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Dockerfile

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+# Use a lightweight Python image as the base
+FROM python:3.9-slim
+
+# Set the working directory
+WORKDIR /app
+
+# Copy the project files to the container
+COPY . /app
+
+# Install dependencies
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Expose Streamlit's default port
+EXPOSE 7860
+
+# Command to run the Streamlit app
+CMD ["streamlit", "run", "app.py", "--server.port=7860", "--server.address=0.0.0.0"]

app.py

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+import streamlit as st
+import requests
+import pandas as pd
+
+# Set the FastAPI base URL
+API_URL = "https://logeswari-backapp.hf.space"
+
+# Streamlit app title
+st.title("⭐World Population Dashboard")
+
+# Sidebar filter for continents
+st.sidebar.header("Filter")
+selected_continent = st.sidebar.selectbox(
+    "Select the Continent:",
+    ['Asia', 'Africa', 'North America', 'South America', 'Europe', 'Oceania']
+)
+
+# Fetch data from the FastAPI endpoint
+if st.sidebar.button("Get Data"):
+    # Call FastAPI to get continent data
+    response = requests.get(f"{API_URL}/continent/{selected_continent}")
+    
+    if response.status_code == 200:
+        data = response.json()
+        st.write(data)
+
+        # Display the continent information
+        st.header(f"Data of {data['continent']}")
+        st.metric("Total Population", f"{data['total_population']:,}")
+        st.metric("Total Area (sq km)", f"{data['total_area']:,}")
+        st.metric("Population Density", f"{data['continent_population_density']:.2f}")
+        st.subheader("Population Highlights")
+        st.write(
+            f"Max Population :{data['max_population']['country']} "
+            f"({data['max_population']['population']:,})"
+        )
+        # Country with min population
+        st.write(
+            f"Min Population:{data['min_population']['country']} "
+            f"({data['min_population']['population']:,})"
+        )
+
+        # countries_data=data['countries']
+        # country_df = pd.DataFrame(countries_data)
+        # st.subheader(f"Population of Countries in {data['continent']}")
+        # st.bar_chart(country_df.set_index("Country"))z
+    else:
+        # Handle errors
+        st.error(f"Error: {response.json()['detail']}")
+
+
+data=pd.read_csv('D:\pandas\world_population (1).csv')
+st.dataframe(data)        

requirements.txt

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+streamlit
+requests
+pandas