spacex_dash_app_FINAL.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-4E','value':'VAFB SLC-4E'}
                                 ],
                                 value='ALL',
                                 placeholder="Select launch site",
                                 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'},
                                                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, values='class', 
        names='Launch Site', 
        title='Total Success Launches for '+ entered_site + ' site')
        return fig
    else:
        filtered_df = spacex_df[spacex_df['Launch Site']==entered_site]
        fig = px.pie(filtered_df, values='Flight Number', 
        names='class', 
        title='Total Success Launches for '+ entered_site + ' 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_chart(entered_site,payload_range):
    filtered_df = spacex_df
    low, high = payload_range
    mask = (filtered_df['Payload Mass (kg)'] > low) & (filtered_df['Payload Mass (kg)'] < high)
    if entered_site == 'ALL':
        fig = px.scatter(filtered_df[mask], x='Payload Mass (kg)',y='class', color='Booster Version Category', 
        title='Correlation between Payload and Success for '+ entered_site + ' site')
        return fig
    else:
        filtered_df = spacex_df[spacex_df['Launch Site']==entered_site]
        fig = px.scatter(filtered_df[mask], x='Payload Mass (kg)',y='class', color='Booster Version Category',
        title='Correlation between Payload and Success for '+ entered_site + ' site')
        return fig

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