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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 charts.""" | |
| chart_data = data.copy() | |
| chart_data['Date'] = pd.to_datetime(chart_data['Date']) | |
| chart_data['Date'] = chart_data['Date'].dt.strftime('%m-%d') | |
| # Plot the line charts | |
| if metrics1 in chart_data.columns: | |
| st.line_chart(data=chart_data,x='Date',y=metrics1) | |
| if metrics2 in chart_data.columns: | |
| st.line_chart(data=chart_data,x='Date',y=metrics2) | |
| if metrics3 in chart_data.columns: | |
| st.line_chart(data=chart_data,x='Date',y=metrics3) | |
| def generate_pie_chart(data, widget_id, chart_title): | |
| """Generate Pie Chart.""" | |
| options = ['Watch time (mins)', 'Stream time (mins)', 'Average viewers'] | |
| 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 = ['Watch time (mins)', 'Stream time (mins)', 'Average viewers'] | |
| 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 Watch time (mins), Stream time (mins), Average viewers', | |
| 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("Twitch Share of Voice") | |
| # Read CSV file | |
| filename = 'csvs/SOV - Twitch_SOV.csv' | |
| data = read_data(filename) | |
| # Generate line chart | |
| st.subheader("Axie Infinity Trend") | |
| generate_line_chart(data,'Watch time (mins)', 'Stream time (mins)', 'Average viewers') | |
| piedf_sov = pd.read_csv('csvs/SOV - Twitch_axie_vs_field.csv') | |
| generate_pie_chart(piedf_sov,'Select 7 day Metrics','7 Days SOV') | |
| generate_bar_chart(piedf_sov,' ') | |
| pie90_df = pd.read_csv('csvs/SOV - Twitch_90_day.csv') | |
| generate_pie_chart(pie90_df,'Select 90 days Metrics','90 Days SOV') | |
| generate_bar_chart(pie90_df,' ') | |
| if __name__ == '__main__': | |
| main() | |