Dashboard_Plotly_Dash.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "6f748ece-8914-4182-8438-bf52bab21284",
   "metadata": {},
   "outputs": [],
   "source": [
    "from dash import Dash, dcc, html, Input, Output\n",
    "import pandas as pd\n",
    "import plotly.express as px\n",
    "import plotly.graph_objects as go"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "175e3872-4883-4b34-8a40-821ec82e6942",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Flight Number</th>\n",
       "      <th>Date</th>\n",
       "      <th>Time (UTC)</th>\n",
       "      <th>Booster Version</th>\n",
       "      <th>Launch Site</th>\n",
       "      <th>Payload</th>\n",
       "      <th>Payload Mass (kg)</th>\n",
       "      <th>Orbit</th>\n",
       "      <th>Customer</th>\n",
       "      <th>Landing Outcome</th>\n",
       "      <th>class</th>\n",
       "      <th>Lat</th>\n",
       "      <th>Long</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2010-06-04</td>\n",
       "      <td>18:45:00</td>\n",
       "      <td>F9 v1.0  B0003</td>\n",
       "      <td>CCAFS LC-40</td>\n",
       "      <td>Dragon Spacecraft Qualification Unit</td>\n",
       "      <td>0.0</td>\n",
       "      <td>LEO</td>\n",
       "      <td>SpaceX</td>\n",
       "      <td>Failure   (parachute)</td>\n",
       "      <td>0</td>\n",
       "      <td>28.562302</td>\n",
       "      <td>-80.577356</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>2010-12-08</td>\n",
       "      <td>15:43:00</td>\n",
       "      <td>F9 v1.0  B0004</td>\n",
       "      <td>CCAFS LC-40</td>\n",
       "      <td>Dragon demo flight C1, two CubeSats,  barrel o...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>LEO (ISS)</td>\n",
       "      <td>NASA (COTS) NRO</td>\n",
       "      <td>Failure   (parachute)</td>\n",
       "      <td>0</td>\n",
       "      <td>28.562302</td>\n",
       "      <td>-80.577356</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>2012-05-22</td>\n",
       "      <td>7:44:00</td>\n",
       "      <td>F9 v1.0  B0005</td>\n",
       "      <td>CCAFS LC-40</td>\n",
       "      <td>Dragon demo flight C2+</td>\n",
       "      <td>525.0</td>\n",
       "      <td>LEO (ISS)</td>\n",
       "      <td>NASA (COTS)</td>\n",
       "      <td>No attempt</td>\n",
       "      <td>0</td>\n",
       "      <td>28.562302</td>\n",
       "      <td>-80.577356</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>2012-10-08</td>\n",
       "      <td>0:35:00</td>\n",
       "      <td>F9 v1.0  B0006</td>\n",
       "      <td>CCAFS LC-40</td>\n",
       "      <td>SpaceX CRS-1</td>\n",
       "      <td>500.0</td>\n",
       "      <td>LEO (ISS)</td>\n",
       "      <td>NASA (CRS)</td>\n",
       "      <td>No attempt</td>\n",
       "      <td>0</td>\n",
       "      <td>28.562302</td>\n",
       "      <td>-80.577356</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>2013-03-01</td>\n",
       "      <td>15:10:00</td>\n",
       "      <td>F9 v1.0  B0007</td>\n",
       "      <td>CCAFS LC-40</td>\n",
       "      <td>SpaceX CRS-2</td>\n",
       "      <td>677.0</td>\n",
       "      <td>LEO (ISS)</td>\n",
       "      <td>NASA (CRS)</td>\n",
       "      <td>No attempt</td>\n",
       "      <td>0</td>\n",
       "      <td>28.562302</td>\n",
       "      <td>-80.577356</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Flight Number        Date Time (UTC) Booster Version  Launch Site  \\\n",
       "0              1  2010-06-04   18:45:00  F9 v1.0  B0003  CCAFS LC-40   \n",
       "1              2  2010-12-08   15:43:00  F9 v1.0  B0004  CCAFS LC-40   \n",
       "2              3  2012-05-22    7:44:00  F9 v1.0  B0005  CCAFS LC-40   \n",
       "3              4  2012-10-08    0:35:00  F9 v1.0  B0006  CCAFS LC-40   \n",
       "4              5  2013-03-01   15:10:00  F9 v1.0  B0007  CCAFS LC-40   \n",
       "\n",
       "                                             Payload  Payload Mass (kg)  \\\n",
       "0               Dragon Spacecraft Qualification Unit                0.0   \n",
       "1  Dragon demo flight C1, two CubeSats,  barrel o...                0.0   \n",
       "2                             Dragon demo flight C2+              525.0   \n",
       "3                                       SpaceX CRS-1              500.0   \n",
       "4                                       SpaceX CRS-2              677.0   \n",
       "\n",
       "       Orbit         Customer        Landing Outcome  class        Lat  \\\n",
       "0        LEO           SpaceX  Failure   (parachute)      0  28.562302   \n",
       "1  LEO (ISS)  NASA (COTS) NRO  Failure   (parachute)      0  28.562302   \n",
       "2  LEO (ISS)      NASA (COTS)             No attempt      0  28.562302   \n",
