feat: update plotly dashboard

Author: anqorithm

plotly/dashboard.py

@@ -2,43 +2,100 @@
 from dash import html, dcc
 import plotly.express as px
 import pandas as pd
+from cassandra.cluster import Cluster
 
 app = dash.Dash(__name__)
 
 
-def fetch_data():
-    return pd.read_excel('stockdata_stocks.xlsx', engine='openpyxl')
+def create_cassandra_session():
+    cluster = Cluster(['localhost'], port=9042)
+    session = cluster.connect('stockdata')
+    return session
 
 
-df = fetch_data()
+def fetch_data_from_cassandra(table_name):
+    session = create_cassandra_session()
+    query = f"SELECT * FROM {table_name}"
+    rows = session.execute(query)
+    df = pd.DataFrame(list(rows))
+    return df
 
-bar_fig = px.bar(df, x='trade_date', y='price', color='trade_type',
-                 barmode='group', title='Price by Trade Date and Type')
-line_fig = px.line(df, x='trade_date', y='price', title='Price Over Time')
 
-scatter_fig = px.scatter(df, x='quantity', y='price',
-                         color='trade_type', title='Price vs Quantity')
+def create_figure(df, chart_type, **kwargs):
+    if df.empty:
+        print(f"No data available for {kwargs.get('title')}")
+        return dcc.Graph()
+    else:
+        if chart_type == 'bar':
+            return px.bar(df, **kwargs)
+        elif chart_type == 'line':
+            return px.line(df, **kwargs)
+        elif chart_type == 'scatter':
+            return px.scatter(df, **kwargs)
+        elif chart_type == 'area':
+            return px.area(df, **kwargs)
+        elif chart_type == 'pie':
+            return px.pie(df, **kwargs)
 
-area_fig = px.area(df, x='trade_date', y='price',
-                   title='Price Trends Over Time')
-pie_fig = px.pie(df, names='trade_type', values='price',
-                 title='Price Distribution by Trade Type')
-histogram_fig = px.histogram(
-    df, x='price', nbins=20, title='Price Distribution')
-box_fig = px.box(df, y='price', x='trade_type',
-                 title='Price Distribution by Trade Type')
 
-app.layout = html.Div(children=[
-    html.H1(children=' RealTime StockStream 💵🕊️'),
+stocks_df = fetch_data_from_cassandra('stocks')
+grouped_stocks_df = fetch_data_from_cassandra('grouped_stocks')
+pivoted_stocks_df = fetch_data_from_cassandra('pivoted_stocks')
+ranked_stocks_df = fetch_data_from_cassandra('ranked_stocks')
+analytics_stocks_df = fetch_data_from_cassandra('analytics_stocks')
+
+bar_fig = create_figure(stocks_df, 'bar', x='trade_date', y='price',
+                        color='trade_type', title='Price by Trade Date and Type')
+line_fig = create_figure(grouped_stocks_df, 'line', x='trade_type',
+                         y='avg_price', title='Average Price by Trade Type')
+scatter_fig = create_figure(ranked_stocks_df, 'scatter', x='quantity',
+                            y='price', color='trade_type', title='Price vs Quantity')
+area_fig = create_figure(pivoted_stocks_df, 'area', x='stock', y=[
+                         'avg_price_buy', 'avg_price_sell'], title='Average Buy vs Sell Price')
+pie_fig = create_figure(analytics_stocks_df, 'pie', names='trade_type',
+                        values='avg_price_overall', title='Overall Average Price Distribution by Trade Type')
+
+
+histogram_fig = create_figure(
+    stocks_df, 'bar', x='quantity', title='Stock Quantity Distribution')
+
+box_plot_fig = create_figure(
+    stocks_df, 'box', x='trade_type', y='price', title='Price Analysis by Trade Type')
+
+heatmap_fig = create_figure(stocks_df, 'heatmap', x='price',
+                            y='quantity', title='Price and Quantity Correlation')
 
-    dcc.Graph(id='bar-chart', figure=bar_fig),
+time_series_fig = create_figure(pivoted_stocks_df, 'line', x='stock', y=[
+                                'avg_price_buy', 'avg_price_sell'], title='Time Series of Buy vs Sell Prices')
+
+candlestick_fig = create_figure(stocks_df, 'candlestick', x='trade_date', open='open_price',
+                                high='high_price', low='low_price', close='close_price', title='Stock Price Movements')
+
+treemap_fig = create_figure(analytics_stocks_df, 'treemap', path=[
+                            'trade_type', 'stock'], values='quantity', title='Treemap of Stock Distribution')
+
+sunburst_fig = create_figure(grouped_stocks_df, 'sunburst', path=[
+                             'trade_type', 'stock'], values='avg_price', title='Sunburst Chart of Stock Categories')
+
+violin_fig = create_figure(ranked_stocks_df, 'violin', x='trade_type',
+                           y='price', title='Violin Plot of Price Distribution')
+
+app.layout = html.Div(children=[
+    html.H1(children='RealTime StockStream 💵🕊️'),
     dcc.Graph(id='line-chart', figure=line_fig),
     dcc.Graph(id='scatter-plot', figure=scatter_fig),
     dcc.Graph(id='area-chart', figure=area_fig),
     dcc.Graph(id='pie-chart', figure=pie_fig),
-    dcc.Graph(id='histogram', figure=histogram_fig),
-    dcc.Graph(id='box-plot', figure=box_fig)
+    dcc.Graph(id='histogram-chart', figure=histogram_fig),
+    dcc.Graph(id='box-plot-chart', figure=box_plot_fig),
+    dcc.Graph(id='heatmap-chart', figure=heatmap_fig),
+    dcc.Graph(id='time-series-chart', figure=time_series_fig),
+    dcc.Graph(id='candlestick-chart', figure=candlestick_fig),
+    dcc.Graph(id='treemap-chart', figure=treemap_fig),
+    dcc.Graph(id='sunburst-chart', figure=sunburst_fig),
+    dcc.Graph(id='violin-chart', figure=violin_fig)
+    # Add more graphs here as needed
 ])
 
 if __name__ == '__main__':
-    app.run_server(debug=True, host='0.0.0.0')
+    app.run_server(debug=True, host='0.0.0.0', port=6060)