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': 'CCAFS SLC-40', 'value': 'CCAFS SLC-40'},
                                                {'label': 'KSC LC-39A', 'value': 'KSC LC-39A'},
                                                {'label': 'VAFB SLC-4C', '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',...)
                                dcc.RangeSlider(id = 'payload-slider',
                                min = 0, 
                                max= 10000,
                                step=1000,
                                marks={0: '0',
                                1000: '1000',
                                2000: '2000',
                                3000:'3000',
		                        4000:'4000',
		                        5000:'5000',
		                        6000:'6000',
		                        7000:'7000',
		                        8000:'8000',
                                },
                                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
    if entered_site == 'ALL':
        fig = px.pie(spacex_df, values = 'class',
        names = 'Launch Site',
        title= 'Succesful Launches')
        return fig
    else:
        filtered_df = spacex_df[spacex_df['Launch Site'] == entered_site]
        filtered_df = filtered_df['class'].value_counts().to_frame().reset_index()
        fig = px.pie(filtered_df, values='class',
        names='index',
        title= f'Launches from:{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(Input(component_id='site-dropdown', component_property='value'),
                Input(component_id='payload-slider', component_property = 'value'),
                Output(component_id = 'success-payload-scatter', component_property='figure'))
def get_scatterplot(Sitedropdown, P_range):
    minRange = P_range[0]
    maxRange = P_range[1]
    range_df = spacex_df[(spacex_df['Payload Mass (kg)'] >= minRange) and 
                         (spacex_df['Payload Mass (kg)'] <= maxRange)]
    if Sitedropdown == 'ALL':
        fig = px.scatter(range_df, x = "Payload Mass (kg)", y = "class",
        color = "Booster Version Category", title= "Launch Outcomes based on Payload Mass (kg)")
        return fig
    else: 
        filtered_df1 = range_df[range_df['Launch Site'] == Sitedropdown]
        fig = px.scatter(filtered_df1, x = "Payload Mass (kg)", y = "class",
         color= "Booster Version Category", title= f"Launch Outcomes from {Sitedropdown} based on Payload Mass (kg) from:")
        return fig

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