Ford_Go_Bike_Presentation_Slide.ipynb

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   "source": [
    "# Ford_Go_Bike Trip Duration vs User Type and Week Days\n",
    "## by Uzedu Omoyemen Frances"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Investigation Overview\n",
    "\n",
    "\n",
    "> In this dataset investigation, I looked at the Bike Trip duration how it cuts across the user types and also against different days of the week. The main variables of interest were the Trip duration, user type, and days of the week the bike was rented.  \n",
    "\n",
    "\n",
    "## Dataset Overview\n",
    "\n",
    "> This data set includes information about individual rides made in a bike-sharing system covering the greater San Francisco Bay area. This dataset contains about 184,000 entries and includes variables such as Bike trip duration, User type, gender, start time, end time, End Station Latitude, End Station Longitude, Start Station Latitude, Start Station Longitude and after some cleaning process was carried out 174,000 rows were left."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
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   "outputs": [],
   "source": [
    "# import all packages and set plots to be embedded inline\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sb\n",
    "\n",
    "%matplotlib inline\n",
    "\n",
    "# suppress warnings from final output\n",
    "import warnings\n",
    "warnings.simplefilter(\"ignore\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>duration_sec</th>\n",
       "      <th>start_time</th>\n",
       "      <th>end_time</th>\n",
       "      <th>start_station_id</th>\n",
       "      <th>start_station_name</th>\n",
       "      <th>start_station_latitude</th>\n",
       "      <th>start_station_longitude</th>\n",
       "      <th>end_station_id</th>\n",
       "      <th>end_station_name</th>\n",
       "      <th>end_station_latitude</th>\n",
       "      <th>end_station_longitude</th>\n",
       "      <th>bike_id</th>\n",
       "      <th>user_type</th>\n",
       "      <th>member_birth_year</th>\n",
       "      <th>member_gender</th>\n",
       "      <th>bike_share_for_all_trip</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>52185</td>\n",
       "      <td>2019-02-28 17:32:10.1450</td>\n",
       "      <td>2019-03-01 08:01:55.9750</td>\n",
       "      <td>21.0</td>\n",
       "      <td>Montgomery St BART Station (Market St at 2nd St)</td>\n",
       "      <td>37.789625</td>\n",
       "      <td>-122.400811</td>\n",
       "      <td>13.0</td>\n",
       "      <td>Commercial St at Montgomery St</td>\n",
       "      <td>37.794231</td>\n",
       "      <td>-122.402923</td>\n",
       "      <td>4902</td>\n",
       "      <td>Customer</td>\n",
       "      <td>1984.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>42521</td>\n",
       "      <td>2019-02-28 18:53:21.7890</td>\n",
       "      <td>2019-03-01 06:42:03.0560</td>\n",
       "      <td>23.0</td>\n",
       "      <td>The Embarcadero at Steuart St</td>\n",
       "      <td>37.791464</td>\n",
       "      <td>-122.391034</td>\n",
       "      <td>81.0</td>\n",
       "      <td>Berry St at 4th St</td>\n",
       "      <td>37.775880</td>\n",
       "      <td>-122.393170</td>\n",
       "      <td>2535</td>\n",
       "      <td>Customer</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>61854</td>\n",
       "      <td>2019-02-28 12:13:13.2180</td>\n",
       "      <td>2019-03-01 05:24:08.1460</td>\n",
       "      <td>86.0</td>\n",
       "      <td>Market St at Dolores St</td>\n",
       "      <td>37.769305</td>\n",
       "      <td>-122.426826</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Powell St BART Station (Market St at 4th St)</td>\n",
       "      <td>37.786375</td>\n",
       "      <td>-122.404904</td>\n",
       "      <td>5905</td>\n",
       "      <td>Customer</td>\n",
       "      <td>1972.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>36490</td>\n",
       "      <td>2019-02-28 17:54:26.0100</td>\n",
       "      <td>2019-03-01 04:02:36.8420</td>\n",
