Browse Source

Reorganized notebooks

WillKoehrsen 6 years ago
parent
commit
58a94cc802
3 changed files with 0 additions and 189 deletions
  1. 0 0
      example_notebook/Untitled09.ipynb
  2. 0 6
      stocker/exploratory work.ipynb
  3. 0 183
      stocker/modeling work.ipynb

example_notebook/modeling_work.ipynb → example_notebook/Untitled09.ipynb


+ 0 - 6
stocker/exploratory work.ipynb

@@ -1,6 +0,0 @@
-{
- "cells": [],
- "metadata": {},
- "nbformat": 4,
- "nbformat_minor": 2
-}

+ 0 - 183
stocker/modeling work.ipynb

@@ -1,183 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Introduction\n",
-    "State notebook purpose here"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Imports\n",
-    "Import libraries and write settings here."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-03-01T13:36:37.852969Z",
-     "start_time": "2019-03-01T13:36:37.811429Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<script type=\"text/javascript\">window.PlotlyConfig = {MathJaxConfig: 'local'};</script><script type=\"text/javascript\">if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}</script><script>requirejs.config({paths: { 'plotly': ['https://cdn.plot.ly/plotly-latest.min']},});if(!window._Plotly) {require(['plotly'],function(plotly) {window._Plotly=plotly;});}</script>"
-      ],
-      "text/vnd.plotly.v1+html": [
-       "<script type=\"text/javascript\">window.PlotlyConfig = {MathJaxConfig: 'local'};</script><script type=\"text/javascript\">if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}</script><script>requirejs.config({paths: { 'plotly': ['https://cdn.plot.ly/plotly-latest.min']},});if(!window._Plotly) {require(['plotly'],function(plotly) {window._Plotly=plotly;});}</script>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<script type=\"text/javascript\">window.PlotlyConfig = {MathJaxConfig: 'local'};</script><script type=\"text/javascript\">if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}</script><script>requirejs.config({paths: { 'plotly': ['https://cdn.plot.ly/plotly-latest.min']},});if(!window._Plotly) {require(['plotly'],function(plotly) {window._Plotly=plotly;});}</script>"
-      ],
-      "text/vnd.plotly.v1+html": [
-       "<script type=\"text/javascript\">window.PlotlyConfig = {MathJaxConfig: 'local'};</script><script type=\"text/javascript\">if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}</script><script>requirejs.config({paths: { 'plotly': ['https://cdn.plot.ly/plotly-latest.min']},});if(!window._Plotly) {require(['plotly'],function(plotly) {window._Plotly=plotly;});}</script>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "# Data manipulation\n",
-    "import pandas as pd\n",
-    "import numpy as np\n",
-    "\n",
-    "# Options for pandas\n",
-    "pd.options.display.max_columns = 50\n",
-    "pd.options.display.max_rows = 30\n",
-    "\n",
-    "# Display all cell outputs\n",
-    "from IPython.core.interactiveshell import InteractiveShell\n",
-    "InteractiveShell.ast_node_interactivity = 'all'\n",
-    "\n",
-    "from IPython import get_ipython\n",
-    "ipython = get_ipython()\n",
-    "\n",
-    "# autoreload extension\n",
-    "if 'autoreload' not in ipython.extension_manager.loaded:\n",
-    "    %load_ext autoreload\n",
-    "\n",
-    "%autoreload 2\n",
-    "\n",
-    "# Visualizations\n",
-    "import plotly.plotly as py\n",
-    "import plotly.graph_objs as go\n",
-    "from plotly.offline import iplot, init_notebook_mode\n",
-    "init_notebook_mode(connected=True)\n",
-    "\n",
-    "import cufflinks as cf\n",
-    "cf.go_offline(connected=True)\n",
-    "cf.set_config_file(theme='white')"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Analysis/Modeling\n",
-    "Do work here"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Results\n",
-    "Show graphs and stats here"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Conclusions and Next Steps\n",
-    "Summarize findings here"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "hide_input": false,
-  "kernelspec": {
-   "display_name": "Python 3",
-   "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": "3.6.5"
-  },
-  "toc": {
-   "base_numbering": 1,
-   "nav_menu": {},
-   "number_sections": true,
-   "sideBar": true,
-   "skip_h1_title": false,
-   "title_cell": "Table of Contents",
-   "title_sidebar": "Contents",
-   "toc_cell": false,
-   "toc_position": {},
-   "toc_section_display": true,
-   "toc_window_display": false
-  },
-  "varInspector": {
-   "cols": {
-    "lenName": 16,
-    "lenType": 16,
-    "lenVar": 40
-   },
-   "kernels_config": {
-    "python": {
-     "delete_cmd_postfix": "",
-     "delete_cmd_prefix": "del ",
-     "library": "var_list.py",
-     "varRefreshCmd": "print(var_dic_list())"
-    },
-    "r": {
-     "delete_cmd_postfix": ") ",
-     "delete_cmd_prefix": "rm(",
-     "library": "var_list.r",
-     "varRefreshCmd": "cat(var_dic_list()) "
-    }
-   },
-   "types_to_exclude": [
-    "module",
-    "function",
-    "builtin_function_or_method",
-    "instance",
-    "_Feature"
-   ],
-   "window_display": false
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}