Create app.py

app.py

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+from dash import Dash, html, dcc, Input, Output
+import pandas as pd
+import plotly.express as px
+
+# Load the dataset
+df = pd.read_csv('C:/Users/aammann/OneDrive - Great American Insurance Group/Documents/cincinnati_traffic_crash_data__cpd.csv')
+
+# Preprocess the data
+df_grouped = df.groupby('SNA_NEIGHBORHOOD')['DATECRASHREPORTED'].count().reset_index()
+df_grouped.columns = ['Neighborhood', 'Total Crashes']
+
+# Initialize the Dash app
+app = Dash(__name__)
+
+# Create a bar chart
+fig = px.bar(df_grouped, x='Neighborhood', y='Total Crashes', title='Total Traffic Crashes by Neighborhood in Cincinnati')
+
+# Define the layout of the app
+app.layout = html.Div(children=[
+    html.H1(children='Cincinnati Traffic Crashes Dashboard'),
+
+    html.Div(children='''Dash: A web application framework for your data.'''),
+
+    dcc.Dropdown(
+        id='neighborhood-dropdown',
+        options=[{'label': n, 'value': n} for n in df_grouped['Neighborhood']],
+        value=df_grouped['Neighborhood'][0]
+    ),
+
+    dcc.Graph(
+        id='example-graph',
+        figure=fig
+    )
+])
+
+# Callback to update graph based on dropdown selection
+@app.callback(
+    Output('example-graph', 'figure'),
+    [Input('neighborhood-dropdown', 'value')]
+)
+def update_graph(selected_neighborhood):
+    filtered_df = df_grouped[df_grouped['Neighborhood'] == selected_neighborhood]
+    fig = px.bar(filtered_df, x='Neighborhood', y='Total Crashes', title=f'Total Traffic Crashes in {selected_neighborhood}')
+    return fig
+
+# Run the app
+if __name__ == '__main__':
+    app.run(debug=True, port=8051)
+    
+