code: # 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 Sites'},
                                          {'label': 'CCAFS LC-40', 'value': 'CCAFS LC-40'},
                                          {'label': 'VAFB SLC-4E', 'value': 'VAFB SLC-4E'},
                                          {'label': 'KSC LC-39A', 'value': 'KSC LC-39A'},
                                          {'label': 'CCAFS SLC-40', 'value': 'CCAFS SLC-40'},
                                          ],
                                      value='All Sites',
                                      placeholder="Select 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',
                                          1000: '1000',
                                          2000: '2000',
                                          3000: '3000',
                                          4000: '42000',
                                          5000: '5000',
                                          6000: '6000',
                                          7000: '7000',
                                          8000: '8000',
                                          9000: '9000',
                                          10000: '10000'
                                          },
                                      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
  #siteList = sorted(list(set(spacex_df['Launch Site']))) 
  
  # 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[spacex_df['Launch Site'] == entered_site ]
      if entered_site == 'All Sites':
          data = spacex_df
          fig1 = px.pie(data, values='class', 
          names='Launch Site', 
          title='Successful Launches per Site')
      else:
          # return the outcomes piechart for a selected site
          data = filtered_df
          fig1 = px.pie(data, 
          names='class', 
          title=entered_site)
      
      return fig1
  
  # 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
    #  low, high = slider_range
    #  mask = (filtered_df['Payload Mass (kg)'] >= low) & (filtered_df['Payload Mass (kg)'] <= high)
  
      if entered_site == 'All Sites':
          fig2 = px.scatter(filtered_df,  #[mask], 
          x = 'Payload Mass (kg)',
          y = 'class',
          color = 'Booster Version Category', 
          title = 'Correlation Across all sites')  
      else:
          # return the outcomes piechart for a selected site
          data = filtered_df # [mask]
          fig2 = px.scatter(data[data["Launch Site"]==entered_site], 
          x = 'Payload Mass (kg)',
          y = 'class',
          color = 'Booster Version Category', 
          title='Correlation For ' + entered_site)
      return fig2
  
  # Run the app
  if __name__ == '__main__':
      app.run_server()
  
apis: pandas.read_csv