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5.2 Launch_Site_Dashboard.py
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# 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(r"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',
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',
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',
min=0, max=10000, step=1000,
marks={
0: '0',
2000: '2000',
4000: '4000',
6000: '6000',
8000: '8000',
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')
)
def get_pie_chart(selected_site):
filtered_df = spacex_df
if selected_site == 'ALL':
fig = px.pie(
filtered_df,
values='class',
names='Launch Site',
title='Success Rate of All Launch Sites'
)
return fig
else:
filtered_df = filtered_df[filtered_df['Launch Site']==selected_site]
success_rate = filtered_df.mean()['class']
fig = px.pie(
filtered_df,
values=[success_rate, 1-success_rate],
names=filtered_df['class'].unique(),
title=f'Success and Failure Rate in {selected_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(selected_site, slider_values):
filtered_df = spacex_df
if selected_site == 'ALL':
filtered_df = filtered_df[
(filtered_df['Payload Mass (kg)']>=slider_values[0]) &
(filtered_df['Payload Mass (kg)']<=slider_values[1])
]
fig = px.scatter(
filtered_df,
x='Payload Mass (kg)',
y='class',
color='Booster Version Category',
)
return fig
else:
filtered_df = filtered_df[
(filtered_df['Launch Site']==selected_site) &
(filtered_df['Payload Mass (kg)']>=slider_values[0]) &
(filtered_df['Payload Mass (kg)']<=slider_values[1])
]
fig = px.scatter(
filtered_df,
x='Payload Mass (kg)',
y='class',
color='Booster Version Category',
)
return fig
# python3.8 spacex_dash_app.py
# Run the app
if __name__ == '__main__':
app.run_server()