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| """Third party imports.""" | |
| import streamlit as st | |
| import pandas as pd | |
| import plotly.express as px | |
| import plotly.graph_objects as go | |
| # Read data from CSV | |
| def read_data(filename): | |
| """Read data from csv.""" | |
| df = pd.read_csv(filename) | |
| df['Date'] = pd.to_datetime(df['Date']) # Convert 'Date' column to datetime | |
| return df | |
| def generate_line_chart(data,metrics1="",metrics2="",metrics3=""): | |
| """Generate Line chart.""" | |
| chart_data = data.set_index('Date') # Set 'Date' column as index | |
| # Get user selection from multiselect checkbox | |
| options = st.multiselect('Select Counts to Display', [metrics1, metrics2, metrics3], default=[metrics1,metrics2,metrics3]) | |
| # Plot the line chart based on user selection | |
| selected_columns = [option for option in options if option in chart_data.columns] | |
| if selected_columns: | |
| st.line_chart(chart_data[selected_columns]) | |
| else: | |
| st.write("Please select at least one count to display.") | |
| def generate_pie_chart(data,widget_id,chart_title): | |
| """Generate Pie Chart.""" | |
| options = ['Tweet', 'Retweet Count', 'Likes Count'] | |
| selected_options = st.multiselect(widget_id, options, default=options) | |
| fig = go.Figure() | |
| for option in selected_options: | |
| fig.add_trace(go.Pie(labels=data['Game'], values=data[option], name=option, textinfo='label+percent', textposition='inside')) | |
| fig.update_layout(title=chart_title) | |
| st.plotly_chart(fig) | |
| def generate_bar_chart(data,widget_id): | |
| """Generate Bar Chart.""" | |
| options = ['Tweet', 'Retweet Count', 'Likes Count'] | |
| selected_options = st.multiselect(widget_id, options, default=options) | |
| counts = data.groupby('Game')[selected_options].sum().reset_index() | |
| counts['Total'] = counts[selected_options].sum(axis=1) # Calculate the sum of selected options as the 'Total' column | |
| counts_sorted = counts.sort_values(by='Total', ascending=True) # Sort by the 'Total' column | |
| labels = counts_sorted['Game'] | |
| values = counts_sorted[selected_options] | |
| fig = go.Figure() | |
| for option in selected_options: | |
| fig.add_trace(go.Bar(y=labels, x=values[option], orientation='h', name=option)) | |
| fig.update_layout(title='Count of Tweets, Retweets, and Likes', | |
| xaxis_title='Count', | |
| yaxis_title='Game', | |
| barmode='stack') | |
| st.plotly_chart(fig, use_container_width=True) | |
| # Main function | |
| def main(): | |
| """Initialize the program.""" | |
| st.title("Twitter Share of Voice") | |
| # Read CSV file | |
| filename = 'csvs/SOV - SoV_twitter.csv' | |
| data = read_data(filename) | |
| ronin_filename = 'csvs/SOV - SoV_Ronin.csv' | |
| ronin_data = read_data(ronin_filename) | |
| cyber_filename = 'csvs/SOV - SoV_CyberKong.csv' | |
| cyber_data = read_data(cyber_filename) | |
| # Generate line chart | |
| st.subheader("Axie Infinity Trend") | |
| generate_line_chart(data,'Tweet','Likes Count','Retweet Count') | |
| st.subheader("Ronin Network Trend") | |
| generate_line_chart(ronin_data,'Tweet ','Likes Count ','Retweet Count ') | |
| st.subheader("CyberKongz Trend") | |
| generate_line_chart(cyber_data,'Tweet Count','Likes Count ','Retweet Count ') | |
| pie_df = pd.read_csv('csvs/SOV - Twitter_axie_vs_field.csv') | |
| generate_pie_chart(pie_df,'Select AVF metrics','Axie Infinity vs Field') | |
| generate_bar_chart(pie_df,' ') | |
| chains = pd.read_csv('csvs/SOV - Twitter_RVF - Copy.csv') | |
| generate_pie_chart(chains,'Select chain metrics','Ronin Network vs Other Chains') | |
| generate_bar_chart(chains,' ') | |
| ronin_games_df = pd.read_csv('csvs/SOV - Twitter_ronin_games.csv') | |
| generate_pie_chart(ronin_games_df,'Select Ronin Games metrics','Ronin Games VS Each Other') | |
| generate_bar_chart(ronin_games_df,' ') | |
| rvf_df = pd.read_csv('csvs/SOV - Twitter_RVF.csv') | |
| generate_pie_chart(rvf_df,'Select RVF metrics','Ronin Games VS Field') | |
| generate_bar_chart(rvf_df,' ') | |
| if __name__ == '__main__': | |
| main() | |