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',...)
                                dcc.Dropdown(id='site-dropdown',
                                            options=[
                                                {'label': 'All Sites', 'value': 'ALL'},
                                                {'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',
                                            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
                                html.Div(dcc.RangeSlider(id='payload-slider',
                                min=0, max=10000, step=1000,
                                marks={0: '0', 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):

    filtered_df = spacex_df[spacex_df['Launch Site']==str(entered_site)]

    #filtered_df = spacex_df
    if entered_site == 'ALL':
        fig = px.pie(spacex_df, values='class', 
        names='Launch Site', 
        title='title')
        return fig
    else:
        filtered_df = filtered_df.groupby(['Launch Site', 'class']).size().reset_index(name='class_count')
        title = f"Total Success Launches for site {entered_site}"
        fig2 = px.pie(filtered_df, values = 'class_count',
        names = 'class', title = title)
        return fig2
     

# 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_plot(entered_site, slider_range):
    filtered_df = spacex_df[spacex_df['Launch Site']==str(entered_site)]
    low, high = slider_range
    mask = (spacex_df['Payload Mass (kg)'] > low) & (spacex_df['Payload Mass (kg)'] < high)

    if entered_site == 'ALL':
        fig = px.scatter(
            spacex_df[mask], x="Payload Mass (kg)", y="class", 
            color='Booster Version Category')
        return fig
    
    else:
        fig2 = px.scatter(
            filtered_df[mask], x="Payload Mass (kg)", y="class", 
            color='Booster Version Category')
        return fig2
        

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