spacex-dash-visualization.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
                                html.Div(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 kg',
                                    10000: '10000 kg'},
                                    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(filtered_df.loc[filtered_df['class'] == 1],
        values='class',
        names='Launch Site',
        title='Successes')
        return fig
    else:
        filtered_df = filtered_df.loc[filtered_df['Launch Site']
            == entered_site]
        # filtered_df.groupby(['class'])
        fig = px.pie(filtered_df,
        # values='Launch Site',
        names='class',
        title=f'Success & Failure: {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_scattered_plot(entered_site, slider_range):
    filtered_df = spacex_df
    low, high = slider_range
    if entered_site == 'ALL':
        mask = (filtered_df['Payload Mass (kg)'] > low) & (filtered_df['Payload Mass (kg)'] < high)
        fig = px.scatter(
            filtered_df[mask],
            x="Payload Mass (kg)",
            y="class",
            color="Booster Version Category",
            size='Payload Mass (kg)'
        )
        return fig
    else:
        filtered_df = filtered_df.loc[filtered_df['Launch Site']
            == entered_site]
        mask = (filtered_df['Payload Mass (kg)'] > low) & (filtered_df['Payload Mass (kg)'] < high)
        fig = px.scatter(
            filtered_df[mask],
            x="Payload Mass (kg)",
            y="class",
            color="Booster Version Category",
            size='Payload Mass (kg)'
        )
        return fig


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