       "3  LEO (ISS)       NASA (CRS)             No attempt      0  28.562302   \n",
       "4  LEO (ISS)       NASA (CRS)             No attempt      0  28.562302   \n",
       "\n",
       "        Long  \n",
       "0 -80.577356  \n",
       "1 -80.577356  \n",
       "2 -80.577356  \n",
       "3 -80.577356  \n",
       "4 -80.577356  "
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "URL = 'https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBM-DS0321EN-SkillsNetwork/datasets/spacex_launch_geo.csv'\n",
    "\n",
    "df_spacex = pd.read_csv(URL)\n",
    "\n",
    "min_payload = int(df_spacex['Payload Mass (kg)'].min())\n",
    "max_payload = int(df_spacex['Payload Mass (kg)'].max())\n",
    "\n",
    "df_spacex.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "6fd30282-634a-4b52-a4f9-f99df10c5c74",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_mod = df_spacex.loc[df_spacex['Booster Version'].str.contains('v1.1')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "119ed945-4fdb-4bf0-ac8a-0022509a942b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2534.6666666666665"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_mod['Payload Mass (kg)'].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "22d8e504-7fd5-4203-a9f6-d6ac5eb193d2",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# dropdown menu to choose from the various sites:\n",
    "app = Dash(__name__)\n",
    "\n",
    "app.layout = html.Div(children = [\n",
    "        html.H1('SpaceX Launch Records Dashboard', \n",
    "                style = {'textAlign': 'center',\n",
    "                         'color': 'black',\n",
    "                         'font-size': 24}),\n",
    "        html.P('Dropdown:'),\n",
    "        dcc.Dropdown(id = 'site-dropdown',\n",
    "                     options = [{'label': 'All Sites',    'value': 'ALL'},\n",
    "                                {'label': 'CCAFS SCL-40', 'value': 'CCAFS SLC-40'},\n",
    "                                {'label': 'CCAFS LC-40',  'value': 'CCAFS LC-40'},\n",
    "                                {'label': 'VAFB SLC-4E',  'value': 'VAFB SLC-4E'},\n",
    "                                {'label': 'KSC LC-39A',   'value': 'KSC LC-39A'}],\n",
    "                                value = 'ALL',\n",
    "                                placeholder = 'Select a site',\n",
    "                                searchable = True),\n",
    "        html.Br(),\n",
    "        dcc.Graph(id = 'pie-chart'),\n",
    "        html.Br(),\n",
    "        html.P('Payload range slider (kg):'),\n",
    "        dcc.RangeSlider(id = 'payload-slider', \n",
    "                        min = min_payload,\n",
    "                        max = max_payload,\n",
    "                        step = 1500,\n",
    "                        marks = {min_payload: str(min_payload),\n",
    "                                1500: '1500',\n",
    "                                3000: '3000',\n",
    "                                4500: '4500',\n",
    "                                6000: '6000',\n",
    "                                7500: '7500',\n",
    "                                9000: '9000',\n",
    "                                max_payload: str(max_payload)},\n",
    "                        value = [min_payload, max_payload]),\n",
    "        html.Br(),\n",
    "        dcc.Graph(id = 'payload-scatter-chart')\n",
    "                                    ])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e7ffd28b-896e-4ba7-9d1f-3f1404fecd76",
   "metadata": {},
   "source": [
    "Through adding the callback function, Dash will automatically be called and the output will be varied depending on what the user inputs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "01e8060e-83bc-4ba4-935f-ff130e7c5892",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Dash is running on http://127.0.0.1:8050/\n",
      "\n",
      " * Serving Flask app '__main__' (lazy loading)\n",
      " * Environment: production\n",
      "\u001b[31m   WARNING: This is a development server. Do not use it in a production deployment.\u001b[0m\n",
      "\u001b[2m   Use a production WSGI server instead.\u001b[0m\n",
      " * Debug mode: on\n"
     ]
    }
   ],
   "source": [
    "# function decorator to specify function input and output\n",
    "@app.callback(Output('pie-chart', 'figure'),\n",
    "              Input('site-dropdown', 'value'))\n",
    "\n",
    "def get_pie_chart(entered_site):\n",
    "    if entered_site == 'ALL':\n",
    "        fig = px.pie(df_spacex, values = 'class', names = 'Launch Site',\n",
    "                     title = 'Successful Launch Distribution by Site')\n",
    "    else:\n",
    "        # choose the rows that have the same launch site as the one entered\n",
