Part_II_slide_deck_template.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Part II - Propser Loan Data\n",
    "## by Samson Amwata"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "\n",
    "## Investigation Overview\n",
    "\n",
    "\n",
    "I focused on key features that will answer the questions for my investigation. I started by showing the amount of loan loaned out and to find out if the Borrower Rate, Prosper rating and APR rate has effect on the amount of loan borrowed. Also I checked the correlation between different features\n",
    "\n",
    "\n",
    "## Dataset Overview\n",
    "\n",
    "This dataset contains loan information of about 113,937 rows with 81 variables on each loan, including loan amount, borrower rate (or interest rate), current loan status, borrower income, and many others.\n",
    "\n",
    "I am looking forward to investigate the following questions\n",
    "\n",
    "- What factors affect a loan’s outcome status?\n",
    "- What affects the borrower’s APR or interest rate?\n",
    "- Are there differences between loans depending on how large the original loan amount was?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "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": [],
   "source": [
    "# load in the dataset into a pandas dataframe\n",
    "df = pd.read_csv(\"prosperLoanData.csv\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Borrowers Rate Vs Period\n",
    "The distribution of Borrower rate and Borrower APR looks multimodal. There is a peak centered at 0.2 and there is a very high increase between 0.35 and 0.36.\n",
    "The borrowers in 2011 got the highest interest rate compared to borrowers in 2005 who got the lowest interest rate\n"
   ]
  },
  {
   "attachments": {
    "image.png": {
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"
    }
   },
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Income Range Vs Borrower Rate\n",
    "We can see that borrowers rate has negative correlation with Income range where the Borrowers rate reduces with increased income rate. This means that the borrowers with high income range is having a lower interest rate which I think it is sales technique to allow high income earners to borrow more\n"
   ]
  },
  {
   "attachments": {
    "image-2.png": {
     "image/png": 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"
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    "![image-2.png](attachment:image-2.png)"
   ]
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    "## Loan Amount Vs Period\n",
    "\n",
    "We found that the amount of loans borrowered by year dropped off in 2009 and there was high number of loan amount in 2013 and increased steadily after 2009. The loan amount taken in 2013 might be affected by either inflation or other economic factors"
   ]
  },
  {
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     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Borrower rate Vs HomeOwner over time\n",
    "I wanted to check the relationship between Interest rate among borrowers with home and those without. I notice that the homeowners got lower interest rate in general throughout the years. We also have outliers on 2005 2006 2007 2008 and 2014. we might consider removing them if we decide to do predictive analysis\n"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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 Part_II_slide_deck_template.ipynb to slides\n",
      "[NbConvertApp] Writing 381504 bytes to Part_II_slide_deck_template.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\\samso\\Anaconda3\\envs\\altx_data\\Scripts\\jupyter-nbconvert-script.py\", line 9, in <module>\n",
      "    sys.exit(main())\n",
      "  File \"C:\\Users\\samso\\Anaconda3\\envs\\altx_data\\lib\\site-packages\\jupyter_core\\application.py\", line 269, in launch_instance\n",
      "    return super().launch_instance(argv=argv, **kwargs)\n",
      "  File \"C:\\Users\\samso\\Anaconda3\\envs\\altx_data\\lib\\site-packages\\traitlets\\config\\application.py\", line 846, in launch_instance\n",
      "    app.start()\n",
      "  File \"C:\\Users\\samso\\Anaconda3\\envs\\altx_data\\lib\\site-packages\\nbconvert\\nbconvertapp.py\", line 338, in start\n",
      "    self.convert_notebooks()\n",
      "  File \"C:\\Users\\samso\\Anaconda3\\envs\\altx_data\\lib\\site-packages\\nbconvert\\nbconvertapp.py\", line 508, in convert_notebooks\n",
      "    self.convert_single_notebook(notebook_filename)\n",
      "  File \"C:\\Users\\samso\\Anaconda3\\envs\\altx_data\\lib\\site-packages\\nbconvert\\nbconvertapp.py\", line 481, in convert_single_notebook\n",
      "    self.postprocess_single_notebook(write_results)\n",
      "  File \"C:\\Users\\samso\\Anaconda3\\envs\\altx_data\\lib\\site-packages\\nbconvert\\nbconvertapp.py\", line 453, in postprocess_single_notebook\n",
      "    self.postprocessor(write_results)\n",
      "  File \"C:\\Users\\samso\\Anaconda3\\envs\\altx_data\\lib\\site-packages\\nbconvert\\postprocessors\\base.py\", line 28, in __call__\n",
      "    self.postprocess(input)\n",
      "  File \"C:\\Users\\samso\\Anaconda3\\envs\\altx_data\\lib\\site-packages\\nbconvert\\postprocessors\\serve.py\", line 90, in postprocess\n",
      "    http_server.listen(self.port, address=self.ip)\n",
      "  File \"C:\\Users\\samso\\Anaconda3\\envs\\altx_data\\lib\\site-packages\\tornado\\tcpserver.py\", line 151, in listen\n",
      "    sockets = bind_sockets(port, address=address)\n",
      "  File \"C:\\Users\\samso\\Anaconda3\\envs\\altx_data\\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": [
    "!jupyter nbconvert Part_II_slide_deck_template.ipynb --to slides --post serve --no-input --no-prompt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "> This should open a tab in your web browser where you can scroll through your presentation. Sub-slides can be accessed by pressing 'down' when viewing its parent slide. Make sure you remove all of the quote-formatted guide notes like this one before you finish your presentation! At last, you can stop the Kernel. "
   ]
  },
  {
   "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": "3.8.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}