spacex_dash_app.py

# Import required libraries
import pandas as pd
import dash
from dash import html
from dash import dcc
from dash.dependencies import Input, Output
import plotly.express as px

# Read the airline data into pandas dataframe
spacex_df = pd.read_csv("spacex_launch_dash.csv")
max_payload = spacex_df['Payload Mass (kg)'].max()
min_payload = spacex_df['Payload Mass (kg)'].min()

# Create a dash application
app = dash.Dash(__name__)

# Create an app layout
app.layout = html.Div(children=[html.H1('SpaceX Launch Records Dashboard1',
                                        style={'textAlign': 'center', 'color': '#503D36',
                                               'font-size': 40}),
                                # TASK 1: Add a dropdown list to enable Launch Site selection
                                dcc.Dropdown(id='site-dropdown',
                                             options=[
                                                 {'label': 'All Sites', 'value': 'ALL'},
                                                 {'label': 'CCAFS LC-40', 'value': 'CCAFS LC-40'},
                                                 {'label': 'CCAFS SLC-40', 'value': 'CCAFS SLC-40'},
                                                 {'label': 'KSC LC-39A', 'value': 'KSC LC-39A'},
                                                 {'label': 'VAFB SLC-4E', 'value': 'VAFB SLC-4E'}
                                             ],
                                             value='ALL',
                                             placeholder="Select a Launch Site here",
                                             searchable=True
                                             ),
                                html.Br(),

                                # TASK 2: Add a pie chart to show the total successful launches count for all sites
                                # If a specific launch site was selected, show the Success vs. Failed counts for the site
                                html.Div(dcc.Graph(id='success-pie-chart')),
                                html.Br(),

                                html.P("Payload range (Kg):"),
                                # TASK 3: Add a slider to select payload range
                                #dcc.RangeSlider(id='payload-slider',...)
                                dcc.RangeSlider(id='payload-slider',
                                min=0, max=10000, step=1000,
                                marks={i: f'{i}' for i in range(0, 10001, 1000)},
                                value=[min_payload, max_payload]),
                                # TASK 4: Add a scatter chart to show the correlation between payload and launch success
                                html.Div(dcc.Graph(id='success-payload-scatter-chart')),
                                ])

# TASK 2:
# Add a callback function for `site-dropdown` as input, `success-pie-chart` as output
@app.callback(
    Output(component_id='success-pie-chart', component_property='figure'),
    Input(component_id='site-dropdown', component_property='value')
)
def update_pie_chart(selected_site):
    if selected_site == 'ALL':
        fig = px.pie(spacex_df, values='class', 
                     names='Launch Site', 
                     title='Total Success Launches by Site')
    else:
        filtered_df = spacex_df[spacex_df['Launch Site'] == selected_site]
        success_counts = filtered_df['class'].value_counts().reset_index()
        success_counts.columns = ['class', 'count']
        fig = px.pie(success_counts, values='count', 
                     names='class', 
                     title=f'Total Success Launches for site {selected_site}')
    return fig
# TASK 4:
# Add a callback function for `site-dropdown` and `payload-slider` as inputs, `success-payload-scatter-chart` as output
@app.callback(
    Output(component_id='success-payload-scatter-chart', component_property='figure'),
    [Input(component_id='site-dropdown', component_property='value'),
     Input(component_id='payload-slider', component_property='value')]
)
def update_scatter_chart(selected_site, selected_payload):
    filtered_df = spacex_df[(spacex_df['Payload Mass (kg)'] >= selected_payload[0]) & 
                            (spacex_df['Payload Mass (kg)'] <= selected_payload[1])]
    if selected_site != 'ALL':
        filtered_df = filtered_df[filtered_df['Launch Site'] == selected_site]
    
    fig = px.scatter(filtered_df, x='Payload Mass (kg)', y='class', color='Booster Version Category',
                     title='Payload vs. Outcome for All Sites' if selected_site == 'ALL' else f'Payload vs. Outcome for {selected_site}')
    return fig

# Run the app
if __name__ == '__main__':
    app.run_server()