       "      <td>375.0</td>\n",
       "      <td>Grove St at Masonic Ave</td>\n",
       "      <td>37.774836</td>\n",
       "      <td>-122.446546</td>\n",
       "      <td>70.0</td>\n",
       "      <td>Central Ave at Fell St</td>\n",
       "      <td>37.773311</td>\n",
       "      <td>-122.444293</td>\n",
       "      <td>6638</td>\n",
       "      <td>Subscriber</td>\n",
       "      <td>1989.0</td>\n",
       "      <td>Other</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1585</td>\n",
       "      <td>2019-02-28 23:54:18.5490</td>\n",
       "      <td>2019-03-01 00:20:44.0740</td>\n",
       "      <td>7.0</td>\n",
       "      <td>Frank H Ogawa Plaza</td>\n",
       "      <td>37.804562</td>\n",
       "      <td>-122.271738</td>\n",
       "      <td>222.0</td>\n",
       "      <td>10th Ave at E 15th St</td>\n",
       "      <td>37.792714</td>\n",
       "      <td>-122.248780</td>\n",
       "      <td>4898</td>\n",
       "      <td>Subscriber</td>\n",
       "      <td>1974.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
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      "text/plain": [
       "   duration_sec                start_time                  end_time  \\\n",
       "0         52185  2019-02-28 17:32:10.1450  2019-03-01 08:01:55.9750   \n",
       "1         42521  2019-02-28 18:53:21.7890  2019-03-01 06:42:03.0560   \n",
       "2         61854  2019-02-28 12:13:13.2180  2019-03-01 05:24:08.1460   \n",
       "3         36490  2019-02-28 17:54:26.0100  2019-03-01 04:02:36.8420   \n",
       "4          1585  2019-02-28 23:54:18.5490  2019-03-01 00:20:44.0740   \n",
       "\n",
       "   start_station_id                                start_station_name  \\\n",
       "0              21.0  Montgomery St BART Station (Market St at 2nd St)   \n",
       "1              23.0                     The Embarcadero at Steuart St   \n",
       "2              86.0                           Market St at Dolores St   \n",
       "3             375.0                           Grove St at Masonic Ave   \n",
       "4               7.0                               Frank H Ogawa Plaza   \n",
       "\n",
       "   start_station_latitude  start_station_longitude  end_station_id  \\\n",
       "0               37.789625              -122.400811            13.0   \n",
       "1               37.791464              -122.391034            81.0   \n",
       "2               37.769305              -122.426826             3.0   \n",
       "3               37.774836              -122.446546            70.0   \n",
       "4               37.804562              -122.271738           222.0   \n",
       "\n",
       "                               end_station_name  end_station_latitude  \\\n",
       "0                Commercial St at Montgomery St             37.794231   \n",
       "1                            Berry St at 4th St             37.775880   \n",
       "2  Powell St BART Station (Market St at 4th St)             37.786375   \n",
       "3                        Central Ave at Fell St             37.773311   \n",
       "4                         10th Ave at E 15th St             37.792714   \n",
       "\n",
       "   end_station_longitude  bike_id   user_type  member_birth_year  \\\n",
       "0            -122.402923     4902    Customer             1984.0   \n",
       "1            -122.393170     2535    Customer                NaN   \n",
       "2            -122.404904     5905    Customer             1972.0   \n",
       "3            -122.444293     6638  Subscriber             1989.0   \n",
       "4            -122.248780     4898  Subscriber             1974.0   \n",
       "\n",
       "  member_gender bike_share_for_all_trip  \n",
       "0          Male                      No  \n",
       "1           NaN                      No  \n",
       "2          Male                      No  \n",
       "3         Other                      No  \n",
       "4          Male                     Yes  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# load in the dataset into a pandas dataframe\n",
