spacex_dash_app-10.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',...)
                                dcc.RangeSlider(id='payload-slider',
                                                min=0, max=10000, step=1000,
                                                marks={0: '0',
                                                    100: '100'},
                                                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
# 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
    if entered_site == 'ALL':
        fig = px.pie(filtered_df, values='class', 
        names='Launch Site', 
        title='Total Success Launches By Site')
        return fig
    else:
        # return the outcomes piechart for a selected site
        filtered_df=spacex_df[spacex_df['Launch Site']== entered_site]
        filtered_df=filtered_df.groupby(['Launch Site','class']).size().reset_index(name='class count')
        fig=px.pie(filtered_df,values='class count',names='class',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='site-dropdown', component_property='value'), Input(component_id="payload-slider", component_property="value"))

def get_scatter_plot(entered_site, payload_slider):
    filtered_df = spacex_df[(spacex_df['Payload Mass (kg)']>= payload_slider[0]) & (spacex_df['Payload Mass (kg)']<= payload_slider[1])]
    if entered_site == 'ALL':
        fig2 = px.scatter(x = filtered_df['Payload Mass (kg)'], y = filtered_df['class'],
        color = filtered_df['Booster Version Category'],
        title='Correlation between Payload and Success')
        return fig2
    else:
        # return the outcomes piechart for a selected site
        filtered_df=spacex_df[spacex_df['Launch Site']== entered_site]
        fig2 = px.scatter(x = filtered_df['Payload Mass (kg)'], y = filtered_df['class'],
        color = filtered_df['Booster Version Category'],
        title='Correlation between Payload and Success')
        return fig2

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