spacex_dash_app.py

# 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.graph_objects as go
import plotly.express as px

# Read the airline data into pandas dataframe
spacex_df = pd.read_csv("spacex_launch_dash.csv")
print(spacex_df['Launch Site'].unique())
ls=[{'label': 'All Sites', 'value': 'ALL'}]
for site in (spacex_df['Launch Site'].unique()):
    d={'label': site, 'value': site}
    ls.append(d)
print(ls)
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=ls, value='ALL', placeholder="place holder 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, marks={0: '0', 100: '100'}, value=[0, 9600]),

                                # 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

pie_data = spacex_df.groupby('Launch Site')["class"].sum().reset_index()
pie_data2 = spacex_df.groupby('Launch Site')["class"].mean().reset_index()
print('pie_data:\n')
print(pie_data)
filtered_df =  pie_data[pie_data['Launch Site']=='CCAFS LC-40']
print(filtered_df)

@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[spacex_df['Launch Site']==entered_site]
    success_ttl=sum(filtered_df['class']==1)
    failure_ttl=sum(filtered_df['class']==0)

    # fig = go.Figure(data=go.Scatter(x=line_data['Month'], y=line_data['ArrDelay'], mode='lines', marker=dict(color='green')))
    if entered_site == 'ALL':
        fig = go.Figure(data=[go.Pie(labels=pie_data['Launch Site'], values=pie_data['class'])])
        fig.update_layout({
          'plot_bgcolor': '#edfaee',
          'paper_bgcolor': '#edfaee',
        })
    else:
        fig = go.Figure(data=[go.Pie(labels=['success','failure'], values=[success_ttl, failure_ttl])])
        fig.update_layout({
          'plot_bgcolor': '#edfaee',
          'paper_bgcolor': '#edfaee',
        })
    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 update_output(site, payloadRange):
    low, high = payloadRange
    mask=(spacex_df["Payload Mass (kg)"]<high) & (spacex_df["Payload Mass (kg)"]>low)
    if site=="ALL":
        fig=px.scatter(spacex_df[mask], x="Payload Mass (kg)", y="class", color="Booster Version")
    else:
        fig=px.scatter(spacex_df[spacex_df["Launch Site"]==site][mask], x="Payload Mass (kg)", y="class", color="Booster Version")
    return fig

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