    "df=pd.read_csv('fordgobike_data.csv')\n",
    "df.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "df.drop(['start_station_latitude','start_station_longitude', 'end_station_latitude', 'end_station_longitude', 'bike_share_for_all_trip'], axis=1, inplace=True)\n",
    "df.dropna(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "df['age']= 2019 - df['member_birth_year']\n",
    "bins=[18,30,60,140]\n",
    "labels=['Youths (18-30)', 'Middle-aged (31-60)', 'Oldies (60+)']\n",
    "df['age_group']=pd.cut(df['age'], bins=bins, labels=labels)\n",
    "\n",
    "\n",
    "df['start_time'] = pd.to_datetime(df['start_time'])\n",
    "df['start_day']=df['start_time'].dt.day_name()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "order=['Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday', 'Saturday', 'Sunday']\n",
    "\n",
    "week_class=pd.api.types.CategoricalDtype(ordered=True, categories=order)\n",
    "df['start_day']=df['start_day'].astype(week_class)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "df['duration_min']=df['duration_sec'] / 60"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "> Note that the above cells have been set as \"Skip\"-type slides. That means\n",
    "that when the notebook is rendered as http slides, those cells won't show up."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Distribution of Bike Trips Duration in seconds\n",
    "\n",
    "Time spent on a trip for most rides was about 10 minutes (600 seconds)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "logsize=0.1\n",
    "bins = 10**np.arange(0, 5+logsize, logsize)\n",
    "sb.set_theme(style=\"darkgrid\")\n",
    "plt.figure(figsize=[8,6])\n",
    "ticks=[100,300,600,1000,3000,10000]\n",
    "labels=['{}'. format (v) for v in ticks]\n",
    "plt.hist(data = df, x = 'duration_sec', bins = bins)\n",
    "plt.xscale('log')\n",
    "plt.xlim([50,10000])\n",
    "plt.xticks(ticks, labels)\n",
    "plt.xlabel('Bike Duration in Seconds')\n",
    "plt.ylabel('Frequency')\n",
    "plt.title('Distribution of various Bike Trip Duration');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Distribution of User Type\n",
    " We have more subscribers than customers. The customers are temporary or one-time users while subscribers are members or frequent users."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(5,6))\n",
    "sb.set_theme(style=\"darkgrid\")\n",
    "base=sb.color_palette()[0]\n",
    "sb.countplot(data=df, x='user_type', color=base)\n",
    "plt.xlabel('User Type')\n",
    "plt.ylabel('Frequency')\n",
    "plt.title('User Type Distribution');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Distribution of Days bikes were rented\n",
    "Most trips were taken during the week especially Thursdays and Tuesdays unlike weekend."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(9,7))\n",
    "sb.set_theme(style=\"darkgrid\")\n",
    "sb.countplot(data=df, x='start_day', color=base)\n",
    "plt.title('Distribution across Days of the week')\n",
    "plt.xlabel('Days')\n",
    "plt.ylabel('Frequency');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Distribution of Bike trip vs User Type\n",
    "Although we have more subscribers, customers on a average tend to spend more time on trips with an average of about 24 minutes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "customer_mean=df.query('user_type == \"Customer\"').duration_min.mean()\n",
    "subscriber_mean=df.query('user_type == \"Subscriber\"').duration_min.mean()\n",
    "\n",
    "plt.figure(figsize=(6,6))\n",
    "plt.bar(['Customer', 'Subscriber'], [customer_mean, subscriber_mean])\n",
    "sb.set_theme(style=\"darkgrid\")\n",
    "plt.title('Average trip duration across the User Type')\n",
    "plt.yticks([0,4,8,12,16,20,24], [0,4,8,12,16,20,24])\n",
    "#plt.ylim(0,25)\n",
    "plt.xlabel('User Type')\n",
    "plt.ylabel('Trip Duration in minutes');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Distribution of Bike trips vs Days of the week\n",
    "More time was spent on trips during the weekends unlike the weekedays"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,7))\n",
