spacex_dash_app.py

# Import required libraries
import pandas as pd
import dash
import dash_html_components as html
import dash_core_components as 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 Dashboard',
                                        style={'textAlign': 'center', 'color': '#503D36',
                                               'font-size': 40}),
                                # TASK 1: Add a dropdown list to enable Launch Site selection
                                # The default select value is for ALL sites
                                dcc.Dropdown(id='site-dropdown',options=[
                                {'label': 'All Sites', 'value': 'ALL'},
                                {'label': 'Cape Canaveral Launch Complex 40 (CAFS LC-40)', 'value': 'CCAFS LC-40'},
                                {'label': 'Cape Canaveral Space Launch Complex 40 (CCAFS SLC-40)', 'value': 'CCAFS SLC-40'},
                                {'label': 'Kennedy Space Center Launch Complex 39A (KSC LC-39A)', 'value': 'KSC LC-39A'},
                                {'label': 'Vandenberg Air Force Base Space Launch Complex (VAFB SLC-4E)', 'value': 'VAFB SLC-4E'}
                                ],
                                value='ALL',
                                placeholder="Select a Launch Site",
                                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',
                                min=0, max=10000, step=1000,
                                marks={0: '0', 100: '100'},
                                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 get_pie_chart(entered_site):
    if not entered_site:
        return px.pie(labels=['No Data'], values=[1], title='No Data Available')

    if entered_site == 'ALL':
        filtered_df = spacex_df.groupby(['Launch Site'], as_index=False)['class'].mean()
        filtered_df['Launch Site'] = 'All Sites'
    else:
        filtered_df = spacex_df[spacex_df['Launch Site'] == entered_site]
    
    counts = filtered_df['class'].value_counts().to_dict()
    outcomes_df = pd.DataFrame(list(counts.items()), columns=['Outcome', 'Count'])

    fig = px.pie(outcomes_df, values='Count', names='Outcome', title=f'Launch Success Rate For {entered_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 get_scatter_chart(entered_site, slider):
    filtered_df = spacex_df[
        (slider[0] <= spacex_df['Payload Mass (kg)']) & (spacex_df['Payload Mass (kg)'] <= slider[1])
    ]
    if entered_site == 'ALL':
        return px.scatter(filtered_df,
                          x='Payload Mass (kg)', y='class',
                          color='Booster Version Category',
                          title='Launch Success Rate For All Sites')
    # return the outcomes in pie chart for a selected site
    filtered_df = filtered_df[filtered_df['Launch Site'] == entered_site]
    filtered_df['outcome'] = filtered_df['class'].apply(lambda x: 'Success' if (x == 1) else 'Failure')
    filtered_df['counts'] = 1
    return px.scatter (filtered_df,
                       x='Payload Mass (kg)', y='class',
                       color='Booster Version Category',
                       title='Launch Success Rate For ' + entered_site)

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