Plotly Dash Application for SpaceX

!pip3 install pandas dash
!pip3 install jupyter_plotly_dash
!pip3 install wget

import pandas as pd
import wget

spacex_file = wget.download('https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBM-DS0321EN-SkillsNetwork/datasets/spacex_launch_dash.csv')

from jupyter_plotly_dash import JupyterDash

import dash
#import dash_core_components as dcc
from dash import dcc
from dash import html
#import dash_html_components as html
from dash.dependencies import Input, Output

import plotly.express as px

# Read the airline data into pandas dataframe
spacex_df = pd.read_csv(spacex_file)
max_payload = spacex_df['Payload Mass (kg)'].max()
min_payload = spacex_df['Payload Mass (kg)'].min()

app = dash.Dash(__name__)

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 Sites'},
                                                          {'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'},

                                                         ],
                                                 searchable=True,
                                                 placeholder='Select a Launch Site here',
                                                 style={'width': '80%', 'padding': '3px','font-size': '20px', 'text-align-last': 'center'}),

                                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, 
                                                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')),])
                
@app.callback(Output(component_id='success-pie-chart', component_property='figure'),
               Input(component_id='site-dropdown', component_property='value'))
            
def get_graph(site_dropdown):
    if site_dropdown == 'ALL':
        piechart = px.pie(spacex_df,values='class', names='Launch Site', title=f"Success Launches for site {site_dropdown}" ) 
        return piechart

    else:
        filtered_df= spacex_df[spacex_df['Launch Site'] == site_dropdown]
        filtered_df= filtered_df.groupby(['Launch Site', 'class']).size().reset_index(name='class count')
        piechart = px.pie(filtered_df, values='class count', names='class', title=f"Success Launches for site {site_dropdown}" )
        return piechart

# 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(site_dropdown,slider_range,):
    low, high = slider_range
    mask = (spacex_df['Payload Mass (kg)'] > low) & (spacex_df['Payload Mass (kg)'] < high)
    filtered_df = spacex_df[mask] 
    
    if site_dropdown == 'ALL':
        #Display all values for the variable
        filtered_df= spacex_df[spacex_df['Launch Site'] == site_dropdown]
        filtered_ddf = pd.DataFrame(filtered_df(['Launch Site']))
        fig = px.scatter(filtered_ddf,x="Payload Mass (kg)", y="class", color="Booster Version Category", title='Payload vs. Outcome for All Sites')
        return fig
    else:
        filtered_df1= filtered_df[filtered_df['Launch Site'] == site_dropdown]
        fig = px.scatter(filtered_df1, x="Payload Mass (kg)", y="class", color="Booster Version Category", title=f"Payload and Booster Versions for site {site_dropdown}")
        return fig

    
if __name__ == '__main__':
    app.run_server()