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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'},
{'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="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=1,
marks={0: '0',
1000: '1000',
2000: '2000',
3000: '3000',
4000: '4000',
5000: '5000',
6000: '6000',
7000: '7000',
8000: '8000',
9000: '9000',
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
# Function decorator to specify function input and 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):
if entered_site == 'ALL':
filtered_df = spacex_df
fig = px.pie(filtered_df, values='class',
names='Launch Site',
title='Total success launches by site')
return fig
else:
# return the outcomes piechart for a selected site
filtered_df = pd.DataFrame(spacex_df[spacex_df['Launch Site']== entered_site]['class'].value_counts())
fig = px.pie(filtered_df, values='class',
names=filtered_df.index,
title=f'Success launches for {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 get_scatter_chart(entered_site, entered_payload):
if entered_site == 'ALL':
df = spacex_df
df = df[df['Payload Mass (kg)'].isin(range(entered_payload[0], entered_payload[1]))]
fig = px.scatter(df, x="Payload Mass (kg)", y="class", color="Booster Version Category")
return fig
else:
df = spacex_df[spacex_df['Launch Site']== entered_site]
df = df[df['Payload Mass (kg)'].isin(range(entered_payload[0], entered_payload[1]))]
fig = px.scatter(df, x="Payload Mass (kg)", y="class", color="Booster Version Category")
#print(entered_site, entered_payload) #just to check
return fig
# Run the app
if __name__ == '__main__':
app.run_server()