from dash import Dash, html, dcc, Input, Output
import pandas as pd
import plotly.express as px

# # Load the dataset
df = pd.read_parquet('cincinnati_traffic_crash_data__cpd.parquet')

# 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__)
server = app.server

# 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)