Create app.py

app.py

@@ -0,0 +1,49 @@
+import streamlit as st
+import pandas as pd
+
+# Load the CSV data
+@st.cache_data
+def load_data(file_path):
+    df = pd.read_csv(file_path)
+    return df
+
+# Paginate function
+def paginate_data(df, page_number, page_size):
+    start_index = page_number * page_size
+    end_index = start_index + page_size
+    return df[start_index:end_index]
+
+# Streamlit app
+def main():
+    st.title("Emotion Filter and Pagination App")
+
+    # Load the data
+    file_path = 'your_data.csv'  # Ensure this is the correct path to your uploaded CSV file
+    df = load_data(file_path)
+
+    # Dropdown for selecting emotion
+    unique_emotions =  ["admiration", "amusement", "anger", "annoyance", "approval",
+                  "caring", "confusion", "curiosity", "desire", "disappointment",
+                  "disapproval", "disgust", "embarrassment", "excitement", "fear",
+                  "gratitude", "grief", "joy", "love", "nervousness", "optimism",
+                  "pride", "realization", "relief", "remorse", "sadness", "surprise",
+                  "neutral"]
+    selected_emotion = st.selectbox('Select Emotion', unique_emotions)
+
+    # Filter the data based on the selected emotion and sort by score
+    filtered_data = df[df['emotion_label'] == selected_emotion].sort_values(by='score', ascending=False).head(100)
+
+    # Pagination settings
+    page_size = 10
+    total_pages = (len(filtered_data) // page_size) + 1
+    page_number = st.number_input('Page number', 0, total_pages - 1, 0)
+
+    # Paginate data
+    paginated_data = paginate_data(filtered_data, page_number, page_size)
+
+    # Display the paginated data
+    st.write(f"Showing page {page_number + 1} of {total_pages}")
+    st.write(paginated_data)
+
+if __name__ == "__main__":
+    main()