awacke1 commited on
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5739290
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1 Parent(s): e6bed31

Update app.py

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Files changed (1) hide show
  1. app.py +22 -43
app.py CHANGED
@@ -2,34 +2,37 @@ import streamlit as st
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  import pandas as pd
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  import random
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  # Magic commands
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  st.set_page_config(page_title='Streamlit Super Power Cheat Sheet - Gamified')
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- #st.set_option('deprecation.showfileUploaderEncoding', False)
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- # Define player cards
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- player1 = [{'Word': 'Strategy', 'Definition': 'A plan of action designed to achieve a long-term or overall aim.'},
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- {'Word': 'Economics', 'Definition': 'The branch of knowledge concerned with the production, consumption, and transfer of wealth.'},
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- {'Word': 'Industry', 'Definition': 'Economic activity concerned with the processing of raw materials and manufacture of goods in factories.'}]
 
 
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- player2 = [{'Word': 'Manufacturing', 'Definition': 'The making of articles on a large scale using machinery.'},
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- {'Word': 'Transportation', 'Definition': 'The action of transporting someone or something or the process of being transported.'},
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- {'Word': 'Community', 'Definition': 'A group of people living in the same place or having a particular characteristic in common.'}]
 
 
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- # Create dataframes for each player card
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  df_player1 = pd.DataFrame(player1)
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  df_player2 = pd.DataFrame(player2)
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-
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- # Merge the dataframes on word matches
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  df_matches = pd.merge(df_player1, df_player2, on='Word')
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- # Display the merged dataframe
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  st.dataframe(df_matches)
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- # Display the word match count
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  match_count = df_matches.shape[0]
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  st.write(f'Number of word matches: {match_count}')
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- # Display a random word match
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  if match_count > 0:
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  random_match = df_matches.iloc[random.randint(0, match_count-1)]
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  st.write(f'Random match: {random_match["Word"]}')
@@ -38,15 +41,7 @@ if match_count > 0:
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  else:
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  st.write('No word matches')
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- # Emoji graphics
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- AI = 'πŸ€–'
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- DATA = 'πŸ“Š'
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- EMOJIS = ['🀣', 'πŸ˜‚', '😜', 'πŸ€ͺ', '😎', 'πŸ€”']
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-
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- # strategy data
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- import pandas as pd
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-
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- # Define the strategy classifications and their definitions
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  strategy_data = [
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  {'Classification': 'Economic', 'Definition': 'πŸ’° The branch of knowledge concerned with the production, consumption, and transfer of wealth.'},
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  {'Classification': 'Industry', 'Definition': '🏭 Economic activity concerned with the processing of raw materials and manufacture of goods in factories.'},
@@ -58,31 +53,15 @@ strategy_data = [
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  {'Classification': 'Network', 'Definition': '🌐 A group of interconnected people, companies, or devices that share information or resources.'},
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  ]
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- st.markdown("""
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- Classification Definition
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- 0 Economic πŸ’° The branch of knowledge concerned with the p...
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- 1 Industry 🏭 Economic activity concerned with the process...
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- 2 Manufacturing 🏭 The making of articles on a large scale usin...
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- 3 Development πŸ—οΈ The process of growth, progress, or realiz...
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- 4 Transport πŸš— The movement of people, goods, or materials ...
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- 5 Income πŸ’Έ The money received by a person, company, or ...
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- 6 Market πŸ“ˆ A regular gathering of people for the purcha...
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- 7 Network 🌐 A group of interconnected people, companies,...
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- """)
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-
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- # Create a dataframe from the strategy data
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  df_strategy = pd.DataFrame(strategy_data)
 
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- # Display the dataframe
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- print(df_strategy)
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-
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-
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- # Example AI data
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  ai_data = {'accuracy': 0.89, 'precision': 0.72, 'recall': 0.64, 'f1': 0.68}
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-
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- # One-liner functions
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  st.write(f"{AI} I'm sorry Dave, I'm afraid I can't do that.")
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  st.dataframe(pd.DataFrame(ai_data, index=['Model']))
 
 
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  st.table(pd.DataFrame(ai_data, index=['Model']))
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  st.json({'foo':'bar', 'fu':'ba', 'ai_data': ai_data})
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  st.metric(label="Model Accuracy", value=ai_data['accuracy'], delta=0.02)
 
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  import pandas as pd
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  import random
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+ # Constants
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+ AI = 'πŸ€–'
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+ DATA = 'πŸ“Š'
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+ EMOJIS = ['🀣', 'πŸ˜‚', '😜', 'πŸ€ͺ', '😎', 'πŸ€”']
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+
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  # Magic commands
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  st.set_page_config(page_title='Streamlit Super Power Cheat Sheet - Gamified')
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+ st.set_option('deprecation.showfileUploaderEncoding', False)
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+ # ------------------------- PLAYER CARDS -------------------------
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+ player1 = [
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+ {'Word': 'Strategy', 'Definition': 'A plan of action designed to achieve a long-term or overall aim.'},
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+ {'Word': 'Economics', 'Definition': 'The branch of knowledge concerned with the production, consumption, and transfer of wealth.'},
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+ {'Word': 'Industry', 'Definition': 'Economic activity concerned with the processing of raw materials and manufacture of goods in factories.'}
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+ ]
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+ player2 = [
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+ {'Word': 'Manufacturing', 'Definition': 'The making of articles on a large scale using machinery.'},
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+ {'Word': 'Transportation', 'Definition': 'The action of transporting someone or something or the process of being transported.'},
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+ {'Word': 'Community', 'Definition': 'A group of people living in the same place or having a particular characteristic in common.'}
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+ ]
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  df_player1 = pd.DataFrame(player1)
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  df_player2 = pd.DataFrame(player2)
 
 
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  df_matches = pd.merge(df_player1, df_player2, on='Word')
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  st.dataframe(df_matches)
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  match_count = df_matches.shape[0]
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  st.write(f'Number of word matches: {match_count}')
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  if match_count > 0:
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  random_match = df_matches.iloc[random.randint(0, match_count-1)]
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  st.write(f'Random match: {random_match["Word"]}')
 
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  else:
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  st.write('No word matches')
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+ # ------------------------- STRATEGY DATA -------------------------
 
 
 
 
 
 
 
 
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  strategy_data = [
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  {'Classification': 'Economic', 'Definition': 'πŸ’° The branch of knowledge concerned with the production, consumption, and transfer of wealth.'},
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  {'Classification': 'Industry', 'Definition': '🏭 Economic activity concerned with the processing of raw materials and manufacture of goods in factories.'},
 
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  {'Classification': 'Network', 'Definition': '🌐 A group of interconnected people, companies, or devices that share information or resources.'},
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  ]
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  df_strategy = pd.DataFrame(strategy_data)
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+ st.dataframe(df_strategy)
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+ # ------------------------- AI DATA -------------------------
 
 
 
 
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  ai_data = {'accuracy': 0.89, 'precision': 0.72, 'recall': 0.64, 'f1': 0.68}
 
 
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  st.write(f"{AI} I'm sorry Dave, I'm afraid I can't do that.")
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  st.dataframe(pd.DataFrame(ai_data, index=['Model']))
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+
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+ # ------------------------- ONE-LINER FUNCTIONS -------------------------
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  st.table(pd.DataFrame(ai_data, index=['Model']))
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  st.json({'foo':'bar', 'fu':'ba', 'ai_data': ai_data})
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  st.metric(label="Model Accuracy", value=ai_data['accuracy'], delta=0.02)