the data to understand income distribution and relationships between variables.")
|
193 |
|
194 |
+
# Add a screenshot of the Power BI dashboard
|
195 |
+
st.image("default.jpg", use_column_width=True)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
196 |
|
197 |
+
# Provide a link to the full Power BI dashboard
|
198 |
+
st.write("Explore the full Power BI dashboard [here](https://app.powerbi.com/view?r=eyJrIjoiZDNjMmExZjYtMWU2NS00NTBjLTk4Y2EtYmQ2MWU2OWMwODMyIiwidCI6IjQ0ODdiNTJmLWYxMTgtNDgzMC1iNDlkLTNjMjk4Y2I3MTA3NSJ9).")
|
199 |
|
200 |
def prediction():
|
201 |
|