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', '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 Sites'
                                            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,
                                                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 pie(site_dropdown):
    df = spacex_df	
    if site_dropdown == 'ALL':
        #ddf = pd.DataFrame(spacex_df.groupby(['Launch Site']))
        fig = px.pie(df, values='class', names='Launch Site', title='Success Counts for Launch Sites in US')

    else:
        title = f"Total Success Launches for site {site_dropdown}"
        filtered_df= spacex_df[spacex_df['Launch Site'] == site_dropdown]
        df1 = filtered_df.groupby(['Launch Site','class']).size().reset_index(name='class count')
        fig = px.pie(df1, values='class count', names='class', title=title)
        
    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 build_scatter(site,payload):
    low,high = (payload[0], payload[1])
    df = spacex_df
    filtered_dfa = df[df['Payload Mass (kg)'].between(low,high)]
	
    if site == 'ALL':
        #Display all values for the variable
        fig = px.scatter(filtered_dfa,x="Payload Mass (kg)", y="class", color="Booster Version Category", title='Payload vs. Outcome for All Sites')
        return fig
    
    else:
        filtered_dfb= filtered_dfa[filtered_dfa['Launch Site'] == site]
        fig = px.scatter(filtered_dfb,x="Payload Mass (kg)", y="class", color="Booster Version Category", title='Payload vs. Outcome for ' + site)
        return fig

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