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': '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 kg', 2500:'2500', 5000:'5000', 7500:'7500', 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
@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 entered_site=='ALL':
        df_all = spacex_df #.groupby('class').size().reset_index(name='class count')
        fig = px.pie(df_all, values='class',
        names='Launch Site',
        title='Total Success Launches by Site')
        return fig
    
    else:
        df_ind = spacex_df[spacex_df['Launch Site'] == entered_site].groupby(['Launch Site', 'class']).size().reset_index(name='class count')
        fig = px.pie(df_ind, values='class count',
        names='class count',
        title=f'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='payload-slider', component_property='value'),
              Input(component_id='site-dropdown', component_property='value'))

def get_scatter_chart(slider, entered_site):

    filtered_df2 = spacex_df[(slider[0] <= spacex_df['Payload Mass (kg)']) & (spacex_df['Payload Mass (kg)'] <= slider[1])]

    if entered_site == 'ALL':
        fig = px.scatter(filtered_df2, x = 'Payload Mass (kg)', y = 'class', color='Booster Version Category',
        title='Correlation between Payload and Success for site all sites')
        return fig
    
    else:
        filtered_df2_2 = filtered_df2[filtered_df2['Launch Site']==entered_site]
        fig = px.scatter(filtered_df2_2, x = 'Payload Mass (kg)', y = 'class', color = 'Booster Version Category', 
        title='title')
        return fig

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