app1.py

# Import required libraries


import pandas as pd
import dash
from dash import html
from dash import dcc
from dash.dependencies import Input, Output
import plotly.express as px

# Read the airline data into pandas dataframe
spacex_df = pd.read_csv("https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBM-DS0321EN-SkillsNetwork/datasets/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__)
server = app.server

# Create an app layout
app.layout = html.Div(children=[html.H1('SpaceX Launch Records Dashboard',
                                        style={'textAlign': 'center', 'color': '#503D36',
                                               'font-size': 40}),
                                html.H4("This dashboard was created to help the prediction about Falcon9 first stage will land successfully .SpaceX advertises Falcon 9 rocket launches on its website, with a cost of 62 million dollars; other providers cost upward of 165 million dollars each, much of the savings is because SpaceX can reuse the first stage. Therefore, if we can determine if the first stage will land, we can determine the cost of a launch. This information can be used if an alternate company wants to bid against SpaceX for a rocket launch. ", 
                                style={'textAlign':"center", 'font-size':20}),
                                # 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': '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
                                             # 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')),
                                ])

# 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='Success Count for all launch sites')
        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 scatter(entered_site,payload):
    filtered_df = spacex_df[spacex_df['Payload Mass (kg)'].between(payload[0],payload[1])]
    # thought reusing filtered_df may cause issues, but tried it out of curiosity and it seems to be working fine
    
    if entered_site=='ALL':
        fig=px.scatter(filtered_df,x='Payload Mass (kg)',y='class',color='Booster Version Category',title='Success count on Payload mass for all sites')
        return fig
    else:
        fig=px.scatter(filtered_df[filtered_df['Launch Site']==entered_site],x='Payload Mass (kg)',y='class',color='Booster Version Category',title=f"Success count on Payload mass for site {entered_site}")
        return fig

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