    "sb.set_theme(style=\"darkgrid\")\n",
    "sb.boxplot(data=df, x='start_day', y='duration_min', color=base)\n",
    "plt.ylim(0,35)\n",
    "plt.title('Trip Duration Across Days of the week')\n",
    "plt.xlabel('Days of the week')\n",
    "plt.ylabel('Trip Duration (mins)');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Distribution of Bike trip vs User type vs Days of the week\n",
    "Customers generally travel long distance especially during weekends, whereas the subscribers take short journeys regardless of what day of the week it is."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8,6))\n",
    "sb.set_theme(style=\"darkgrid\")\n",
    "sb.pointplot(data = df, x = 'start_day', y = 'duration_min', hue = 'user_type', palette = 'Reds', dodge = 0.3, linestyles = \"\")\n",
    "plt.ylabel('Trip Duration(mins)')\n",
    "plt.xlabel('Days of the week')\n",
    "plt.ylim(5,35)\n",
    "plt.suptitle('Trip Duration vs WeekDays vs UserType')\n",
    "plt.legend(title='User Type');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "### Generate Slideshow\n",
    "Once you're ready to generate your slideshow, use the `jupyter nbconvert` command to generate the HTML slide show.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[NbConvertApp] WARNING | Config option `kernel_spec_manager_class` not recognized by `NbConvertApp`.\n",
      "[NbConvertApp] Converting notebook Ford_Go_Bike_Presentation_Slide.ipynb to slides\n",
      "[NbConvertApp] Writing 708146 bytes to Ford_Go_Bike_Presentation_Slide.slides.html\n",
      "[NbConvertApp] Redirecting reveal.js requests to https://cdnjs.cloudflare.com/ajax/libs/reveal.js/3.5.0\n",
      "Traceback (most recent call last):\n",
      "  File \"C:\\Users\\USER\\anaconda3\\Scripts\\jupyter-nbconvert-script.py\", line 10, in <module>\n",
      "    sys.exit(main())\n",
      "  File \"C:\\Users\\USER\\anaconda3\\lib\\site-packages\\jupyter_core\\application.py\", line 269, in launch_instance\n",
      "    return super().launch_instance(argv=argv, **kwargs)\n",
      "  File \"C:\\Users\\USER\\anaconda3\\lib\\site-packages\\traitlets\\config\\application.py\", line 846, in launch_instance\n",
      "    app.start()\n",
      "  File \"C:\\Users\\USER\\anaconda3\\lib\\site-packages\\nbconvert\\nbconvertapp.py\", line 369, in start\n",
      "    self.convert_notebooks()\n",
      "  File \"C:\\Users\\USER\\anaconda3\\lib\\site-packages\\nbconvert\\nbconvertapp.py\", line 541, in convert_notebooks\n",
      "    self.convert_single_notebook(notebook_filename)\n",
      "  File \"C:\\Users\\USER\\anaconda3\\lib\\site-packages\\nbconvert\\nbconvertapp.py\", line 508, in convert_single_notebook\n",
      "    self.postprocess_single_notebook(write_results)\n",
      "  File \"C:\\Users\\USER\\anaconda3\\lib\\site-packages\\nbconvert\\nbconvertapp.py\", line 480, in postprocess_single_notebook\n",
      "    self.postprocessor(write_results)\n",
      "  File \"C:\\Users\\USER\\anaconda3\\lib\\site-packages\\nbconvert\\postprocessors\\base.py\", line 28, in __call__\n",
      "    self.postprocess(input)\n",
      "  File \"C:\\Users\\USER\\anaconda3\\lib\\site-packages\\nbconvert\\postprocessors\\serve.py\", line 90, in postprocess\n",
      "    http_server.listen(self.port, address=self.ip)\n",
      "  File \"C:\\Users\\USER\\anaconda3\\lib\\site-packages\\tornado\\tcpserver.py\", line 151, in listen\n",
      "    sockets = bind_sockets(port, address=address)\n",
      "  File \"C:\\Users\\USER\\anaconda3\\lib\\site-packages\\tornado\\netutil.py\", line 161, in bind_sockets\n",
      "    sock.bind(sockaddr)\n",
      "OSError: [WinError 10048] Only one usage of each socket address (protocol/network address/port) is normally permitted\n"
     ]
    }
   ],
   "source": [
    "# Use this command if you are running this file in local\n",
    "!jupyter nbconvert Ford_Go_Bike_Presentation_Slide.ipynb --to slides --post serve --no-input --no-prompt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "celltoolbar": "Slideshow",
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}