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Update app.py
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app.py
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import streamlit as st
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import pandas as pd
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# Magic commands
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st.set_page_config(page_title='Streamlit Cheat Sheet')
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st.set_option('deprecation.showfileUploaderEncoding', False)
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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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# 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"]}')
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st.write(f'{random_match["Definition_x"]}')
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st.write(f'{random_match["Definition_y"]}')
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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 = 'π€'
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DATA = 'π'
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EMOJIS = ['π€£', 'π', 'π', 'π€ͺ', 'π', 'π€']
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# strategy data
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import pandas as pd
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# Define the strategy classifications and their definitions
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strategy_data = [
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{'Classification': 'Economic', 'Definition': 'π° The branch of knowledge concerned with the production, consumption, and transfer of wealth.'},
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{'Classification': 'Industry', 'Definition': 'π Economic activity concerned with the processing of raw materials and manufacture of goods in factories.'},
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{'Classification': 'Manufacturing', 'Definition': 'π The making of articles on a large scale using machinery.'},
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{'Classification': 'Development', 'Definition': 'ποΈ The process of growth, progress, or realization of goals.'},
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{'Classification': 'Transport', 'Definition': 'π The movement of people, goods, or materials from one place to another.'},
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{'Classification': 'Income', 'Definition': 'πΈ The money received by a person, company, or country for work, services, or investment.'},
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{'Classification': 'Market', 'Definition': 'π A regular gathering of people for the purchase and sale of goods.'},
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{'Classification': 'Network', 'Definition': 'π 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 π° The branch of knowledge concerned with the p...
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1 Industry π Economic activity concerned with the process...
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2 Manufacturing π The making of articles on a large scale usin...
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3 Development ποΈ The process of growth, progress, or realiz...
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4 Transport π The movement of people, goods, or materials ...
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5 Income πΈ The money received by a person, company, or ...
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6 Market π A regular gathering of people for the purcha...
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7 Network π A group of interconnected people, companies,...
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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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# 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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# 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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st.button('Hit me ' + random.choice(EMOJIS))
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st.download_button('On the dl', pd.DataFrame({'foo': [1,2,3], 'bar': [4,5,6]}))
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st.checkbox('Tickle me ' + random.choice(EMOJIS))
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st.radio('Choose your favorite ' + DATA, ['Bar chart', 'Pie chart', 'Line chart'])
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st.selectbox('Select your ' + DATA, ['Sales', 'Expenses', 'Profits'])
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st.multiselect('Pick your favorite ' + DATA + 's', ['Revenue', 'Profit', 'Loss'])
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st.slider('Slide to ' + DATA, min_value=0, max_value=10)
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st.select_slider('Slide to select your favorite ' + DATA, options=[1,2,3,4])
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st.text_input('Enter some ' + DATA)
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st.number_input('Enter a random ' + DATA + ' value')
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st.text_area('Type something ' + random.choice(EMOJIS) + ' here')
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st.date_input('Choose a ' + random.choice(['start', 'end']) + ' ' + DATA + ' date')
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st.time_input('What time is it? ' + random.choice(EMOJIS))
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st.file_uploader('Upload your favorite ' + DATA + ' ' + random.choice(EMOJIS))
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st.color_picker('Pick a ' + DATA + ' ' + random.choice(EMOJIS))
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