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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',...)
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),
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,
value=[min_payload,max_payload],
marks={0: '0', 2500:'2500',5000:'5000',
7500:'7500', 10000: '10000'}),
# 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 build_graph(site_dropdown):
if site_dropdown == 'ALL':
piechart = px.pie(data_frame = spacex_df, names='Launch Site', values='class' ,title='Total Launches for All Sites')
return piechart
else:
#specific_df = spacex_df['Launch Site']
specific_df=spacex_df.loc[spacex_df['Launch Site'] == site_dropdown]
piechart = px.pie(data_frame = specific_df, names='class',title='Total Launch for a Specific Site')
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 update_graph(site_dropdown, payload_slider):
if site_dropdown == 'ALL':
filtered_data = spacex_df[(spacex_df['Payload Mass (kg)']>=payload_slider[0])
&(spacex_df['Payload Mass (kg)']<=payload_slider[1])]
scatterplot = px.scatter(data_frame=filtered_data, x="Payload Mass (kg)", y="class",
color="Booster Version Category")
return scatterplot
else:
specific_df=spacex_df.loc[spacex_df['Launch Site'] == site_dropdown]
filtered_data = specific_df[(specific_df['Payload Mass (kg)']>=payload_slider[0])
&(spacex_df['Payload Mass (kg)']<=payload_slider[1])]
scatterplot = px.scatter(data_frame=filtered_data, x="Payload Mass (kg)", y="class",
color="Booster Version Category")
return scatterplot
# Run the app
if __name__ == '__main__':
app.run_server()