Week 3 - Interactive Dashboard with Ploty Dash - 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()

launchSiteDF = spacex_df['Launch Site'].unique()
launchSiteOptions = ['ALL']
launchSiteOptions.extend(sorted(launchSiteDF))

# 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' if i == 'ALL' else i), 'value': i} for i in launchSiteOptions
                                        #{'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', 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'))

# Add computation to callback function and return graph
def get_graph(entered_site):
    filtered_df = spacex_df
    if entered_site == 'ALL':
        fig = px.pie(data_frame = filtered_df[filtered_df['class'] == 1], names = 'Launch Site', values = 'class', title = 'Total Success Launches for All Sites')
        return fig
    else:
        filtered_df = spacex_df[spacex_df['Launch Site'] == entered_site]
        fig = px.pie(data_frame = filtered_df, names = 'class', title = 'Total Launches for %s' % 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')])

# Add computation to callback function and return graph
def update_graph(site_dropdown, entered_payload):
    if site_dropdown == 'ALL':
        filtered_df = spacex_df[(spacex_df['Payload Mass (kg)'] >= entered_payload[0]) & (spacex_df['Payload Mass (kg)'] <= entered_payload[1])]
        fig = px.scatter(data_frame = filtered_df, x = "Payload Mass (kg)", y = "class", color = "Booster Version Category")
        return fig
    else:
        specific_df = spacex_df.loc[spacex_df['Launch Site'] == site_dropdown]
        filtered_df = specific_df[(specific_df['Payload Mass (kg)'] >= entered_payload[0]) & (spacex_df['Payload Mass (kg)'] <= entered_payload[1])]
        fig = px.scatter(data_frame = filtered_df, x = "Payload Mass (kg)", y = "class", color = "Booster Version Category")
        return fig

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