    "        df_filtered = df_spacex.loc[df_spacex['Launch Site'] == entered_site]\n",
    "        \n",
    "        fig = px.pie(df_filtered, names = 'class',\n",
    "                     title = 'Launch Distribution for ' + entered_site)\n",
    "    return fig\n",
    "\n",
    "@app.callback(Output('payload-scatter-chart', 'figure'),\n",
    "              [Input('site-dropdown', 'value'),\n",
    "               Input('payload-slider', 'value')])\n",
    "\n",
    "def get_scatter_chart(entered_site, payload):\n",
    "    # expand equals True to return a data frame\n",
    "    # with seperated strings in different columns\n",
    "    df_split = df_spacex['Booster Version'].str.split(' ', expand = True)\n",
    "\n",
    "    df_mod = df_spacex.drop(columns = ['Booster Version'], inplace = False)\n",
    "    # save the splitted column in the modified data frame\n",
    "    df_mod['Booster Version'] = df_split[1]\n",
    "    # based on the input payload range choose the corresponding rows\n",
    "    df_mod = df_mod.loc[df_mod['Payload Mass (kg)'].between(payload[0], payload[1])]\n",
    "\n",
    "    if entered_site == 'ALL':\n",
    "        fig = px.scatter(df_mod,\n",
    "                         x = 'Payload Mass (kg)', \n",
    "                         y = 'class',\n",
    "                         color = 'Booster Version',\n",
    "                         hover_data = ['Booster Version']) \n",
    "    else:\n",
    "        df_filtered = df_mod.loc[df_mod['Launch Site'] == entered_site]\n",
    "        \n",
    "        fig = px.scatter(df_filtered,\n",
    "                         x = 'Payload Mass (kg)', \n",
    "                         y = 'class',\n",
    "                         color = 'Booster Version',\n",
    "                         hover_data = ['Booster Version'])         \n",
    "    return fig\n",
    "    \n",
    "if __name__ == '__main__':\n",
    "    app.run_server(debug = True, use_reloader = False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f7e6e25d-bc80-470d-8ba4-0b88dcef27d4",
   "metadata": {},
   "source": [
    "1. Which site has the most successful launches?\n",
    "2. Which site has the highest launch success rate?\n",
    "3. Which payload range(s) has the highest launch success rate?\n",
    "4. Which payload range(s) has the lowest launch success rate?\n",
    "5. Which F9 booster version has the highest launch success rate?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "063f0a8b-75db-460a-a417-977da7a4e953",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Payload range: [0, 4000]\n",
      "class\n",
      "0    18\n",
      "1    16\n",
      "dtype: int64\n",
      "Success rate is 47.0 %\n",
      "Payload range: [4000, 6000]\n",
      "class\n",
      "0    8\n",
      "1    5\n",
      "dtype: int64\n",
      "Success rate is 38.0 %\n",
      "Payload range: [6000, 10000]\n",
      "class\n",
      "0    6\n",
      "1    3\n",
      "dtype: int64\n",
      "Success rate is 33.0 %\n"
     ]
    }
   ],
   "source": [
    "payload_range = [[0, 4000], [4000, 6000], [6000, 10000]]\n",
    "\n",
    "for i in payload_range:\n",
    "    class_distrib = df_spacex[df_spacex['Payload Mass (kg)'].between(i[0], i[1])].value_counts('class')\n",
    "    print('Payload range: ' + str(i))\n",
    "    print(class_distrib)\n",
    "    print('Success rate is ' + str(100*round(class_distrib[1]/(class_distrib[0]+class_distrib[1]), 2)) + ' %')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "631f0488-39b7-4143-93f8-ee7dfc787359",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Booster version: v1.0\n",
      "class\n",
      "0    5\n",
      "dtype: int64\n",
      "Booster version: v1.1\n",
      "class\n",
      "0    14\n",
      "1     1\n",
      "dtype: int64\n",
      "Booster version: FT\n",
      "class\n",
      "1    16\n",
      "0     8\n",
      "dtype: int64\n",
      "Booster version: B4\n",
      "class\n",
      "1    6\n",
      "0    5\n",
      "dtype: int64\n",
      "Booster version: B5\n",
      "class\n",
      "1    1\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "df_split = df_spacex['Booster Version'].str.split(' ', expand = True)\n",
    "df_mod = df_spacex.drop(columns = ['Booster Version'], inplace = False)\n",
    "# save the splitted column in the modified data frame\n",
    "df_mod['Booster Version'] = df_split[1]\n",
    "    \n",
    "booster_version = df_mod['Booster Version'].unique()\n",
    "\n",
    "for i in booster_version:\n",
    "    print('Booster version: ' + i)\n",
    "    class_distrib = df_mod[df_mod['Booster Version'] == i].value_counts('class')\n",
    "    print(class_distrib)\n",
    "    #print('Success rate is ' + str(class_distrib[1]/(class_distrib[0] + class_distrib[1])) + ' %')"
   ]
  }
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