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()
min_value = min_payload
max_value = max_payload


# 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': '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', min=0, max=10000, step=1000,
                                    marks={0:'0', 2500: '2500', 5000:'5000', 7500:'7500', 10000:'10000'}, 
                                    value=[min_value, max_value]),

                                # 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
# Function decorator to specify function input and 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):
    filtered_df = spacex_df
    if entered_site == 'ALL':
        fig = px.pie(filtered_df, values='class', 
            names='Launch Site', 
            title='Total Success Launches By Site')
        return fig
    else:
        # return the outcomes piechart for a selected site
        fig = px.pie(filtered_df[filtered_df['Launch Site']==entered_site],  
            names='class', 
            title='Total Success Launches for site ' + 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(site, payload_Range):
    if site == 'ALL':
        fig = px.scatter(spacex_df[ (spacex_df['Payload Mass (kg)']>=payload_Range[0]) & 
            (spacex_df['Payload Mass (kg)']<=payload_Range[1]) ], 
            x="Payload Mass (kg)", y="class", color= "Booster Version Category")
    else:
        fig = px.scatter(spacex_df[ (spacex_df['Launch Site']==site) & 
            (spacex_df['Payload Mass (kg)']>=payload_Range[0]) &
            (spacex_df['Payload Mass (kg)']<=payload_Range[1]) ], 
            x="Payload Mass (kg)", y="class", color= "Booster Version Category")
    return fig

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