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spacex_dash_app.py
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spacex_dash_app.py
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# 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',
options=[
{'label': 'All Sites', 'value': 'All Sites'},
{'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'}
],
placeholder='Select a Launch Site Here',
value='All Sites',
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={i: '{}'.format(i) for i in range(0, 10001, 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(launch_site):
if launch_site == 'All Sites':
fig = px.pie(values=spacex_df.groupby('Launch Site')['class'].mean(),
names=spacex_df.groupby('Launch Site')['Launch Site'].first(),
title='Total Success Launches by Site')
else:
fig = px.pie(values=spacex_df[spacex_df['Launch Site']==str(launch_site)]['class'].value_counts(normalize=True),
names=spacex_df['class'].unique(),
title='Total Success Launches for Site {}'.format(launch_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_payload_chart(launch_site, payload_mass):
if launch_site == 'All Sites':
fig = px.scatter(spacex_df[spacex_df['Payload Mass (kg)'].between(payload_mass[0], payload_mass[1])],
x="Payload Mass (kg)",
y="class",
color="Booster Version Category",
hover_data=['Launch Site'],
title='Correlation Between Payload and Success for All Sites')
else:
df = spacex_df[spacex_df['Launch Site']==str(launch_site)]
fig = px.scatter(df[df['Payload Mass (kg)'].between(payload_mass[0], payload_mass[1])],
x="Payload Mass (kg)",
y="class",
color="Booster Version Category",
hover_data=['Launch Site'],
title='Correlation Between Payload and Success for Site {}'.format(launch_site))
return(fig)
# Run the app
if __name__ == '__main__':
app.run_server()